ABSTRACT. Smart port development and new technological mobilization are new managerial practices and solutions port administrations have adopted to improve port performance, since they enable customized value-added services and intelligent integrated operation. In this context, port authorities must invest in new technologies, innovative solutions in line with their budget, capacity, and challenges. This article presents an exhaustive scientific literature review of smart technologies mobilized in the context of a smart port and classifies these technologies into 10 families. This article provides port authorities and the scientific community with a toolbox that lists all innovative technologies deployed in a smart port.

ABSTRACT. With the growth of the maritime industry, which is a key sector for many supply chains worldwide, ports are looking to increase their capacity and performance in order to meet the challenges and opportunities created by the increased demand. Among various possible avenues, port expansion is one approach to achieving the objective of increased capacity, but requires significant resources and careful planning. Before undertaking a project of this scale, it is important to have a good understanding of the port’s current capacity as well as the requirements and limitations of an expansion project based on historical data and future forecasts. The objective of the research project presented in this paper is to develop a methodology for predicting bottlenecks and evaluating capacity in the context of a port expansion project. Moreover, the proposed methodology addresses the particular case of ports with limited visibility and data on their operations, which constitutes an additional challenge for port organizations. With the use of a quantitative approach based on discrete-event simulation, the proposed methodology is applied to the case study of a Canadian port.

ABSTRACT. Some global drivers of the shipping market, such as the carriers’ alliance consolidation process, the growing ship sizes and the advanced bridge between sea and land, have determined critical conditions on standalone ports. The traditional attitude of ports was to consider other ports as competitors following the hidden postulate of the natural monopoly of access to a territory. However, the necessity to respond to the binding request of port users and of the ship gigantism brought to different experiences between ports of the same territorial system. New forms of cooperation and competition took place in different levels. The paper presents a theoretical equilibrium model to analyse the competition and/or cooperation scenarios of two, or more, ports belonging to a territorial system. The model is based on the consolidated topological-behavioural paradigm of Transportation System Models. The proposed equilibrium model allows to simulate the condition inside a port system, which moves from competition between ports to cooperation, within the same modelling framework. The model could provide to the port authorities, managers, planners and researchers a quantitative tool to understand the competition-cooperation scenarios and to define alternative strategies in relation to the decisions taken by other actors of the market.

ABSTRACT. AI technologies' adoption is increasing in most industries, but their capabilities differ. With the utilization of AI, there is a potential to boost the maritime industry through higher commercial speed and better quality of services. Therefore, AI would be an opportunity to enhance efficiency in diverse aspects of port stakeholders' operations. To evaluate whether AI technologies and their benefits emerge, the consciousness of the costs and benefits of these innovations is essential. There is no cohesive framework concerning AI technologies' cost and benefit thus far. Therefore, this research fills in this gap in the existing literature. An exhaustive literature review is carried out, and a comprehensive framework is developed to identify the costs and benefits of AI technologies used in port operations. To validate this framework, a case study associated with ships' arrival process to the port of Antwerp is investigated. The case study demonstrates that even while a micro-level challenge is tackled through AI, other stakeholders who interact with the challenge owner also can enhance their operation. Moreover, the proof of benefits gained by initial challenge owners can stimulate similar companies to leverage the exact solution for overcoming their challenges.

ABSTRACT. In recent years digitalization has become a topic of great importance in the maritime and port sectors. All actors in this industry are experiencing a path of change, with the primary goal of pursuing technological innovation and a higher digital maturity level. Although there is a clear goal, many port actors are still doubtful on how to approach this journey and which strategies to use to face the awaiting challenges. Therefore, this research comes from the idea to help port actors to better define and understand their own position in relation to the current changes and offer them a tool to get inspiration to refine their level of digital maturity within the domain of their capabilities. The following study develops and applies a Digital Capability Maturity Model (DCMM). The model includes the main dimensions on which port actors can work on to strengthen their digital capability maturity. This tool was applied through a survey, in which 100 port actors participated (European mostly). The results show that none of the port actors already have a sufficiently advanced level of digital capability maturity, but all of them have approximately an intermediate level, thus requiring tailored recommendations to advance to the next level.

ABSTRACT. Assessing level of service offered by a railway station to passengers is a tedious job and hence it is essential to have a well-defined framework. This study emphasizes on calculating the passenger level of service (P-LOS) of a railway station using point-based system which takes qualitative and quantitative factors into account. With the proposed method, points for the potential factors were given by passengers through a questionnaire survey was considered for the analysis. Using the potential factors with highest ranking, P-LOS analysis was carried out and factors identified from the analysis were accessibility, safety and comfort. Threshold values of each selected factor were identified and applied to assess railway station level of service. Both platform and connections between platforms were considered for the analysis. Physical examination of each factor was also carried out to estimate the LOS score. After combining LOS scores of platforms and FOB, the overall score of the station was obtained. A P-LOS matrix representation containing four zones is proposed to depict the LOS scores obtained and further specific improvements and suggestions were provided. The proposed methodology is reliable, robust and easy to apply and acts as a template for calculating P-LOS for any railway station.

ABSTRACT. The use of information systems in the rail sector has recently accelerated thanks to increasing innovations in digitalization and information technology in different transport sectors. Thus, investments in systems such as traffic information can bring substantial social value to the users, particularly during traffic disruptions. Investments in an efficient sustainable and scalable traffic information system could be an important complement to infrastructure investments and maintenance activities. In this context, we review existing research on traffic information systems, their different effects and more importantly, the assessment of their social value. We focus on the case of disruptions in railway passenger traffic although many discussions are about more general transport situations. The reviewed literature reveals several studies on the valuation of traffic information to passengers under different travel situations. However, we conclude that such valuations are rarely used in the context of cost-benefit analysis for planning investments for traffic information systems.

ABSTRACT. With a route length of around 108 km, High Speed 1 (HS1) is the only high speed rail line in operation in the UK. This paper attempts to provide a socio-economic assessment of HS1, building on the earlier work of the author and of others. International services failed to attract the demand levels that were forecast and instead domestic passenger traffic has filled the capacity gap. However, the user benefits to these domestic passengers were less than that forecast for international passengers and as a result HS1 has failed to achieve a Benefit Cost Ratio in excess of unity, based on conventional transportation costs and benefits. This shortfall might be made up by regeneration benefits, as HS1 was specifically designed to stimulate economic activity in central and east London and in Kent. Some impacts in terms of land values can be detected, initially in central and east London, but subsequently spreading outwards to Kent. There is also some evidence of population gains but, like the changes in land values, these could be abstractive rather than generative. Moreover, evidence of increased productivity in terms of Gross Value Added per capita is difficult to find.

ABSTRACT. Analysis of the working situation for women in the railway industry needs in-depth study of the viewpoints expressed by both men and women which is understudied in the literature especially in developing countries. Employment of women in the railway industry of Iran has nearly doubled since 2006 and it provided an interesting case study for this aim. The authors developed a questionnaire to explore various aspects of employment including general features like salary and prestige as well as evaluating different perspectives for women employment. Data was derived from 289 filled out questionnaires which were distributed in a public and a private railway company. We conducted independent sample T-tests to see whether there is statistically significant difference in the judgements of men and women for each item as well as the impact of place of employment, age, marital status and studying railway engineering. The obtained results could help the policymakers to improve further the working situation of women in this industry which is claimed to be heavily masculine.

ABSTRACT. The focus of this study is to explore the service quality (SQ) of train mode by Structural Equation Model (SEM) in Bangladesh based on users’ perception. A face-to-face interview survey was carried out at Kamalapur Railway Station in Dhaka city to 1037 rail users. Four SEMs are developed revealing the relationships of variables with SQ. The best fit model is M4 with two latent variables ‘Trip making features (η1)’ and ‘Service features (η2)’. Finally ranking of significant attributes influencing SQ of the train is done. The result shows that ‘Seat comfort level’, ‘Female harassment condition’, ‘Safety’, ‘Train compartment condition’, ‘Entry/Exit system’, ‘Food court facility’, ‘Staff behavior’, ‘Toilet facility’, ‘Train compartment arrangement’ and ‘Cleanliness’ are the most significant attributes that influence the service features mostly. With the determination of the most and the least important attributes, this research may help to concentrate the limited resources to initiate a staged development to improve the train SQ.

ABSTRACT. High Speed Railway (HSR) significantly reduces inter-city travel times; hence, it has large-scale implications on urban growth. Many developing countries, like India, are looking forward to constructing HSR. However, the urban growth impact of HSR in these countries will differ from the developed world, requiring newer urban planning methods. Considering public opinion is pertinent for participatory planning. The study analyses factors of an HSR city’s urban growth as perceived by ordinary citizens. The rank analysis of the data collected from a questionnaire survey shows that Indians are more concerned about basic amenities than facilities for leisure purposes. Connectivity to HSR stations by metro and proximity to transit stations were the most critical factors for residential growth. Contrary to planners’ view, the multi-functional high-rise commercial development of an HSR station building was perceived as the least important factor for urban growth. Significant differences in the perception among different socio-economic groups were also observed. This study reveals the similarities between the public perception in a developing country and the empirical evidence from developed countries. Also, it highlights the importance of understanding public perception about the effects of transit on urban development.

ABSTRACT. Rail liberalisation in Europe is an on-going process, with a high degree of heterogeneity across countries. Its long-run effects on the rail market however are still debated. This paper focuses on the specific case of the Italian rail market and explores the link between presence of head-on competition, price level and service frequency in the long-distance market. It first uses a cluster analysis to identify statistically two distinct market segments, which allow to analyse routes with and without competition within the appropriate context. It then exploits this segmentation in a difference in difference estimation to explore the evolution of prices and frequency over the summer periods from 2017 to 2021. Results vary considerably deepening on the segment. Among ”core” routes, in fact, a decrease in early-booking fares is observed within one year of entry of the newcomer. On the other segment, instead, entry is linked to an increase in prices. Frequency, on the other hand, is affected positively until before the pandemic in the core segment, whereas no effect is visible on the other one. The paper is completed with a policy comment of the findings, providing an explanation for such different outcomes of head-on rail competition.

ABSTRACT. Europe is finally entering a season of liberalisation in long-distance rail passenger market. The model is on-track competition among public and private operators. The paper provides a broad-scope comparison of relevant European markets, both belonging to liberalised and non-liberalised countries, with the aim to point out the patterns in terms of supply, competition model and prices. The paper is based on a sample of heterogeneous 69 city-pairs, analysed in two fourteen days periods in 2019 (May/June and November). All modes available are observed, collecting info on companies, frequency of services, cheapest price. The analysis starts from a schematisation of supply models, based on literature. Then, using the database, we study the country’s supply structure, size, and level of intermodal and intra-modal competition through HHIs. Prices are then analysed in two steps: the average prices and the price dispersion, searching for their main determinants, including competition. Results show that a higher competition level is not always reducing prices, which are instead determined by many other factors such as size of market, demand, socio-economic characteristics, subsidies, production costs, speed advantage, strength of the incumbent, etc. The competition level, instead, directly influences the quality, the supplied capacity and the price dispersion.

ABSTRACT. Although previous studies have investigated multiple perspectives of socioeconomic effects of High-Speed Rail (HSR) on the city development individually, it is unclear how and to what extent HSR affects the overall attractiveness of cities. This study addresses this question by identifying key factors of city attractiveness and examining the effects of HSR on attractiveness using structural equation modeling. The results reveal that economic performance and urban amenities are two main factors affecting city attractiveness. Generally, urban amenities have bigger effects than economic performance, although the effects vary in social groups such as tourists, firms, and employees. Moreover, it is found that housing, education, and technology play more significant role in increasing city attractiveness than other amenities. Furthermore, the analysis shows that HSR has different influential mechanisms on city attractiveness in two stages: introduction and operation. At the introduction stage, HSR affects attractiveness indirectly by its joint effects on the economy and amenities. On average, the introduction of HSR improves city attractiveness by 47.1%. At the operation stage, HSR affects attractiveness primarily by its role in improving amenities. On average, a 1% increase in HSR operation such as frequency and number of stations will generate a 0.668% increase in city attractiveness.

ABSTRACT. High Speed Rail (HSR) represents an opportunity for serving passenger mobility at medium-long distances. Generally, the objective of the realized lines is to reduce temporal and spatial distances between to railway terminals. The purpose of this paper is to review the existing HSR lines to verify how a HSR line produces direct connections between two territories, making railway system more competitive respect to other transport alternative. To achieve the paper’s objectives, information and data about the European HSR lines are collected, focusing on the planimetric characteristics. Elaborations of the obtained data are useful in planning and designing processes of the HSR lines. The main result of the paper is connected to the review of existing planimetric characteristics of the HSR lines in Europe. The results obtained from elaborations show the tendency to improve performances of connections among territories. A correct design of a HSR line contributes to increase social, economic and environmental sustainability. The obtained results are useful as address for operators and decision makers involved in the transportation planning process. Further developments regard two research directions: more insight about other factors that influence HSR design; analyses of efficiency and effectiveness performances of existing lines.

ABSTRACT. High-speed rail(HSR) stations play a vital role in the HSR system.HSR stations in different cities can vary greatly, and an efficient HSR system requires an in-depth understanding of the interrelations between the related influential factors and spatiotemporal passenger flow patterns of different HSR stations. This study adopts a new scheme for clustering HSR stations based on passengers' arrival and departure time series in Jiangsu, China. To this end, 71 HSR stations are clustered into 3 classes and the spatiotemporal characteristics of passenger flow at different stations are compared. Finally, a geographically weighted multinomial logit model (GWMNL) is built to explore the influence of the built environment, socioeconomic indicators, and HSR station attributes on the classification results of HSR stations related to the time-varying characteristics of passenger flow. Additionally, for HSR stations under the same classification result, these variables also have different effects on them in the geographical dimension. According to these findings, quantitative analysis of the linkages between the passenger flow patterns at different HSR stations and the impacting factors would offer implications for planners and policymakers in HSR station planning and associated urban development.

ABSTRACT. The second wave of the Covid-19 pandemic has a devastating impact, and many lives have been lost. These lives were lost, primarily because there was not enough oxygen therapy support, which would give time to the infected individuals to enable their bodies o fight the infection. The same is attributed simultaneously to insufficient production capacity and poor logistics support. We reflect on this crisis, especially from an Indian perspective, as India was one of the most seriously impacted countries. We are driven in our exploration by the question – Did we do all that was there in our hands to fight the second wave? And assess how prepared we are to be for any possibility in the future.

Studying the events that unfolded during the first and the second Covid wave, we find that the logistics supply chain could have never matched the sudden spurt in demand for medical oxygen during the second wave. Further, while we have an action plan in place, the plan limits the extent to which it can match the uncertainty of oxygen demand. However, the limits are expandable and can be planned for higher levels before the demand-supply gaps become too broad.

ABSTRACT. This research helps develop effective freight demand management (FDM) programs to reduce the amounts of “panic buying” purchases to mitigate shortages. This research assesses the potential of a novel FDM initiative that relies on Trusted Change Agents (TCAs) to convince individuals to limit their purchases of critical supplies; and outlines a comprehensive FDM program with initiatives spanning the entire disaster management cycle. The research: analyzed the survey data to gain insight into the reasons to participate in “panic buying”; concluded that the term “panic buying” is a misnomer—as the instances of true “panic” are extremely rare—and suggested the term “Disaster-Related Buying Behaviors” (DRBBs)” because it better describes the phenomena; created a data-driven taxonomy of objectives and motivating reasons; estimated a Structural Equation Model (SEM) to assess the strengths of the interconnections between reasons, themes, and objectives pursued by individuals that enact DRBBs; assessed the impacts of the appeals of TCAs; identified the initiatives needed, together with the timing and sequencing, to be conducted at the various stages of the disaster management cycle; and identified the stakeholders that ought to be involved in the executions of these initiatives; and put these elements together to outline a comprehensive FDM program.

ABSTRACT. After an earthquake strikes, the survival and the suffering reduction of the victims largely depends on the aid provided within the first hours of the emergency; the local government, supported by local relief agencies are the first responders, which can represent a coordination problem at the beginning because each of them carries out their own logistics practices and the lack of information. In this paper, some highlights to design a framework to carry out an early response in real-time to an earthquake disaster in urban areas are presented. The paper focuses on the description of six elements of the management process of the delivery of relief goods in real-time from local warehouses to aid-giving facilities: damage assessment, operative coordination, information management, facilities management, vehicle paths management, and inventory management. The management of the first hours of a hypothetical earthquake emergency is exemplified by considering a short-distance distribution network and these six elements in an area of Mexico City, selecting the scenario to begin the relief efforts and evaluating the subsequent reports of damaged buildings and roads.

ABSTRACT. Through the lens of network effects, this study developed digitalization, digital transformation, digital logistics platform, and organization performance bundling model to achieve maritime shipping digital transformation and organization performance. A structural equation modeling analysis was employed to test the research hypotheses. The results show that the shipping industry should actively develop digitalization because of the positive and significant impact on digital logistics platforms, digital transformation, and organization performance. Another important source of shipping digital transformation is the digital logistics platform, which simplifies the order process, integrates intelligent technologies into shipping logistics, provides better collaborative sharing of information, and improves operational efficiency. In addition, the positive correlation between digital transformation and organization performance indicates that shipping supply chain operators can strengthen investment in digital infrastructure and facilities, adopt digital technology applications, empower digital talents, improve digital capabilities, implement digital strategies, participate in digital logistics platforms, and further deepen digital transformation for organization performance.

ABSTRACT. Freight transportation security concerns both public and private sector institutions, yet their interests are often misaligned, resulting in tensions and trade-offs between performance criteria. Previous research overlooks the connection of public and private interests and provides a fragmented view of the institutions that impact operational conditions and performance within freight transportation security. Thus, this paper proposes a Freight Transportation Security System (FTSS) model that integrates macro- and micro-economic perspectives and connects institutional pressure with performance. Based on an integrative literature review, the FTSS model comprises seven institutions that exert pressure on operational conditions and performance: regulations, law enforcement, Customs-to-Business partnerships, industry standards, Information and Communication Technologies (ICT), security solutions, and insurances. This model extends previous research by focusing on institutions as a phenomenon instead of motivational forces, and by integrating three aspects from organisational theory. By defining the FTSS model as an organisational field, the level of analysis is changed and new aspects can be explored. Further research may test this model empirically. From a managerial perspective, this model can be used as a tool in policy design and evaluation to identify tensions and trade-offs, which may reduce silo-thinking and, ultimately, improve policy effectiveness and ensure business value.

ABSTRACT. This study analyses hoarding in Sweden during the first phase of the COVID-19 pandemic in 2020. Two surveys were conducted to study what was hoarded, by whom and why. Results show that Swedes mainly hoarded canned food, pasta and toilet paper. Both surveys clarify that people with a university education hoard more than people with shorter education and there is also a correlation between higher income and hoarding in the second survey. Demographically, those who hoard are somewhat younger than those who do not, and hoarding is more common in households with partners or where children are included as well as in big cities. Self-rated health and subjective well-being were unrelated to hoarding. The most interesting finding is that only 34 per cent stated that they hoarded because of concerns that goods would run out, 55 per cent stated that the reason was fear of being infected or concern for infecting others and an additional 6 per cent stated other pandemic-related reasons. The analysis of effects for supply chains is assisted by a framework categorising product types based on how flexibly the production system can scale up production and to what extent consumption is increased or just delayed by hoarding.

ABSTRACT. The food supply is important in the event of a crisis. However, the conditions differ between urban and rural areas. The aim of this study is to investigate if hoarding behaviour and attitudes differ between various kind of residential areas and analyse how it affects grocery supply chains. The survey sample (N=4658) consists of residents in USA, UK, Germany and Sweden, representative regarding age, gender and residential areas. The analysis shows that hoarding foremost is a city-centre phenomenon and that residents in more rural and suburban areas are hoarding to a less extent. Residents in the city-centres were also more worried for that groceries and necessities should run out and perceived it more necessary to hoard. Except in Sweden, there were however no significant (p<.05) differences in experiences from groceries running out between different residential areas. Furthermore, there were no significant (p<.05) differences related to worries related to COVID-19, which is an alternative explanation to hoarding behaviour during the pandemic. In conclusion, urban consumers are more worried and concerned, even if there are no differences between experiences from that groceries are running out between different residential areas. A strength of the present study is consistency between the four countries.

ABSTRACT. The global spread and devasting impact of the COVID-19 pandemic led to governments taking stringent measures to control its rapid spread. Despite a boost in activity as COVID-19 infections drop worldwide, global growth remains subdued and is projected to slow down further. A key factor slowing down global growth is travel limitations at the center of the fight against the epidemic, especially in China, with substantial worldwide economic disruption observed. The pandemic has severely influenced transportation networks, including marine, rail, aviation, and trucking industries, causing disruptions in freight transit and logistics flow. The purpose of this research is to explore the influence of Covid-19 on worldwide freight and logistics. This research presents a systematic and bibliometric review of existing research to provide an in-depth evaluation of the impact of COVID-19 on global freight and logistics. Through a rigorous and systematic search, we identified 62 relevant articles published between 2020 and 2022 and studied the methodologies, context and theories used in each piece. The directions resulting from a critical review of these papers can guide researchers in designing and conducting impactful research. Guide policymakers to make necessary trade-offs as the world recovers from the pandemic and prepares for future pandemics.

ABSTRACT. The purpose of this paper is to provide an overview of the empirical literature on the impacts of EWE and adaptations to climate change on road and rail freight transport as well as inland navigation. The frequency and intensity of EWE are increasing, along with the number of damages to the critical infrastructure that is supposed to guarantee the mobility of society and maintain supply chains. At the same time, only a few adaptations have been undertaken and discussed so far, as this literature review makes clear. In Germany, it is mostly the increase in hot days and precipitation events that cause damage to rail and road infrastructure. IWT, which is otherwise reliable and comparatively inexpensive for bulk goods, is also affected by climate change. Depending on the event, freight transport and modes of transport are affected by varying degrees. This paper focuses on climate change impacts and adaptation measures. Further research will be needed, especially to fill the gap in the implementation of adaptation measures in the local context for Germany.

ABSTRACT. Due to the rapid growth of cities, in addition to high urban flow of goods in cities, aggravated by problems of congestion and air pollution in urban areas, there is a growing need for logistics services to be operated in a digital platform environment. This paper proposes the concept of a collaborative platform for Urban Logistics as a Service (ULaaS) and validates it through a literature review and field research based on primary databases, in-depth interviews, and surveys conducted in the Campinas city, Brazil. The analysis of collected data contributed to the validation of the proposed concept and identified modules that can generate value for the stockholders in the Campinas city: parking space reservations, shared warehousing, e-commerce deliveries and logistics services. Even though the concept is not entirely new, and some similar initiatives are found in the literature, the contribution of this work is to provide a comprehensive conceptual view of the platform. The paper also discusses a possible business model for its implementation and a preliminary canvas for a minimum viable product (MVP).

ABSTRACT. The paper aims to identify business models for sustainable last-mile delivery, which are the most preferred by e-customers, and assess the impact of those models on the environment, economics, and society. To achieve the purpose, the authors conducted a survey with conjoint analysis, the Delphi method, and the MCDM: Promethee-Gaia. Research shows that, in choosing a delivery method, price is the most significant factor for e-customers. However, the business models for last-mile delivery and return preferred by e-customers were not considered as sustainable by experts. These models create value for customers but not for the urban community at large. Research shows that there are business models for last-mile delivery that can offer a compromise between creating value for e-customers and co-creating value for the city. The results offer valuable guidelines for both courier companies and local governments.

ABSTRACT. Crowdshipping implies involving nonprofessional operators in transporting goods. While its financial benefits are easy to grasp, its environmental implications much depend on the transportation mode used and whether the trips are dedicated or non-dedicated. One way of greening crowdshipping services is to use public transportation (less polluting) as a mode of transportation and commuters as bringers (non-dedicated trips). This, in fact, allows for minimizing both pollution and congestion at the same time. While conceptually interesting and theoretically self-evident this is practically difficult to implement and much under-studied. This paper addresses these two issues at once by defining a research agenda for the future and offering a prioritization of the issues to be investigated. A literature review and in-depth interview are the methods used in sequence to provide the added value discussed above. The added value this paper produces is a confirmation of already existing research foci, an extension of the research agenda thanks to the investigation of adjacent research fields (passenger and freight urban integration), an enlargement thanks to the practical knowledge deriving from a crowdshipping operator and a prioritization of research issues.

ABSTRACT. This paper examines the role of the business model in city logistics, specifically focusing on cost structures and revenue streams. City logistics aims to manage urban goods movement while balancing environmental and societal impacts with economic development. The complexity of this field necessitates effective management, and scholars recognize the business model as a valuable tool for capturing system components and predicting changes. While the value proposition, revenue streams, and customer relationships are acknowledged as core components, there is limited understanding of cost structures and revenue streams. To address this gap, qualitative and empirical data from 14 European city logistics projects were analysed. The findings highlight the importance of integrating cost structures and revenue streams into the business model for sustainable and financially viable city logistics initiatives. This research enhances our understanding of business models in city logistics and offers insights for practitioners and policymakers involved in urban freight management.

ABSTRACT. Worldwide, e-commerce and home deliveries are rapidly growing. In the parcel delivery sector, there has been a shift from mostly business logistics requiring speedy delivery to consumers expecting the same service. Consequently, to manage the heavy workload and reduce delivery costs, delivery companies outsourced last mile deliveries to subcontractors. However, this resulted in untransparent parcel delivery chains that have been causing all kinds of malpractices. This paper starts by giving an overview of the market structure of the parcel delivery sector, where subcontracting is widespread. Secondly, the relevant legal frameworks – i.e. transport, labor, economic and competition law - are analyzed based on their effectiveness to remedy these malpractices. Often, their maladjusted scope together with other obstacles often still impede an effective remedy. Lastly, the recent legislative initiative in Belgium, which aims to improve transparency and mitigate social dumping, is presented. This proposal adopts a policy-driven approach by implementing regulations pertaining to transparency, working hours, and compensation throughout the entire delivery chain for all delivery workers regardless of their status. This distinctive aspect makes the Belgian model a possible influential precedent as it introduces social protection measures in a sector largely comprised of self-employed workers, while simultaneously respecting market preferences.

ABSTRACT. Modeling and understanding freight mode choice behavior is vital for policy makers and operators to design environment-friendly freight systems and improve service quality. This paper studies the shippers’ choice between truck and road-rail intermodal. Considering that a single shipper provides multiple groups of stated preference data under different transport contexts, a model integrating grouped and repeated observations (IGRO) is constructed based on a standard mixed logit (ML) model to capture the heterogeneity of intra-individual. A standard multinomial logit (MNL) model, an ML model without considering panel effect and a standard ML model with panel effect are also tested in this study. Statistical indicators show that the IGRO model performs the best, which indicates that the intra-individual heterogeneity across different transport contexts is stronger than the correlation. The potential factors contributing to the heterogeneity of intra-individual freight value of time (FVOT) are different origin-destinations (ODs) and cargo categories. In addition, a two-stage weighted calibration scheme is proposed. Subsequently, based on the calibrated model, some suggestions for increasing the intermodal market share are obtained through elasticity calculation and scenario analysis. Moreover, this paper measures carbon emission reduction under different modal shift scenarios and its monetary values.

ABSTRACT. This study attempts to develop a joint framework model that simultaneously estimates the mode choice and shipment size choice for inter-city freight. The disaggregated dataset of intercity freight from the Japan Commodity Flow Survey (CFS) and the Level of Service (LOS) data from NITAS were used in estimating the parameters of the model. A logit mixture model was developed using the variables of time, cost, distance, and the number of employees. The framework was then utilized in analyzing the model parameters and computed elasticities for the chemical, metal and machinery, and light industrial commodities. The models that were developed highlight the importance of considering the transport mode and shipment size simultaneously, validating the results of pasts studies. Insights from the parameter estimation show that different industries have different behaviors regarding the correlation of error components among the alternatives. The computed elasticities indicate that there will be a change in the probabilities of shipment size distribution when there is a shift in mode choice.

ABSTRACT. Rail and truck are primary modes of transportation in North America. However, their use as individual modes has also raised concerns, e.g., congestion due to extensive trucking and accessibility issue of rail due to sparse rail networks. Combining these modes has the ability to overcome challenges and limitations in individual modes. As a result, rail-truck intermodal has emerged as an alternative to individual modes. A key is to efficiently configure associated activities such as inbound/outbound drayage and long haul. To achieve this, there are a few studies that design intermodal networks as a hub-and-spoke system for regular freight. In this research, we extend the concept of intermodal hub-and-spoke networks to dangerous goods transportation. Our focus is primarily to address two concerns: make use economies of scale during long haul, and determine routings for inbound and outbound drayage activities from risk perspective. To this end, we develop a bi-level model in which the upper-level is a p-hub median single allocation problem to minimize the transportation cost and lower level is a routing problem for intermodal shipments to minimize the transportation risk in the network. We reduce the problem to a single level and illustrate the solution on a prototype intermodal network.

ABSTRACT. Modal choice models in the context of strategic freight transportation studies covering large inter-regional or international areas are generally difficult to set up because of lack of precise or even simply available relevant data. Using origin-destination (OD) matrices, it is possible to construct explanatory variables such as transportation costs or transit times. Those variables are indeed often considered as belonging to the most important drivers for freight mode choice decisions. Further, the computed trip lengths can be used, along with the transported quantities embedded in the OD matrices, to compute some spatial accessibility measures that can be used as an additional explanatory variable. This article addresses two research questions. Does it make sense to consider spatial accessibility in the mode-choice decision? Does the integration of a spatial accessibility measure in the mode-choice model improve its performance? We come to the conclusion that both questions must be answered in the affirmative.

ABSTRACT. Motorists’ Global Positioning System (GPS) data is becoming widely available. The possibility to automate transport network modelling based on extracted features from GPS data can minimize the quantity of resources usually invested in that task. Within the last decade, two literature reviews have explored the work done in road map inference from GPS data. However, they did not explore the road network inference methods from a transport modelling perspective and were not systematic nor reproducible. Thus, it was not possible to determine if the presented algorithms were able to produce road networks or network features that are directly usable in transport models. The objective of this research is to perform a systematic and reproducible literature review on the use GPS data in transport network modelling and determine future work to extract a road network representation for transport models. This was done by examining the studies’ different approaches with respect to used GPS samples, road network definition, output quality, and reproducibility. It was found that none of the studies produced a detailed enough road network for transport models. Other limitations were found such as the bias in GPS samples and the difficulty in reproducibility.

ABSTRACT. A food delivery platform dispatches crow-sourced drivers to pick up meals at merchants, e.g., restaurants, grocery supermarkets, and then deliver the meals to customers. Apart from setting the delivery price paid by customers and the wage offered to drivers, the platform can also adjust the number of customers' orders assigned to one driver in each batch (denoted as assignment factor) to affect the market equilibrium and achieve certain objectives. This paper develops a mathematical model to characterize the equilibrium state of an on-demand food delivery market, and investigate the platform's optimal operating strategies in terms of the delivery price, wage and assignment factor for maximizing the platform profit or social welfare. In particular, we consider two market scenarios depending on whether the meals are ready before the drivers arrive at the merchants' locations to pick up the meals. It is interesting to find that the platform will choose a strategy leading to the scenario where the meals are ready as the drivers arrive at the merchants. Following this observation, we further discuss the main properties of the monopoly optimum, social optimum and Pareto-efficient solutions in the on-demand food delivery market.

ABSTRACT. Emergence of road users’ global positioning system (GPS) trajectory data is increasing research interest in knowledge discovery to improve transport planning related methods and tools. In fact, the widespread of GPS enabled smartphones and mobile internet has increased the availability and size of such data. With the increase in GPS data coverage and availability, some research has expanded its use to estimate state-wide vehicle-miles travelled, to classify driving maneuvers for road safety assessment, or to estimate environmental performance indicators, such as vehicular fuel consumption and pollution emissions. In computer science, research has used GPS data to infer road network maps. Although the inferred maps had a correct topology and connectivity, they were lacking essential details to be used for transport modelling. Therefore, this work proposes a method to extract network-wide road direction and turning movement rules. In addition, it serves as a proof of concept by building a road network model under a widely used macroscopic transport modelling software, EMME. Sensitivity analysis was carried out to determine the output quality and recommend future improvements. Road segment geometry and directionality were extracted accurately, however, turning movement rules can be extracted more accurately using a larger GPS trajectory sample.

ABSTRACT. One of the core problems in the strategic planning of railway operations is the development of a line plan. The line plan optimisation problem aims to build a workable line system that achieves specific objectives. Most models published thus far in the literature seek to either maximise direct traveller numbers or minimise costs. This paper introduces a model with several objectives for solving line plan optimisation problems where lines can have different stopping patterns. Our model examines how setting different objectives can result in different line plan designs. It will be useful for railway operators to have different perspectives when deciding which design should be applied, particularly for new railway service development (e.g., high-speed train) based on their interests. A case study of future semi high-speed rail in Indonesia is presented to test the model.

ABSTRACT. This paper investigates the relationship between day-to-day travel time reliability (TTR) and vehicle density distribution on the freeway stretches from the Minneapolis-St. Paul freeway network and San Diego freeway network, and provides a corresponding theoretical model. We first established the existence of a counter-clockwise hysteresis loop between average vehicle density and experienced travel time standard deviation, and found that vehicle density heterogeneity has a more significant effect on TTR when congestion is moderate. Next, we determined the time-homogeneous Poisson process describes the vehicle arrival process on the freeway stretch during the morning peak period. Based on the M/M/1 queueing model, we derive a model for the variance of experienced travel time and average vehicle density, and density heterogeneity. Then, based on the `birth–death process ', we provide another model for the relationship between average vehicle density and density heterogeneity. Finally, we combine these two models to obtain a new model that estimates freeway stretch travel time reliability based on average vehicle density and traffic flow.

ABSTRACT. The maritime flow of West African ports, in particular those of the main ones, namely Dakar, Abidjan, Tema, Lomé, Cotonou and Lagos, have experienced an evolution characterized by the growth of containerized traffic since the 2000s. Containerization has increased with the construction of new port and land infrastructures and the acquisition of modern equipment. As a result, the LSCI average for these countries improved between 2006 and 2021, rising to 19.56. The average annual volume of containers multiplied by 1.63 in Dakar, 1.25 in Abidjan, 2.66 in Tema, 5.45 in Lomé, 3.50 in Cotonou and 2.49 in Lagos. During the decade from 2000 to 2009, an average volume of 292,252 TEUs was handled annually at the port of Dakar, 582,982 in Abidjan, 360,545 in Tema, 170,834 in Lomé, 128,288 in Cotonou and 588,782 TEU in Lagos. Between 2010 and 2021, the average annual container volume increased to 475,886 TEUs in Dakar, 734,011 in Abidjan, 960,383 in Tema, 931,531 in Lomé, 435,960 in Cotonou and 1,465,495 in Lagos. These ports play a very important economic function and contribute an average of 85% to the customs revenue of their State.

ABSTRACT. Automated People Mover systems are considered a key in improving a city’s transport system performance, as they can pool several passengers together, resulting in less cars on the roads. Such systems are expected to bloom in later stages of vehicle automation adoption as for the moment their biggest challenge is their co-existance with human driven vehicles which are essentially unpredictable. The aim of this study is to investigate the interaction of an APM system with the rest vehicular traffic of an urban road network and assess its traffic impacts in the transition era towards vehicles’ automation and connectivity. This is achieved through well-defined what-if alternative scenarios that considered different Autonomous Vehicles (AVs) stages, ie. different levels of AV penetration rates and AV technology maturity level. The results showed that AVs, and specifically the deployment of an APM system, have the potential to contribute positively. This contribution can be reflected twofold; first, as a decrease in the average number of delays associated to the performance of the APM system and second, as decrease of the average number of stops of the overall transport network performance.

ABSTRACT. The main objective of on-demand ridepooling is to merge multiple requests for a single vehicle. However, sufficient demand for the service is crucial to achieve this goal. Hence, the service’s efficiency highly depends on the number of requests. On the other hand, providers need to decide how many vehicles to use for their service in order to achieve the highest possible occupancy rate while keeping the percentage of empty, idle vehicles low. Therefore, the knowledge about how many vehicles are required to serve a given demand is of particular importance. In addition, whether a given ratio between the number of operating vehicles and the number of requests results in satisfactory service efficiency is of great interest, especially to providers. Addressing these issues, we present a simulation study, evaluating 1000 different combinations of fleet size and demand. In our evaluation, we focus on crucial efficiency criteria such as waiting time, occupancy rate, number of rejections, and share of empty vehicle kilometers. Our results show a clear relation between demand and fleet size for the efficiency of a ridepooling service. In particular, we found that a constant ratio be-tween demand and fleet size does not scale linearly with respect to efficiency.

ABSTRACT. With the rise of ridesourcing platforms such as DiDi, Uber, and Lyft, passengers can send online travel requests anytime and anywhere, and can also cancel orders at any time to take cruising taxis that they meet earlier. In this paper, we devise a simulation model of the coupled ridesourcing and taxi market to describe the complex interactions between passengers and ridesourcing drivers and taxi drivers, taking into account the different cancellation behaviors of passengers before and after order matching (i.e., cancellation of unconfirmed and confirmed orders). It is found that the waiting time of passengers served by taxis increases monotonically as the demand increases, while the waiting time of passengers served by ridesourcing vehicles shows a non-monotonic trend. At a low demand level, ridesourcing drivers have a huge advantage in competition with taxi drivers, while taxi drivers can obtain more profits at a high demand level. Overall, ridesourcing services are effective in improving vehicle utilization, and the results of this study can help the government and ridesourcing platforms better understand the coupled ridesourcing and taxi market and make more favorable decisions.

ABSTRACT. In the ride-hailing market, the platforms could recruit contractors subject to prescriptive schedules to reduce the labor supply uncertainty and balance the demand and supply, and the drivers are entitled to become a freelancer or a contractor and choose the schedule they would like to provide the service. This paper proposes an analytical framework to capture the drivers' decisions of becoming a freelancer and contractor as well as arranging work schedules in a dual sourcing market. The utility structures for freelancers and contractors are defined and a time-expanded network is adopted to portray the drivers’work schedule choices. With this setting, the drivers’ simultaneous contractual mode and work schedule selection model is formulated and the algorithm is designed. A bi-level programming is further formulated with the lower level referring to the drivers' endogenous labor supply equilibrium choice and the upper level representing the profit maximization for the platform. The numerical examples are conducted to investigate the characteristics of the equilibrium solutions. The results show that a dual sourcing market is always advantageous to contractors and conditionally beneficial to the platform, freelancers and customers. This work could provide new insights on how to manage a dual sourcing market for the platform.

ABSTRACT. Considering the rising GHG emission from the transport sector, cities around the globe are switching to sustainable modes of transport. One such mode is the battery electric bus (BEB). Cities like Shenzhen, London, and many European cities have already electrified the majority of their existing fleet of buses. Many Indian cities are opting for electric bus fleet with support from Central Government Schemes. Replacement of conventional buses with E-buses possess challenges such as reduced operational kilometers because of battery limitations, changes in the bus schedules, frequent breakdowns, and high cost of procurement. The primary criteria for the selection of electrification of the fleet is the cost of procurement and operations. Cities decide upon the type of buses based on route characteristics, battery capacity, availability of charging infrastructure and passenger demand. The high upfront cost of BEB, battery replacement and charging infrastructure are some of the issues the urban local bodies have been trying to solve over the years. Presently, cities are yet to identify the right e-bus technologies for their operating conditions. Thus, it is critical to assess the performance of already operational e--buses to improve their operational performance and assist public transport authority in making informed future procurement choices.

ABSTRACT. Conventional public transportation systems operate with fixed routes and fixed schedules, which cannot meet the time-varying travel demands, especially in low-density urban areas. We propose a flexible public transportation system that provides advanced booking service and can also respond to real-time requests. The flexible bus operates with stop-skipping and flexible schedules to reduce unnecessary bus travel distance while reducing passengers' long waiting times at stops. We develop a two-stage mixed integer programming model to maximize the operator's revenue. This model designs the initial route and schedule of buses by considering the historical and reserved passenger demand in the first stage and considering the responses to random real-time passenger demand in the second stage. The effectiveness of the method is evaluated in the No. 75 bus line in Shanghai with different demand intensities compared with the conventional transit. Sensitivity analysis is performed on parameters such as the duration of the reservation time window and the ratio of reservation requests to real-time requests. The results show that this flexible bus system outperforms the conventional bus in cases with lower passenger demand density.

ABSTRACT. Rerouting drivers from selfish route choices to system-optimal traffic patterns has the potential to improve the performance of existing infrastructure. Previous research has looked into assessing the potential of rerouting through the empirical price of anarchy, a measure of network efficiency. However, studies using real-world measurements have been limited by methodological accuracy and network size. Also, they have lacked understanding of the spatial distribution of benefits from rerouting and the relationship with marginal external cost road charges that can be used for implementation. In this article, we create an accurate data-driven traffic assignment model of England's Strategic Road Network. We use it to calculate the national price of anarchy, which is found to be almost 1 implying gains from rerouting at the national scale are minimal and smaller than in other studies. The results show the distribution of rerouting benefits varies strongly with different network zones and demand profiles. This did not match the distribution of marginal external cost charges. Some zones have noticeable benefits from rerouting although the overall network benefit is small, however, these zones do not coincide with where the largest road charges have to be applied for system-optimal rerouting. These results have implications for rerouting implementation.

ABSTRACT. Integrating advanced sensing, communication, and computing technologies into the design and operations of intelligent transportation systems has become increasingly important. Operating a large-scale carsharing system requires intelligent allocation and management of its resources and demands. An efficient and friendly operations management system is essential and critical to the success of its daily operations, dedicated to managing vehicles, infrastructure, passengers, crew members, information, and a variety of accidents and unexpected or disrupted events. The core technical part of this system is a set of data-based, algorithm-driven functions. In this paper, three challenges are identified in designing a carsharing operations management system. To design an advanced carsharing operation management system (COMS), we analyze the functional requirements and describe a five-layer system architecture in detail. In particular, we present a set of relevant technologies and open-source components used within the different subsystems of COMS. Finally, we provide a COMS prototype and show the system visualization interfaces. COMS adopts lightweight container technologies for a distributed deployment. It has good expandability and scalability and can dynamically adjust the computing and storage scale according to the system size, so as to effectively reduce the development and deployment costs, making it easier to use for commercial applications.

ABSTRACT. Many on-demand mobility simulation models focus on modelling the average weekday, even though Transport Network Company (TNC) data have shown distinct differences in trip patterns between the average weekday, Saturday and Sunday. This means that these simulation models do not necessarily capture essential weekend characteristics, especially the high tendency for group travel.

This study investigates the relationship between weekend travel and the operational efficiency of on-demand mobility service, focusing on shared autonomous vehicles (SAVs) with a dynamic ridesharing system. It also proposes a methodology for creating group travelers from travel surveys with limited information on group travels. Weekend trip patterns are compared with weekday patterns to demonstrate how this might affect SAV policies.

The findings reveal that when simulating on-demand mobility services, there are some slight differences between an average weekday and the weekend, with Saturday being more distinctive. Furthermore, we show that failing to consider group travelers in ridesharing simulations affects the results on pooling, whereby the effects can be underestimated with a difference of up to 38\% for our case study.

ABSTRACT. Connected and automated vehicle (CAV) technologies are well recognized as effective measures to improve traffic operation efficiency and safety. In this paper, we propose a cooperative eco-driving control approach for mixed traffic composed of CAVs and connected human-driven vehicles (CHVs) at urban signalized intersections. Instead of considering individual CAVs or mixed platoons, the proposed model takes into account of all vehicles in the control zone, wherein the desired arrival time to the stop line of each vehicle is estimated. A Nash-based distributed model predictive control (DMPC) approach is developed to reduce computational complexity and ensure that vehicles arrive at the stop line at the desired time with the free-flow speed, and to minimize vehicle speed fluctuations to reduce the idling time and fuel consumption. Numerical experiment results demonstrate that the proposed DMPC approach significantly reduces computation time while retain similar performance to the centralized MPC. In addition, the proposed DMPC approach significantly reduces delays, fuel consumption, and idling time in different traffic conditions compared to the classical predictive cruise control (PCC) and benchmark methods.

ABSTRACT. The vehicle fleet circulating in Brazilians’ city centers has increased significantly, but the mobility public policies have not been sufficient to follow this growth. The consequence of it is the increase of traffic congestion. Given this scenario, there are several studies about Computational Intelligence in traffic control. In this context, this paper presents a new mathematical model: OACTS - Optimization of the Active Control of Traffic Signals. This model uses Genetic Algorithm to optimize traffic signal parameters: green time, cycle time, phase sequence and offset. For this, the model proposes a new delay time function to evaluate solutions of the algorithm. A case study is developed in which real vehicles demand data are loaded in AIMSUN simulator. This simulator is calibrated previously to better represent real conditions. The model receives the demand from AIMUSUN and, based on the application of GA, defines, in real time, the traffic parameters' value that meets the demand in order to reduce the delay of vehicles. The experiments were statistically analyzed and the results show that OACTS found better solutions to the problem when compared to other models that optimize a smaller set of parameters and to the traffic plan currently used in the region.

ABSTRACT. Crashes involving pedestrians are particularly common at unsignalized mid-block crosswalks, where, at times, vehicles do not yield to pedestrians. For the safer crosswalks, not only encouraging safe yielding of drivers but also improving pedestrian cognition and reaction to conflicts with vehicles is important. A refuge island is a countermeasure at mid-block crosswalks on two-lane roads to improve the safety in pedestrian–vehicle conflicts. This study investigates the impact of refuge islands at unsignalized mid-block crosswalks on pedestrian crossing behavior and conflict severity, considering vehicle approach speed and direction of movement. A virtual reality experiment was designed to compare pedestrian crossing behaviors at mid-block crosswalks with and without refuge islands. Forty individuals were invited to participate in this study. The results revealed that at higher vehicle approaching speeds, pedestrians tended to accept shorter gaps, leading to a higher rate of unsafe crossings. Generally, in a refuge island setting, pedestrians accept significantly shorter gaps, which increases the operational efficiency of the crosswalk without significantly affecting the severity of conflicts with vehicles. Furthermore, the subjective evaluation of the pedestrians after the experiment clearly indicated their preference for the refuge island setting, as they reported a safer crossing experience.

ABSTRACT. Trajectory estimation techniques track the future locations of vehicles and pedestrians to evaluate intersection safety and warn of potential safety issues. This paper explored trajectory estimation frameworks for intersection safety evaluation of both vehicles and pedestrians using physics-based models and deep neural networks (DNNs). The physics-based model first guides the DNN to learn the trajectory estimation by itself, resulting in a physics-informed deep neural network (P-DNN). The intelligent driver model and social force model were used for the physics model of vehicles and pedestrians, respectively. To evaluate the stochastic nature of the safety evaluation, future locations were probabilistically estimated by the expected distribution in a 2-dimensional open space. Future trajectories of vehicles and pedestrians, estimated over a time range of 1 to 5 s, exhibited good accuracy. Using the proposed framework, the safety evaluation performance for detecting potentially dangerous situations was tested by the time-to-collision between vehicles and pedestrians. Because the future trajectory can be estimated probabilistically, the time-to-collision between two objects was analyzed stochastically using the Monte Carlo method and Kolmogorov-Smirnov test. For evaluating 3 s or shorter future events, the developed method exhibited over 95% accuracy; however, accuracy declined to about 70% for 5 s future events.

ABSTRACT. Safety issues for Vulnerable Road users (VRUs) such as pedestrians, motorcyclists, bicyclists, and other non-motorized transport (NMT) users is a substantial challenge all over the world. The problem is predominantly higher in urban areas of Low- and Middle-Income Countries (LMICs). Because hit-and-run crashes account for a noteworthy share of the VRUs death rate in urban India; a better understanding of these crashes will help in reducing VRU fatality risk in Indian cities. In this background, the current paper examines the impact of seasonal variations, crash timing, traffic exposures, roadway characteristics, land use, and spatial aspects of a site on the possibility of VRU hit-and-run crashes. Using 8-year (2011-2018) crash data obtained from Kolkata Police, three sets of binary logistic regression models are established to identify the key factors influencing hit-and-run crashes related to pedestrians, two-wheelers, and NMT users. Based on a systematic investigation, the present paper recognizes five topmost factors, namely, crash timing: night and early morning, speed, midblock locations, absence of pavement marking, and insufficient illumination that largely affect the possibility of VRUs hit-and-run in an urban context of LMICs. The study also identifies poor road infrastructure, slum areas, and ineffective traffic movements as important determinants of hit-and-run crashes.

ABSTRACT. Korea has the highest proportion of pedestrian fatalities among Organisation for Economic Cooperation and Development (OECD) member countries. In 2021, 1,018 pedestrian fatalities have been recorded on the roads in Korea, which constitutes 34.9% of the total road fatalities and is more than double the average number recorded by OECD member countries. In particular, the most vulnerable pedestrians are elderly people, as they constitute 59% of the total pedestrian fatalities. This study aims to identify the main exploratory variables that affect elderly pedestrian crashes by applying a classification and regression tree (CART) to road crash data in Korea. The CART is useful for identifying factors without statistical inference and is widely used for crash analysis. For the study, road crash data are obtained from a national police agency. The individual crash data include information pertaining to crash severity, crash locations, vehicle types, road types, and pedestrian activity types. The results show that speeding, the time of crash occurrence, and vehicle types are the most important factors that can lead the fatal crashes. These points need to be considered in the establishment of plans for reducing pedestrian fatalities via engineering, enforcement, and education.

ABSTRACT. Pedestrian-vehicle crashes are a leading cause of road traffic crash death all over the world. Since the factors affecting the crashes depends on many factors such as road infrastructure and environmental settings, determining area-specific characteristics which influence the crashes is important. This study focuses on pedestrian crash severity modelling in Chennai, India. We develop an ordered probit model to identify the factors affecting different levels of injury severities for the years 2017- 2019. The severity levels were divided into three categories, simple injury, grievous injury, and fatality. The primary data was taken from Road Accident Database Management System and additional data about location-specific information such as intersection presence, type of intersection and bus stop presence were extracted manually using Google Earth Pro. The results showed that environmental settings (urban or rural) significantly impact pedestrian-vehicle crashes with higher injury severities in rural areas. Time of the day, presence of bus stops within 250ft of crashes and intersection-related crashes also have significant impacts on the severity. Gender related factors were explored. Further interpretation of results was done by computing the marginal effects. Site specific treatments and need for advance pedestrian safety measures are highlighted after analysing the modelling results

ABSTRACT. Transit agencies collect onboard surveys of passengers’ socioeconomic and travel (SE&T) characteristics on a regular basis. The surveys are subject to sample and response biases, which can affect the representativeness of the results. Independently conducted passenger stop to stop origin-destination (OD) flow surveys are used to correct for some biases, but these additional surveys are costly and time-consuming. The OD flows can be estimated using data already being collected from Automatic Passenger Count (APC) and Automatic Fare Collection (AFC) systems, and these estimates can conceivably be used to correct the SE&T characteristics, thereby reducing or eliminating the need for the additional OD surveys. A large scale empirical study was conducted to investigate the sensitivity of adjusted SE&T characteristics to OD flows derived from different data sources. The results indicate that using OD flows determined from already existing APC and AFC data leads to the similar or better quality of adjusted SE&T characteristics in comparison to the quality resulting from using the additional OD surveys administered in practice.

ABSTRACT. The journeys between home and school for children represent a significant share of the total trips made on a typical day. There is, however, an alarming number of children being killed on the road due to various factors including unsafe road and traffic conditions. This paper presents the conduct of surveys to determine the commuting characteristics of school children as well as the application of the Star Rating for Schools (SR4S) methodology for road assessment. The surveys were undertaken in Valenzuela City and Zamboanga City, which were the pilot cities for a project on Child Road Traffic Injury Prevention (CRTIP). The survey collected information on the main mode of transport, travel times to and from school, usual companion to and from school, and accident and near miss involvement of school children during commute to and from school, among others. Information from these data sets can be used as the basis for the identification and implementation of interventions such as road infrastructure improvements as well as to formulate policies to make the journeys of school children safer.

ABSTRACT. There has been an ongoing debate on whether telecommuting increases or decreases traffic. These effects are usually studied based on travel diary data from household travel surveys. Previous research shows that survey period can influence measures of travel behaviour. However, it is unclear if this also holds true when measuring the influence of telecommuting on travel behaviour.

We analysed how the survey period of travel diaries affects estimates of telecommuting effects on travel behaviour measures. Our results show that an increased telecommuting frequency has a negative effect on the number of trips conducted regardless of the survey period. However, there is a significant influence of the survey period when measuring the effect of work from home on person kilometers travelled. While the baseline estimator for the telecommuting frequency is negative, this only holds true for the 1-day survey. The effect becomes positive when considering the 1-week survey influence. These findings lead us to conclude that studies based on 1-day trip diary data will likely overestimate traffic reduction potential of telecommuting measures and results from such studies should be interpreted with caution. The results are of interest to policy makers as they assess the influence of telecommuting on travel demand.

ABSTRACT. Survey design and data collection methodology has profound impact on a response-based study especially if transit commuter’s satisfaction and importance ratings are to be collected. This paper discusses survey methodology design, and the outcomes of data collection effort related to the floating of three formats of a questionnaire through two modes of survey, namely conventional and online. This standardizes Commuters’ Satisfaction and Importance Survey (CSIS) methodology. Effectiveness is examined in terms of response rate, completion rate, cost of survey, target population representatives, and influence of scale’s description and presentation. The experiences gained are shared in the form of challenges, observations, and improvement measures. The survey at the pre-test level is conducted on bus and metro routes in two different Indian cities. Eventually, the standardized survey instrument is used to conduct CSIS at varying transit systems i.e., Commuter Rail, MRT, BRT, and CBT in New Delhi, Mumbai, and Ahmedabad.

ABSTRACT. Surveys are among very important tools to gather data in the field of transportation and mobility behavior. Since the emergence and advancement of web technology, traditional survey modes such as paper-and-pencil have given way to web-based surveys. Despite web-based surveys' low cost and time requirements, higher break-off and lower response rates became a major concern. Respondent burden, the effort required to fill out a survey, is identified as one of the important drivers of survey break-off. Hence, identifying factors that contribute to respondent burden and developing measures to quantify them is imperative for understanding their impact on burden formation. This paper will provide a review of different measures of burden in various survey types and aims to find research gaps in this field. Based on the review, there is a narrow body of literature measuring perceived burden in web surveys, and such measures have been developed through other survey methods such as in-person interviews. Likewise, no studies have measured burden in transportation-related surveys, nor developed any transportation-related indicators in this regard. In light of the insights captured and the gaps identified in the course of this review, future works will be proposed to extend the knowledge of this concept.

ABSTRACT. Estimating unrealized demand for travel has vexed transportation professionals for decades. Latent demand and suppressed travel are ‘known unknowns,’ but policymakers who rely on benefit-cost analysis lack rigorous information on the social and economic returns of unlocking unrealized travel. Decision makers are thus perpetually at risk of under-estimating the benefits of infrastructure investments in communities where unrealized travel is more prevalent. To advance theory and research in this area, we critically review 17 studies on suppressed travel that we identified as part of a broader systematic review of the transportation-related social exclusion (TRSE) literature. We rank each study using Clifton and Moura’s (2017) six level framework for describing latent demand to evaluate the extent to which researchers have overcome expectations bias in estimating suppressed travel. We also evaluate the studies’ question language, recruitment methods, results, and populations studied. We conclude that estimates of unrealized travel and activity participation vary widely. Different target populations, sampling techniques, and question formats contribute to the wide range of results. We offer a series of recommendations for further research to improve estimation of travel suppression in ways that can inform more equitable transportation planning.

ABSTRACT. This research answers the following question: what are the main modal shift strategies discussed in the literature of the last 10 years? It also undertakes to analyze the impacts of each of the strategies present in the literature. It exposes a scoping review of the literature aiming to draw an up-to-date portrait of the literature on modal shift in order to synthesize it and draw conclusions for future research and policies regarding modal shift strategies. Empirical results suggest that it is possible to implement public policies to facilitate modal shift and thus help reduce car dependence. A majority of the studies reports successes: 67% for those aimed at public transport and 81% for those aimed at active transport.

ABSTRACT. COVID-19 had unprecedented consequences in our daily routines and habits. From a transportation context, there is the potential for unintended positive consequences on sustainability made possible by working from home (WFH) which reduced mobility significantly, but with significant negative effects such as the increase of car use. This paper uses data collected during the three years of the pandemic in two metropolitan areas in Australia to estimate the changes in workers’ daily decision to not work, WFH or to commute by different modes of transport. A hybrid choice model is estimated which includes three latent variables: life satisfaction, concern towards the use of public transport, and social-meeting loving attitude. Results suggest that WFH has settled as a valid and efficient alternative to a regular workplace, given the reduced stigmas employers increasingly support this flexible hybrid working model. Results show that the majority of these “saved” commuting trips were previously by car, and not by more sustainable options such as public transport and active modes. If respondents do not have the option to WFH and thus have to attend the workplace, the increase in commuting trips tends to be by car, despite evidence of some amount of return to public transport.

ABSTRACT. In a situation of increasing environmental awareness, regulatory measures, capacity shortages across different modes, and the need for a more seamless passenger journey, the optimization and alignment of multimodal transport in Europe are of the utmost importance for the overall performance of the (future) transport system. In this context, identifying the determinants of passengers’ choice of transportation is of prime importance. We assess the substitution paths between air and rail for French, German and Spanish city-pairs where both modes are supplied. On the routes studied, we estimate the market share of travel alternatives characterized by their service provider, quality and price. The model we develop involves conditional probabilities of choice coming from game theory. We particularly pay attention to the characteristics of air and rail transports, to determine how they impact the passenger’s choice for each mode. The estimated price elasticities of demand and the demand sensitivity to quality are high, showing that passengers’ propensity to modify their choice of transport is important.

ABSTRACT. Ropeways have proven to be a suitable transit extension in Latin American cities and could be a solution for moderately sized European cities with capacity problems in their public transport systems based on trams and busses. Current travel demand models indicate a modal shift of car and public transport trips towards an urban ropeway if the system offers attractive travel times. Cycling is typically not considered in studies of ropeways but may compete with this new mode, especially in European cities. In this paper, we estimate a mode choice model for persons without car availability. Among other reasons, cyclists prefer biking over public transport due to shorter travel times, independence from timetables or crowding. A ropeway may change their choice, since its cabins are continuously available and offer low crowding levels. Based on a stated choice experiment, we estimated a mode choice model considering specific properties of a ropeway, public transport and cycling. The model considers travel times, costs, weather conditions, reliability and crowding. Using a mixed logit model, the parameter estimation indicates that crowding, reliability, weather conditions and personal attitude have a statistically significant influence on the choice behavior of people in Graz, a moderately sized city in Austria.

ABSTRACT. Recent mode choice studies primarily use revealed preference (RP) data to reflect individuals’ true behaviour. However, this may not be the best practice, given the lack of information in RP data. This study uses a nonlinear utility specification for a multinomial logit choice model development using high-quality travel data collected by a GPS-based smartphone application complemented by stated preference (SP) data. The aim is to estimate Sydney residents' mode-specific value of time (VoT). The model results highlight the impact of sociodemographic variables on mode choice behaviour and individuals’ VoT when the model is jointly developed compared to stand-alone SP and RP models. The main message of this study is that in addition to collecting RP, which is a reliable and unbiased source of data, collecting complementary SP data is beneficial as it provides information that is not otherwise available in RP data. This may include a proper variation in the public transport cost variable. Using a mixed multinomial logit (MMNL) model in the willingness to pay space applied to the SP data, the unobserved heterogeneity within the estimated VoTs is captured revealing a higher variation in car users’ value of time compared to bus riders.

ABSTRACT. Late shift workers constitute 17% of the urbanized labour force in the United States (APTA, 2019) and 15% of the labour force in Canada (Wong et al., 2011). These workers are more likely to be socio-economically disadvantaged compared to other workers (Saenz, 2008), despite shift work including a range of higher income professions in technology and medicine. A significant amount of research contours the adverse health effects of working overnight (Neil-Sztramko et al., 2014), including an increased risk of causing a vehicle accident (M. L. Lee et al., 2016). Emerging research suggests that shift workers experience lower transit accessibility (Chandra et al., 2017; W. K. Lee et al., 2018), further establishing evidence of transport inequalities for this group. This study presents an exploratory analysis of night shift commuting and the impact of shift work on commuters’ time constraints in both the United States and Canada. We ask four questions: who works nights and evenings, and how does working at these times impact upon their trip-making, subjective wellbeing, and levels of time-related stress? We also explore how working nights and evenings alters the relationship between transportation resources and subjective wellbeing.

ABSTRACT. This paper studies frequent immobility (more than 3 days a week) as recorded by last French Travel Surveys. A previous analysis, based on 2007-2008 French Travel Survey, limited itself to adults on working days (Motte-Baumvol and Bonin, 2018). Here, we investigate frequent immobility (4 to 7 episodes a week, Monday to Sunday), with social equity issues in mind. After describing the variable (number of immobile days within a week), and how it evolved between last two French Travel Surveys, we identify factors that explain frequent immobility with a logit model. The last part of the paper focuses on travel behaviors on a mobile day to approach compensatory effect.

ABSTRACT. Given the profound changes expected to transform the mobility sector, a better understanding of the determinants of stability and changeability of travel behavior is needed. In this paper we use insights from a three-phase qualitative social network analysis conducted in Karlsruhe, Germany. Aim of this research is to develop a deeper understanding of why people stick to their daily life configurations. In contrast to examining rather broad categories of activities, this research takes as its starting point the social relations of people. To focus on different activity purposes, a social network was defined as a web of relations that connects individual, corporate and collective actors. Accordingly, people maintain social relationships with their friends, but also with their sports club or supermarket. As a result, deep insights into the characteristics of heterogenous social relationships are provided. Two issues have emerged to be central for the analysis of stability and variability: the spatio-temporal context in which interactions usually take place as well as the emotive-affective contexts in which relationships are embedded. In doing so, the article suggests that considering relationships instead of rather heterogenous activities provides a more holistic view into the contextual factors that accompany daily life of individual travelers.

ABSTRACT. Various interactions, time arrangements, and constraints exist for individuals scheduling their day as a member of the household, which affect their in-home as well as out-of-home activity schedule. However, the existing activity-based models are mostly based on the individual decision-making process, which are limited in their demonstration of behaviour. We propose a daily activity scheduling framework that accommodates multiple intra-household interaction dimensions and generates realistic realisations of their daily schedules. Our approach adopts the Optimisation-based Activity Scheduling Integrating Simultaneous choice dimensions (OASIS) framework, which is at the level of isolated individuals and focuses on out-of-home activity schedules. We incorporate interactions into the framework and jointly simulate in- and out-of-home activities. Our scheduling model contributes to the state-of-the-art in activity-based modelling by explicitly capturing multiple interaction dimensions within the same framework, such as allocation of the private vehicle to household members, dividing household maintenance responsibilities within the core adults, escorting, joint activity participation, and sharing rides. The approach is operationalised using time-use-survey data from the UK. The simulation results demonstrate the ability of the framework to capture complex intra-household interactions. The proposed framework is a general approach applicable to different household compositions and available resources.

ABSTRACT. Static economic models of traffic on highways, in the tradition of Walters (1961), feature singular, downward-sloping “demand curves.” This paper complicates this situation in two ways. First, we show that convex travel cost functions can cause demand curves to bend backwards when travelers choose between low- and high-occupancy modes—a phenomenon that Lehe and Pandey (2020) derived for a downtown zone and named “hyperdemand.” Second, if the high-occupancy mode exhibits economies of scale, there may be multiple demand curves which each corresponds to a different equilibrium intensity of high-occupancy usage.

ABSTRACT. Parking facilities are a critical part of a transportation system: vehicles are typically parked about 23 hours per day and require parking at each destination. These facilities impose various economic, social and environmental costs. This article estimates the number of parking spaces per vehicle, their costs and prices. This information is important for policy and planning analysis. Recent surveys indicate that North American communities typically average three to eight parking spaces per vehicle, including many seldom-used government-mandated spaces. Their annualized costs, including land, construction and operating expenses, typically range from about $600 for basic surface parking on inexpensive land to more than $5,000 for high-amenity structured parking. Overall, their costs are estimated to average about $1,000 annually per space or $5,000 per vehicle-year, totaling more than a trillion dollars per year in the U.S. For every dollar motorists spend on their vehicles somebody spends about a dollar on parking. Most parking costs are external, increasing taxes, rents and retail prices. This is economically inefficient and unfair since it increases total parking and traffic costs, and forces households that drive less than average to subsidize higher-mileage motorists. More efficient parking management could provide larger savings and benefits than previously recognized.

ABSTRACT. Agglomeration economies arising from the spatial concentration of economic activity have been known to exist and induce higher productivity for firms. The existing empirical evidence, however, has two key caveats. First, it mostly assumes a pre-specified (mostly log-log) functional form for the relationship between firm productivity and agglomeration. Second, it may lack valid instruments to adjust for potential confounding biases (for instance, from the omission of characteristics of local input and output markets) in the estimation of this relationship. This study adopts a flexible Bayesian Non-Parametric Instrumental Variables based approach to quantify non-linear effects in agglomeration economies. The approach uses innovative external instruments derived from traffic casualty data. We adopt a two-step framework: we first isolate the firm's total factor productivity from a Cobb-Douglas production function and thereafter estimate the non-linear effects of agglomeration on this productivity. Using data from a sample of firms classed into six key industry sectors in England, we present novel evidence that indicates the presence of significant non-linearities in agglomeration elasticities for most industry sectors. Our results provide critical inputs for the appraisal of transport investments.

ABSTRACT. The development of roads network does not automatically lead to the development of local economies. The value of the road will only become apparent when businesses and other users make effective use of the road. The purpose of this paper is to take the estimates from the SCGE model as the 'potential value of roads', compare them with actual economic changes, and consider the need for coordination with industrial policy (support for businesses) to realize the potential value of roads. This paper first estimates the change in production by region and industry for roads development in Japan over the past 10 years using a with-without analysis with the SCGE model and confirms the characteristics of the estimates by comparing them with the actual change in the economy as a whole. The model then confirms the effects of external factors such as the economic climate and decisions specific to particular companies, which are not represented in the model, by interviewing companies to ascertain the factors that cause the discrepancy them and clarifies the necessary conditions such as industrial policy for the effects of changes in the economic mechanism assumed by the model, if they are occurring in the real economy.

ABSTRACT. The Linear Chuo Shinkansen is expected to have economic effects on three metropolitan areas in Japan. Meanwhile, the gap between urban and rural areas will expand. The Spatial Computable General Equilibrium (SCGE) models can describe the distribution of the effect through social infrastructure developments. We propose an empirical SCGE model applying an aggregated logit model for subdivided areas where only value-added data are prepared without an input-output table. However, we developed these models only for freight transport improvements. Therefore, this study aims to develop an SCGE model considering passenger and freight transport and measure economic impacts of highways and interregional high-speed railroads. Consequently, we found that total benefit was almost identical to existing trial calculation results. Using the model in this study, calculating the effects of railroad projects even in subdivided areas where input-output tables have not been prepared is possible.

ABSTRACT. Road Traffic congestion, resulting from the inadequacy of existing transportation infrastructure to transport people from various origins to various destinations, using the same paths, at the same time (without delay) is an issue of concern to humanity. Inadequate funding for transportation limits the number of roads that can be built to increase the capacity of the transportation network. Road traffic congestion pricing has been identified as a way of reducing congestion, as it makes the cost of travel more apparent to users, but there is concern about equity issues for those who may not be able to afford the price tag. This study used the records of vehicle miles traveled in a country to illustrate the variations in revenue that could be achieved with a varied fuel efficiency of vehicles. This review noted that the VMT ‘road user fee’ pricing system is a viable way to make the cost of travel apparent to motorists and form a basis for equity between those who use fossil fuel vehicles and those who use alternative energy. The study also presented a simplified method to estimate the appropriate fuel tax, as well as VMT road user fee to achieve a self-funded transportation system.

ABSTRACT. Road pricing (RP), and congestion pricing (CP) in particular, is widely accepted among experts as an effective way to reduce greenhouse gas (GHG) emissions and mitigate traffic congestion problems. The literature on analyzing major stakeholders’ opinions about CP and ways to improve the odds of making a CP plan successful is limited to auto-centric cities in North America. Among some recent efforts in the US, LA Metro is currently conducting a Traffic Reduction Study to develop comprehensive pricing policies in the Los Angeles region. In this study, we review the relevant literature and conduct interviews with road pricing experts to assess the current and future potential for CP in the US, the challenges that lie ahead, and how likely these will be overcome. We find that public perception, political support, and revenue reinvestment are the most important concerns, though a wide array of aspects within the road pricing scheme, such as legislation, equity, design considerations, and technology, are also involved in these discussions. With conflicting stakeholder interests, the agency must develop its pricing scheme carefully such that a successful pilot program would path its way to being a permanent policy and a role model of other cities with similar characteristics.

ABSTRACT. Road or lane closures due to maintenance or construction sites are annoying to mobile people. These inconveniences are externalities and so-called ``social costs'' and they impact, e.g., traffic and economic activities. To reduce these social costs, economists suggest using instruments for internalizing these costs. First schemes emerged that aim to incentivize the closure's causer to reduce the disruption to a minimum, e.g., ``London's Lane Rental Scheme''. However, given the complex interactions in large networks with several parallel closures, the challenge becomes to identify the social costs and then attribute them to specific sites.

In this paper, we propose to use accessibility to estimate the social costs of closures. Accessibility establishes a link between traffic in networks and land use. It provides a relationship with the economic performance of regions: a closure reduces accessibility across the network, which allows estimating economic losses. We illustrate the mechanism for Munich. We find that on a daily basis, the economic losses are about a hundred euros for closing a single lane of a collector road to a couple of thousand euros for closing an arterial. Assuming cost-based pricing, these social costs can serve as a pricing estimate for the party causing the closure.

ABSTRACT. The transport market includes several players, public transport, ride-sourcing operators and travellers, interacting with each other and maximising their benefits. However, the market is characterised by a planning agency as the dominant player, making strategic decisions to regulate the market and affect the players' behaviours. This paper formulates and solves a Stackelberg game for a network-constrained transport system. The dominant player is the Stackelberg leader, and a network operator and travellers act as followers. As only one strategic player exists, the formulation is a mathematical program with equilibrium constraints (MPEC). The MPEC is reformulated as a mixed-integer linear program (MILP) by using disjunctive constraints to solve the problem. The MILP formulation allows one to add discrete constraints to the original MPEC formulation with equilibrium constraints. We illustrate numerical experiments on a toy network in Sydney to highlight the capacity and capabilities of the model for policy analysis.

ABSTRACT. Motorcycles are a common sight in all Vietnamese cities and are currently employed for more than 80% of all urban freight journeys. However, more urban freight motorbike traffic means more traffic jams, accidents, and greenhouse gas emissions. New options for zero-emission urban cargo transportation are being made possible as a result of the development of electric cargo vehicles (cargo EVs). This study examines the obstacles to the use of cargo EVs for urban freight transport. We conducted a survey of 1,335 motorcycle freight riders in Hanoi, Vietnam, to learn more about their perception of the adoption of cargo EVs. In the context of city logistics, we used latent class cluster analysis to identify two groups of cargo MC drivers, as delineated by their intention to use cargo EVs. As a result of the main obstacles related to the high cost and ambiguous battery capacity of cargo EVs, the results demonstrate that almost two-thirds of respondents would not choose to use cargo EVs. Based on the results, cargo EV producers should ensure that cargo EVs perform well, especially the battery component and financial incentives, to appeal to carriers who have recently expressed interest in cargo EVs.

ABSTRACT. Vehicle electrification has shown the potential to reduce environmental impacts and greenhouse gas emissions from the transport sector. As electric vehicles (EVs) are gaining considerable attention, locating charging infrastructure efficiently becomes a complex question that needs to be addressed. By employing empirical data from freight vehicles, this paper investigates how travel and parking patterns affect the distribution of charging infrastructure installation across the freight network. A node-based approach is presented in this paper for optimizing the allocation of charging infrastructure for freight transport. Using GPS-based data collected from a fleet of freight vehicles operating in the greater Gothenburg metropolitan area, optimal locations for operator-owned charging infrastructure are identified. This study aims to understand better the charging infrastructure requirements of the underlying freight transport system and provide decision-support to the logistic company in transitioning from conventional fossil fuel vehicles to electric freight vehicles. The proposed model could easily be adapted to other freight transport systems to assist in the transition to fossil-free freight transport promptly.

ABSTRACT. For years, numerous studies have called for a greater shift of freight transport from road to eco-friendly transport modes to avoid serious consequences of climate change. Despite these scientific calls, road transport is still the dominant mode in the sector. A key element to increase modal shift is to transform freight mode choices, as they have a decisive impact on the chosen transport mode based on identified transport performance criteria. However, there is a lack of academic research that examines the relationship between modal shift measures and mode choice criteria, as most studies focus on only one area without analysing the interactions. Using a survey-based assessment with 131 responses from shippers and logistics service providers in Austria, Germany and the Benelux countries, a user-centric framework was established to identify the most influential modal shift measures on freight mode choice criteria. The results show that infrastructure development and service and efficiency improvements are the most important measures influencing mode choice criteria and therefore have the potential to lead to a modal shift. In addition, the paper emphasises the need to adjust freight rates, as the price of transport remains the most important mode choice criteria.

ABSTRACT. This study aims to project the potential cost of the sustainability transition for the Swedish road transport system under six different scenarios. Interviews with experts are used to project the future pathway for the road transport sector in Sweden's heavy-duty fleets and design the scenarios. Through numerical modeling and based on designed scenarios, we calculate the system’s expenses. The results show that in scenarios with both dominant battery-electric vehicles (BEVs) and a mix of BEVs and fuel cell vehicles (FCVs) when the speed of transition is high and 100% market share is taken by carbon-neutral vehicles by 2050, the lower fuel and maintenance expenses can offset the higher investment expenses. Our findings also confirm a significant variance in fuel expense under different charging/refueling strategies showing the importance of charging/refueling strategic decisions on the operational expenses and therefore different vehicle technologies' competitiveness. Our result also confirms the significant role of green financing in reducing the cost of capital for the transition in scenarios with maximum electrification by penetration of BEVs and FCVs. This study provides a better understanding of the cost of the sustainability transition for Sweden’s road transport system.

ABSTRACT. Waste collection and transportation is an essential public service which is sometimes perceived very negatively by the general population in residential and urban areas. The noise and emissions released from the tailpipe of conventional refuse collection vehicles (RCVs) are major concerns for local authorities in the United Kingdom (UK). Moreover, RCVs are one of the targets under Clean Air Zones (CAZ) policies that are encouraging waste management companies to start planning and implementing trials on electric RCVs. This study assesses the impact that different charging patterns have on energy management and consequently on grid dependency, total cost, and GHG emissions. Three charging patterns are analysed, viz., charging the fleet at 16:00h; at 21:00h; and finally splitting the fleet and charging over two different time slots: 11:00h and 23:00h. The results are assessed considering the installation of localised PV solar energy and battery storage. The results conclude that the most economical configuration corresponds to the scenario where the depot has PV solar panels installed, with a Battery Energy Storage System (BESS) and an eRCV fleet which is charged in two different time slots. For this configuration, the total cost can be reduced by up to £1m over the system lifetime.

ABSTRACT. The supply of a variety of transport modes and services and the need to offer seamless solutions centred on the users needs are leading to revise design criteria and standards for the railway stations. Questioning consolidated formats and opening up to experiments to intercept the needs and opportunities of the users, some experiences in the stations are based on tactical approaches, combining physical design and supply solutions for indoor and outdoor spaces. Working in Milan Rogoredo railway station, the paper introduces the outcomes of RAISE_UB EIT_UM project (RAIlways stations multi-SErvice hUB) finalized to exploit the transformative potentiality of transition experiments, conceived as a tool for testing a range of possible solutions, to enhance quality and safety of the station. Profiling the transformative potentialities of Rogoredo station and its catchment area, focussing on its spaces and services, how they are perceived and analysing the basic needs of the station’s users, the paper introduces the implemented small and temporal solutions and assess their impacts with an online engagement platform for collecting data on users’ perceptions of space changes and community engagement in the testbed. As a final outcome, a scalable roadmap for possible combinations of physical design and supply solutions is provided.

ABSTRACT. Connected vehicles open the way for offering new strategies that can prioritize transit vehicles without having adverse impacts on the general traffic. Driver advisory system DAS is one strategy that relies on vehicle-to-infrastructure communication to advise bus drivers with specific traveling speeds and dwell times that achieve specific objectives. In this study, we conducted a comprehensive analysis of the impacts of different DAS algorithms on the performance of electric buses (e-buses) and the general traffic. Additionally, we examined two supporting space priority strategies to allow the buses to travel at the advised speeds. A simulation model for the Eglinton East corridor in Toronto, Canada was built using Aimsun Next in order to quantify the impacts of the DAS algorithms. The results show that DAS is a promising strategy that allows the buses to travel near the maximum possible speed with 25% to 55% reduction in the total number of stops, 20% to 55% higher levels of comfort, and 10% to 20% reduction in the bus energy consumption rates. Additionally, the DAS can improve the headway regularity, improving the level of service (LOS) from LOS F to LOS C when the headway regularity was added to the objectives of the DAS.

ABSTRACT. Transportation carbon dioxide (CO2) emission is an important component of carbon emissions in China, and is affected by many aspects such as energy, transportation structure, and residents' travel patterns. The excavation of those relevant factors will help us further understand the composition and main driving factors of transportation CO2 emissions. This study takes Beijing-Tianjin-Hebei region as an example, using the LMDI decomposition method to quantitatively analyze the factors of CO2 emissions from various perspectives, such as population and transportation structure, to explore the changes of passenger transportation CO2 emissions under the impact of different factors. The results show that compared with road transportation, railway transportation has an advantage in CO2 emission reduction; the same factors also show different impacts on different cities.

ABSTRACT. As an innovative, app-based, and demand-responsive mode of public transport, customized bus (CB) services have been increasingly promoted in cities around the world, but little is known about how it performs and what factors affect its performance. This study utilizes a practical subscription dataset for more than two years to assess the spatiotemporal patterns of CB and key factors driving the demand for CB over time. The results suggest: (1) CB services still exhibit regular (peak/off-peak) and recurrent travel patterns over time; (2) CB services are not only popularly used for commuting but for transport station (e.g., airport/railway station) transfer; (3) passenger loyalty, trip fare, and trip distance are the top three factors affecting the demand for CB; (4) the nonlinearities indicate that trip distance can be set at 20 km for maximizing the demand. To inform practice, long-distance commuting and airport transfer services from suburbs should be the two targeted niche markets for CB. Retaining existing customers rather than gaining new customers may be a more efficient strategy to increase the profitability of CB service. Locating stops near the neighborhoods with high-activity centres help increase service demand.

ABSTRACT. Many cities are moving towards environmentally friendly public transport such as electrification of public buses, the attractiveness of such innovative solutions among the bus users is yet to be explored. In this study, the influencing factors of e-bus users’ overall satisfaction (bus and bus-stop tangible, operating, safety and security, advanced technology application, and environmental performance) were investigated using the bus user satisfaction questionnaire. The study established the hypothetical relationships between overall satisfaction and the intention to continue using e-buses in the future and constructed an e-bus travel behaviour structural equation model (SEM). Through a direct questionnaire survey, the survey data of 394 e-bus users were obtained and verified for analysis. The results show that perceived advanced technology application and the perceived environmental performance have a positive impact on the overall satisfaction of the young e-bus user group. The study also revealed a positive association between customer satisfaction and intention to continue using e-buses in the future. From the young user's point of view, this study plays a positive role in a more comprehensive understanding of the factors enhancing the application of e-buses. Meanwhile, it provides a strong basis for government departments, industry management departments and bus companies to formulate policies.

ABSTRACT. More and better bicycle parking facilities are essential to promote cycling. Therefore, this paper analyses cyclists’ parking preferences regarding facility type and location (i.e., with respect to access and egress distances), as well as the influence of bicycle parking fees and user-specific factors. We conducted a stated-preference experiment (n = 2,960) among university students and employees of RWTH Aachen University, one of the largest universities in Germany, regarding bicycle parking choice behavior. Using a mixed logit model, we analyze the willingness to pay for parking facilities, the influence of the facility’s placement-related necessary cycling detours and walking distances. In our study, bicyclists are more than twice as sensitive to walking distances than to cycling detours. The results indicate a general preference for bicycle parking stations and covered over uncovered parking racks. While previous research has shown that groups of cyclists have different preferences and parking behaviors, it has been unclear what factors influence group assignment. Our paper shows that student status, employee group affiliation, and the resale value of the bicycle are important user-specific factors influencing the choice between parking facilities. Furthermore, there is a considerable willingness to pay for bicycle parking, especially among those with expensive bicycles.

ABSTRACT. Bike sharing is emerging globally as an active, convenient and sustainable mode of transportation. To plan successful bike sharing systems (BSSs), many cities start from a small-scale pilot and gradually expand the system to cover more areas. For station-based BSSs, this means planning new stations based on existing ones, which requires demand prediction for these new stations before they are built. Previous studies typically rely on relatively simple regression models, and latest deep learning methods are mostly developed for short-term prediction for existing stations. In this study, we propose a multi-graph attention framework to predict the potential demand for BSS expansion (BSS-MGAT) based on various urban built environment features. Specifically, it constructs localized graphs centered on each target station based on both geographical proximity and built environment similarity, and uses attention mechanisms to learn the correlation weights between stations. Experiments are conducted using real-world BSS expansion data from New York City, and the results validate the superior performance of BSS-MGAT compared to existing methods. We further demonstrate the interpretability of the model for uncovering the effects of built environment features, and the spatial interactions between BSS stations, which can provide strategic guidance for station location selection and capacity design.

ABSTRACT. Mobility system transformation is essential to realise climate justice and sustainable transport. The current study aims to measure and optimise the operational performance of shared electric mobility hubs (eHUBs). Determining the performance of eHUBs, one can get helpful insights from the results to develop appropriate future planning and management policies for improving the transport chain. Incorporating data from September 2021 to October 2022, we developed a novel dynamic two-stage data envelopment analysis (DEA) framework to assess the performance of the eHUB network in Inverness. In the first stage, the model computed relative efficiency scores related to the operational performance of the stations. In the second stage, we focus on examining the factors that may influence the high or low obtained performance scores. Scrupulous analysis shows that the population in the catchment area of the eHUBs and weather conditions, specifically temperature, are among the most important influencing factors on riding demand. The findings can be used to improve the development of sustainable mobility strategies, particularly related to electric-assist bikes (e-bikes, aka pedelecs) in cities.

ABSTRACT. In a measure to recognize and act upon civic mobility outgrowths, benchmarking is an effective means of encouraging performance-oriented behaviour through peer pressure. This study is an attempt to identify the performance indicators that majorly affect the walkability and cyclability of people and their mode preference in small and medium sized Indian cities capable of promoting active mobility. This is achieved through literature review and analysis of various policies, programs, and practices adopted nationally & internationally. The indicators that were both unique and common to cyclists and pedestrians were listed. A Delphi survey was conducted based on Analytic Hierarchy Process to identify the performance indicators that can be benchmarked for promoting active mobility in a beginner city. The indicators selected have been segregated into five dimensions to categorize the performance indicators: socio-demographic, socio-economic, physical environment, built environment, and safety. Results obtained from the study showed that land use and network continuity, built environment, and safety are the most important drivers of active mobility uptake and could influence the active modal share. The analysis will provide a useful perspective on active transportation benchmarking and help advance the logical understanding of key performance indicators in the case of cycling and pedestrianization.

ABSTRACT. Limited data hinder the promotion of active transportation (walking and bicycling) in developing countries. It is important to utilize the available information on the road environment to assess walkability and bikeability. The study aims to correlate the objective factors (sidewalk and bicycle lane inventory data) to the subjective factors that could assess a road network’s walkability and bikeability. Both factors were subdivided into three main components: convenience, safety, and comfortability, for walkability and bikeability indices. The internal consistency was determined in the questionnaire scores’ evaluation. Then, principal component analysis (PCA) was proposed to group indices into summarized factors. A case study of a city in Metro Manila showed a strong positive correlation between the scores in all components of the objective and subjective factors, in which a correlation coefficient is greater than 0.83 in all the components. This meant that the user-perception were reflective and indicative of the state of the objective characteristics of the sidewalks and bicycle lanes, which meant that the questionnaire could be used for urban roads. The results suggest that the perception scores of urban roads are a determining factor in diagnosing and evaluating countermeasures to improve the objective features of sidewalks and bicycle paths.

ABSTRACT. Green stormwater infrastructure (GSI) is increasingly used in urban planning to replace grey infrastructure and achieve environmental, social and economic benefits. The design of this infrastructure can result in a substantial reallocation of the space and contribute to active mobility, especially when implemented in the right-of-way. Yet, few studies have investigated the relationship between GSI and active mobility. In this paper, we systematically review the scientific literature (65 studies) to assess this synergy. While the review reveals a lack of empirical studies on GSI and active mobility, the potential effects that GSI can provide through their common characteristics with other green features are highlighted. The main potential benefits identified are increasing active travel, increasing physical and outdoor activities, improving road safety, and improving street aesthetics. The studies also raised concerns about car mobility, safety and aesthetic. Findings demonstrate that the relationship between green features, GSI, and active mobility is complex and needs further empirical studies to understand the nuanced effects of different types of infrastructure on active travel. This study is of relevance to researchers and planners aiming to delve deeper to understand how GSI can be designed and implemented to support both urban water management and active mobility.

ABSTRACT. The 2015 Metro Vancouver Transportation and Transit Plebiscite was the first direct democratic vote on public transit funding held in a Canadian city-region. Using qualitative methods and a conceptual framework based on orders of policy learning, this research investigates the learning of TransLink's Mayors' Council on Regional Transportation in the five years following the 2015 Plebiscite. The findings are that the Mayors' Council engaged in second and third-order policy learning, enabling them to creatively utilize their limited political, organizational, and relational resources to achieve multi-level funding agreements with senior government partners on significant parts of the plan left unfunded in 2015. Their learning led them from a stance of puzzling out policy options to a phase of powering, building leverage which they had lacked during the 2015 Plebiscite through a campaign communicating the political possibility of higher senior government contributions to regional transportation investments.

ABSTRACT. This paper analyses the determinants of participation of stakeholders in Marine Environmental Protection Committee of the International Maritime Organization using information on 2,669 proposals to 28 MEPC meetings (2002-2019). Proposals were submitted by 117 different Members States and by 75 by Intergovernmental or Non-Governmental Organizations. Proposals from Member States are by rich countries, with a vested interest in international trade and with a high political accountability. Countries that are both vulnerable to climate change and have less adaptive capacity to cope with climate change impacts are less active, unless they are large ownership countries. Out of the 15 IGOs and 60 NGOs submitting proposals, shipowners’ interests and shipping-related associations represent the majority of all IGO and NGO submissions. Finally, when Member States cooperate with NGO, they tend to collaborate with shipowners’ interest associations. Our findings confirm the large participation of a handful of countries in the first stage of the decision-making process at IMO, while highlighting the lack of diversity in the profile of participants. IMO should encourage a wider participation of vulnerable countries with less adaptive capacity to cope with climate change impacts and NGO to counterbalance the strong participation of large shipping nations and industry representatives.

ABSTRACT. Autonomous Vehicles (AVs) are commonly presented with potential to transform urban transportation systems. However, political-institutional factors are vital to enable AVs large-scale and safe deployment. The current literature lacks important questions of AVs governance such as the influence of power and politics, and how policy gets made. Using the mobilities paradigm, this paper explored the role of political-institutional power in influencing the future deployment of AVs in New Zealand (NZ). This paper analysed policy documents and interview data with government officials and transport professionals. Discourse analysis shows how AVs policy was advanced by ‘paradigm shift’ storylines (2012-16) but was then thwarted by ‘technology risk and uncertainty’ storylines (2017-22). The shift in policy direction was a result of complex institutional structures, different hierarchical levels, and contested priorities of political governments. Findings also show how funding sources influence decision-making dynamics for investment in AVs infrastructure between central and local government. The paper shows how the formal and informal networks of actors influence government decisions and priority for AVs policy. The paper concludes that the complex governance environment and the central government politics dominate the priority settings of the AVs agenda in NZ which hinder a smooth transition towards AVs in the future.

ABSTRACT. As the volume of goods transported globally continues to rise, public infrastructure owners and operators must find ways to expand capacity and at the same time cope with limited financial resources. Is it possible to have a sustainable transport infrastructure network that is efficient in both economic and societal terms? We contend that current ways of evaluating public project investments, most notably Cost-Benefit Analysis (CBA), are not able to meet the needs of decision-makers for the capital investments required. We propose a new tool that can handle the dynamic nature, international dimension, and interdependence of infrastructure projects. We refer to this tool as ‘Socio Economic Monitoring Instrument or SEMI’. SEMI is based on CBA and on the Real Options philosophy. It can be used by decision-makers to identify the investments with the highest economic and societal benefits, and to help them in making the right decisions at the right time, in framing future options, and in presenting decisions made to stakeholders. We show how SEMI can be applied through a case study of the hinterland connections of the Port of Zeebrugge.

ABSTRACT. There is a growing literature on public participation in transport governance. However, most studies focus on organized, deliberative planning processes managed by government actors. This paper addresses another type of participation, namely various aspects of political participation and channels used to influence politics. It is a perspective well established in the political science literature, but minor studied in the field of transport. The paper is based on a literature review, which identified 68 articles that contained examples of political participation used to engage in transport issues. Three channels are recurring a) voting b) expressing views on-line and 3) social movement activities including protests and community opposition. The paper presents a framework discussing how the findings can be linked to governance. This is a first attempt to conceptualized political participation within the transport governance literature. It is concluded that the literature within this field is scattered, and more studies are need.

ABSTRACT. Risk explains public-private partnership (PPP). And PPP anchors on trust. No contract is complete. Contracts include the unknown. Moreover, even the known strands of risk interact in ways that prevent delineation. Therefore, PPP must rely on trust. How? This paper uses the physics of dynamical systems to answer that question. More specifically, the paper uses Lyapunov stability. And the paper draws in the M40 motorway in the UK as case phenomenon. Consequently, the paper provides a frame for both explicating past projects (evaluation) and illuminating ongoing and future ones (appraisal). And that explication and illumination is the essence of case study. Extending that abstraction: There are two options of PPP – concession or management contract. Either option leads to a fuzzy path. The dominant concessions rely on the market to drive policy. That is not sustainable. On the other hand, management contracts require a holonomic state. The younger states have moulding structures, which do not provide holonomic effect. Therefore, management contracts will be unstable. Whichever path, policy designers must install incremental and reflexive functions to navigate their complex spaces.

ABSTRACT. This article researches the impact that new regional rail transport infrastructure has on travel choices. The research is based on the observations from a newly created regional rail that connects the urbanized area of Tricity (Gdansk, Gdynia, Sopot) in Poland to its surrounding counties. We posit that regional rail infrastructure is efficient in reducing car-related travel choices even for users who have good access to a private car. Moreover, we check the impact of intermodality – i.e. the good connectedness of rail to other public transport as an important factor influencing traveler’s choices. We propose a SEM model modified from the original Aizen’s idea by the introduction of intermodality as a mediator. Our results and observed moderation effects show that rail ridership is statistically significantly influenced by intermodality. Interestingly we also find that car-ownership is not so much limiting a factor in decisions towards the use of rail options as other studies suggest and environmental awareness is a considerable variable behind rail transport user attitudes.

ABSTRACT. In this paper, we develop the concept of a “Sustainable Mobility Guarantee”. We first review existing “Mobility Guarantees”, which are motivated by socioeconomic interests and thus oriented from a civil minimum, and classify them. Based on this assessment, we define a Sustainable Mobility Guarantee, which extends existing approaches with environmental interests. It is an emerging concept in policymaking to ensure a certain level of mobility without private cars, particularly in rural areas, but it is still in its infancy and lacks clear definitions. The concept embraces the idea of classical Mobility Guarantees while seeking to enable and promote the use of non-automobile modes for everyday travels for everyone, not only for specific trip purposes like commuting, nor for specific target groups like the elderly. We then discuss practical implementation and financial feasibility. Implementation is possible through programmatic or regulatory approaches, which may serve as a potential transitional basis for legal regulation. At least in developed countries, implementing mobility services realizing a Sustainable Mobility Guarantee is deemed financeable, given that financial instruments now subsidizing automobile use are shifted towards implementation of the guarantee, without being detrimental to the economy.

ABSTRACT. There is an ongoing discussion that greenhouse gas emissions of transport will be incorporated in the existing European Emissions Trading System. The cap and trade approach will lead to substantial price increases of fossil fuel. Empirical evidence shows that carbon pricing seems to have a regressive effect. Redistribution by means of equal-per-capita-payments can reverse this regressive effect into a progressive effect. Nevertheless, there is significant variation within the different levels of economic status leaving considerable shares of households with a low economic status without a positive net transfer. This paper aims to show that in the transport sector impacts of carbon pricing on households vary substantially with the economic status and the regions. To this end car ownership, horsepower of cars, annual mileage, and mode choice of households are analysed differentiated by different levels of equivalised disposable income and by different area categories of the urban and the rural regions. Since mobility is generally seen as a precondition for social activity there may be a need for transport allowances even if equal-per-capita-payments were introduced.

ABSTRACT. Federal governments across North America are increasingly working to scale up active-transportation investments and to harmonize policy efforts aimed at decarbonizing of the transport sector. While such policies promise to provide increased support for active transport, the extent to which central-government interventions can foster wide-reaching and equitable infrastructure transitions remains an open question. This paper offers a comparison of recent federal policy initiatives aimed at supporting the development of facilities for cycling, walking and other active mobilities across Canada, the United States, and Mexico. Using a comparative content-analysis approach, we analyse national strategies in terms of policy development, goals, instruments, and social-equity considerations. Findings indicate that policy instruments, development resources, and social-equity mechanisms vary considerably. While Canada’s policies offer targeted project funding for active transport, its national road-safety vision lacks attention to social equity concerns. The United States’ policies emphasize large-scale infrastructure transitions, but risk deprioritizing active-transport projects within wider investments. Mexico’s new mobility and road safety law lacks infrastructure funding but leads in its human-rights approach. While these differences can be attributed to differences between national contexts, we posit that they provide insights into shared challenges and opportunities in national efforts aimed at providing comprehensive support for active-transport systems.

ABSTRACT. The purpose of public transport is to expand activity opportunities of residents. Many public transport planning methods focus on the needs of residents. However, residents can adapt to the environment and form limited needs in areas with low public-transport service levels, such as rural areas. Therefore, it is important to focus on activity opportunities (various states of people (being) and actions (being able)) rather than needs. The authors constructed a method for local public transport planning that focuses on activity opportunities; however, the variables and solutions of the model were abstract and thus did not reach the stage of practical application. Therefore, this study aimed to put into practical use a support method for local public transport planning. This method consists of a “measurement model for activity opportunity,” in which a given bus service and the ability to use it are variables, and an “evaluation model for planning alternatives” that incorporates a social relationship function and disparity principle. Through a case analysis in a rural area to which this method was applied, its usefulness was verified, and it was confirmed that it can contribute to public transport planning to increase activity opportunities.

ABSTRACT. By providing territorial accessibility, municipalities play a vital role in securing social interactions, daily commuting and other leisure and commercial activities. At the same time, its transport systems enhance environmental pressures such as air pollution or change of land use. Efficiency is therefore an important goal of municipalities’ transport policy. Studies discussing transport efficiency often focus on the performance of public transport systems or operators. Given, however, the multi-modal character of urban mobility, this study seeks to analyze urban transport systems in a broader context, accounting for both public and private transport. Therefore, a two-stage non-parametric technique is adopted to measure the efficiency of transport systems of 49 German municipalities and to identify potential drivers of inefficiencies by employing a truncated regression analysis. In line with many other empirical results, we find highly populated municipalities to operate more efficient than smaller ones. Second, efficiency is driven by modal split and individual mobility patterns, with positive correlation between territorial accessibility and trips made by bike or public transport. Interestingly, we find negative significant impacts of territorial extension and the degree of urbanization. Finally, findings confirm the positive and significant impact of municipalities’ financial capabilities.

ABSTRACT. In this study, we examined the factors that caused a decrease in the number of bus users owing to COVID-19 using data from transportation smart cards. The analysis indicated that bus usage decreased even in February and March 2021 at bus stops inhabited with many elderly population. The decrease in bus ridership was greater for ODs with longer travel distances. Propensity score matching method analysis revealed that even in February and March 2021, bus ridership declined at bus stops with restaurants. Probably, the use of restaurants by buses did not recover even in February and March, 2021.

ABSTRACT. Studies investigating the effects of COVID-19 pandemic on ridership of low-demand transit systems are scarce. Hence the three unclear research aspects are: (i) transit patronage losses attributed to pandemic restrictions, (ii) vulnerability of zones to demand declines, and (iii) factors contributing to vulnerability. This study analyses these aspects by investigating zonal-level boardings of bus transit system in Winnipeg, Canada, from 2017-2020. Two multivariate adaptive regression splines (MARS) models were developed. First, a time-series MARS model was used to forecast transit demand for 2020 based on historical demand patterns. Second, difference between predicted and observed transit demand for 2020 is modeled as a function of land use, socio-demographic, and zonal-level variables. The study showed that the magnitude of demand decline was highest in April 2020, with a total loss of 1.74 million boardings attributable to pandemic. Transit usage in commercial (50%-60% reduction), education (80% reduction), and recreational (60%-80% reduction) zones were most affected by pandemic restrictions. Besides, transit coverage to essential services, the proportion of education uses, and the median age of youth are the most important determinants of zonal vulnerability. The findings are valuable for transit officials of low-demand transit cities to plan response strategies for long-term operational disruptions effectively.

ABSTRACT. The public passenger transport sector in Brazil is experiencing a strong economic crisis. Outdated remuneration models, combined with planning and management difficulties, are causing a permanent drop in passenger numbers, a decline in productivity and user dissatisfaction. The different interests of management, users and operators create situations where the success of one is to the detriment of the other, making it necessary to review the regulatory model. This study foresees adjustment of the remuneration criteria for transport services, including productivity and quality factors in the fare calculation. These factors will foster a cycle of efficiency and effectiveness in the provision of services, with the anticipated sharing of results and the possibility of bonuses for users, operators and workers. The study also presents a real test, using data from the city of Belo Horizonte/Brazil.

ABSTRACT. Countries worldwide have been experiencing a dramatic decrease in mobility levels due to COVID, followed by a slow recovery, particularly for public transport ridership. We asked ourselves two main questions: (i) after COVID ends, will people continue riding transit? and (ii) what are riders’ reasons behind increasing, maintaining, or decreasing public transport use? Using a two-wave survey conducted in 2020 and 2021, we assess the motives behind future public transport use in two Canadian cities (Toronto and Vancouver). To do this, we use quantitative and qualitative methods, particularly clustering techniques, text mining, and content analysis. Our research allowed us to understand the heterogeneity of users based on their behavior before, during, and coming out of the pandemic. We identified six clusters, ranging from those experiencing transport poverty who rely on public transport to those more resourced users who will ride less transit since they can choose alternatives such as remote work, private modes, or active travel. We discuss the policy and practice implications of these results, focusing on what public transport decision makers should prioritise to benefit disadvantaged groups and recover ridership in order to improve the economic sustainability of transit systems.

ABSTRACT. The transport sector is undergoing electrification, but the transport system still contributes greatly to global emissions of greenhouse gases. An important part of reducing the negative impacts of mobility would be to move some of the trips currently made by private car to public transport. Research has shown that the propensity to shift from car to public transport is low and that few people who own a car are willing to switch to public transport. Therefore, it might be argued that to achieve significant changes the transport system must be designed so that fewer people experience a need to own a car. This study investigates whether the design of the public transport system has an impact on car ownership. A Poisson model of car ownership is estimated using survey data on travel behaviour from Sweden. It is found that car ownership is affected not only by socioeconomic factors such as income, education and age, but also by the time required to take the bus to work, the price of the taking the bus to work, and the time required to get to work by bicycle.

ABSTRACT. Addressing unemployment and income inequalities within transport and land use policies are important, especially after the impact of Covid-19 on global economies. Previous research proves the impact of a spatial mismatch on the probability of an individual to become employed but ignores the impact on an employee’s decision to remain in employment, ultimately impacting on their employment duration. This research provides evidence that longer commute distances between an employee’s residence and work location reduces their employment duration for lower income employees. The converse it true for higher income individuals which shows a positive relationship between commute distance and employment duration. The differentiated impact that transport distance has on the employment duration for different income groups can be incorporated in transport and land use policy that considers the improvement of employment and equity outcomes.

ABSTRACT. This article presents an overview of the methodology developed for the conception of the National Logistics Plan 2035 - NLP 2035, the most recent reference in terms of strategic transportation planning at a national level in Brazil. NLP 2035 is the first instrument of the Brazilian National Transport Policy - NTP - prepared under the guidelines of the Department of Infrastructure’s Ordinance No. 123 of 2020, which established the Integrate Transport Planning – ITP. The National Logistics Plan – NLP 2035, developed according to the methodology presented, identified needs and opportunities that guide the planning process at the tactical level, such as regions which need improvements in transport costs, accessibility and safety. In addition, it identifies the projects with most positive impact on the objectives of the NTP. It’s worth to highlight the elements already addressed that were part of the initial framework of the NLP 2035 and that were fundamental to the greater ability to perceive future scenarios: the ODM of people and cargoes obtained with innovative methodologies and technologies; modeling considering a network that covers all modes; and the use of scenarios and a system of indicators that aims to signal impacts.

ABSTRACT. Developing countries have implemented diverse policies to mitigate the externalities generated by car use; some of them more successful than others. However, there is little evidence about what drives the acceptance of these policies among vehicle owners, especially in Latin American countries. This research aims to contribute to his literature by evaluating the factors that influence the preferences of vehicle owners from Colombia towards some transport policies typically implemented in the Global South. To do so, we estimate hybrid choice models from stated preferences inquiring preferences towards a set of transport policies, collected in the five main cities of the country. The framework allows to identify heterogeneity in the preferences and biases toward acceptance. Results suggest that policies oriented towards active travel alternatives and congestion charging generate resistance among vehicle owners. In contrast, implementing public transport subsidies and reducing fuel subsidies are more accepted. Individuals with pro-car attitudes are more likely to accept policies that increase road supply, while pro-environmental prefer more sustainable alternatives, as expected. Finally, we discuss implications considering that findings are in the interest of policy making and decision makers to formulate strategies that facilitate the acceptance and implementation of transport policies.

ABSTRACT. Transport-related social exclusion is a well-researched area in many parts of the world, however, in Africa, where transport services and infrastructure are poor and inhibit the well-being of a majority of citizens, the area is significantly under-researched. This paper uses a bibliometric analysis to determine the current state of TRSE research in Africa. The results reflect that there is little research that addresses the issue directly. Much of the research is found to be related to other issues, such as health services, which access is affected by transport inaccessibility. There are however several studies that do specifically aim at researching TRSE, although these tend to consider specific geographical areas or issues, such as the impact on people with disability or the elderly. There is little that considers TRSE from a broader perspective. The findings reflect a need for extensive data, to ensure that proposed projects and policies are based on meaningful information. Future research directions should also consider the role of technology, as a tool in alleviating TRSE. The role of infrastructure requires investigation, particularly in urban environments. Finally, there is a specific need for local knowledge advancement, to enable the development of locally applicable solutions and policies.

ABSTRACT. The impact of the pandemic on travel behavior has evolved as COVID-19 progressed worldwide. The mobility patterns and the frequency of travel have significantly changed over time. This study focuses on the changes in travel behavior among residents in the Western Province of Sri Lanka, regarding their mode of transport for different trip purposes during and after the COVID-19 pandemic. To gather data, online questionnaire surveys were conducted in two phases, collecting information on trip frequencies and transport mode choices for various trip purposes. The results indicate a decrease in the utilization of public and shared transportation modes for work, school, and other trips, followed by an increase in private modes during and after the first wave. Although the shift in mobility patterns gradually decreased during the second wave, it did not return to pre-pandemic levels. Moreover, the findings reveal a transition from public transportation to alternative modes for all trip types, accompanied by a decrease in out-of-home activities during the pandemic. The most common reasons for the change in transport modes were health concerns, government regulations, and capacity constraints. These results provide insights for relevant authorities in planning for mobility needs during a pandemic like COVID-19 in the future.

ABSTRACT. Metro Manila’s problem with traffic congestion has been an ongoing problem in the transportation sector in the country. The consequences of traffic congestion and heavy volumes of vehicles contribute to both pollution and economic loss. The COVID-19 pandemic has brought changes in terms of transportation restrictions that were caused by the different lockdown periods in the country, namely the General Community Quarantine (GCQ) and the Enhanced Community Quarantine (ECQ). Due to these changes in restrictions and regulations in the transportation sector, the current situation of the transportation sector was unclear as there were conflicting reports regarding travel behavior and modal shifts for both public and private transportation. With this, the researchers conducted a survey which aimed to capture the state of the transportation sector before and during the COVID-19 pandemic. From the gathered data, the researchers were able to quantify the time costs, vehicle operating costs, and emissions costs for the pre-pandemic state, GCQ, and ECQ through the Co-Benefits approach.

ABSTRACT. An emerging body of evidence suggest there is a social equity dimension in the distribution of benefits from new urban transit systems. This can be interpreted in terms of the influence of new infrastructure on different population groups and across space. People’s use of the rail transit system varies over space, but whether social inequity arises is poorly evidenced. This study demonstrates the effect of rail transit in facilitating people’s travel and mitigating transport-related social inequity, including for those with mobility disadvantages and living in areas with poor access to public transport. The results also emphasise the necessity of associated development strategies and transport policies in favour of socially disadvantaged groups, such as low fare levels. A geographically weighted regression (GWR) model is used to reveal the spatial variation in parameter estimates, complementing the traditional multivariate global model. Reflections for planning interventions are proposed based on the model results.

ABSTRACT. Understanding how the passenger satisfaction varies across multiple Public Transit (PT) modes is helpful to identify different needs of service users and make improvements accordingly. This study investigates customer satisfaction in three PT modes (bus rapid transit, metro, and jitney) using a set of consistent customer satisfaction surveys; providing a comparable approach in the surveying tool, defined variables, and model structure across different modes. Additionally, the effects of a wide set of variables influencing satisfaction such as personal and trip characteristics, and perceptions towards service quality attributes have been incorporated in the modeling process. A total of 1,808 valid responses from PT passengers in Tehran have been used to develop ordered logit models. The findings indicate that bus rapid transit and metro users are respectively more satisfied with their trips compared to jitney users, and the reasons have been explored. Also, an importance-performance analysis has been applied on the modeling results as an application of the study to prioritize improvements in the service quality attributes of all three PT modes aiming towards allocating limited resources more efficiently. The transit agencies can benefit from this study to find specific strategies for each PT mode and increase competitiveness within the transit system.

ABSTRACT. Enhancing the walking environment around metro stations is essential for the success of the metro service. The objective of the study is to develop an easy and comfortable method to measure the walkability around metro stations using an audit tool developed and provide recommendations for its improvement with prioritizing the needs of pedestrians. The study explores the microscale built environment factors affecting walkability around metro stations. Twenty factors were selected and clustered in four groups: mobility, comfort, safety, and security. Fifteen catchment areas of Delhi metro stations, India were inspected by walkability audit, and objective scores were computed for each selected attribute. Further, importance score of each attribute was derived from questionnaire survey. Importance performance analysis was performed to identify the areas which require improvement. At the end, by estimating and comparing the walkability scores for different metro stations, conclusions and recommendations were made to enhance the walkability and walk-accessibility to metro stations. The proposed approach is simple and it accounts the metro users’ perception which is missing in previous approaches. This approach would be helpful for planners and policymakers to improve walkability around stations, thereby creating a transportation network more sustainable.

ABSTRACT. Addressing the need for curbing private motorization and car dependency while reducing inequalities associated with transport requires in-depth understanding of the individual and collective practices, attitudes and experiences of urban accessibility and mobility. This paper builds on qualitative research methods and a framework of urban transitions to sustainable accessibility to examine the links between travel needs, preferences and attitudes and structural factors such as urban form, poverty, and informality at different scales. It proposes methods and evidence for accessibility-centered analysis that can enrich policy and practice in Sub-Saharan African (SSA) cities, using Sierra Leone’s capital Freetown as case study. While literature on urban mobility, accessibility and land-use in SSA cities is increasing, research on this topic largely consists of quantitative and spatial metrics at the macro scale. The focus of international scholarship on the city-scale offers limited information about the diversity of transport needs, preferences and behaviours and their intersections with the multitude of social identities of urban citizens. The study examines four neighbourhoods with different levels of access and motorization. It interrogates components of accessibility and how they lead to individual and collective everyday experiences of transport and its implications for access and sustainable urban mobility in the future.

ABSTRACT. Driver behaviour plays a significant role in the assessment of safety performance of road infrastructure systems. The present study introduces the methodological concept of a threshold tangent and recommends a threshold tangent length of 130 m to demarcate dependent and independent driver behaviour. A novel parameter called Geometry Representative Factor (GRF) is also developed in the present study, which can represent the effect of curve geometry, i.e. radius and length of curve, simultaneously. Assessment of driver behavior on hilly roads by studying the variability of maximum and minimum speed and speed positions on different curves and tangent respectively constitutes another important focus of the study. Significant variability is reported to be associated with the distribution of maximum and minimum speed and speed positions on different curves and tangent respectively. The findings of the present study signify the fact that higher level of variability and different trend of variability is associated with the minimum and maximum speed position on curves and tangents respectively in case of hilly roads compared to plain roads. Increased variability of critical speed positions substantiates the importance of considering the entire length of curves and tangents in the development of operating speed model.

ABSTRACT. Physical risk control techniques are essential elements in the development of any country’s transportation. Therefore, making sure that the road environment is safe, is a positive step to changing rightly motorists’ behaviour for compliance’s sake. This study evaluated physical risk control techniques for road safety compliance, with specific reference to the perceptions of motorists in Lagos, Nigeria. This study employed a survey research design anchored on a quantitative method. The study adopted a cross-sectional survey research design. A survey-based questionnaire was applied to 287 registered motorists. Thus, the data procedural technique employed were simple frequency percentages and Friedman’s rank test statistical method. The findings show that physical risk control techniques are significant in attracting reasonable risk attitudes from motorists. The study recommended that efforts be made to ensure that collaborations are encouraged among stakeholders (such as Federal Road Safety Corps, Nigeria Police Force, and other State Transport Authorities) in a bid to see that adequate road safety compliance is sustained.

ABSTRACT. Road traffic crashes are the result of a complex interaction between the way people behave on the roads, the vehicles they use, speed, and the design of the roads. An efficient crash recording and analysis system is one of the basic requirements for any country attempting to tackle road safety on a rational basis. This research demonstrates the use of an efficient crash data recording system to adopt a safe system approach on case study state of Himachal Pradesh in India. A Mass action plan is a network level program and a set of engineering countermeasures that targets a specific collision type. Crash data analysis using tools in crash database management system indicates that 5 collision types (run-off road, head-on, hit pedestrian, hit in-side and hit in rear) account for 95% of the fatalities and serious injuries in the state. This paper discusses a methodology of spatial analysis to identify the clusters of the predominant crash types on different types of roads. The paper also suggests corresponding mass action plans to rectify the top collision types in the state which may in turn lead to a substantial reduction in the likelihood of crash occurrence and it's severity.

ABSTRACT. In road safety, authorities need to prioritize projects while working within a limited budget. To do this effectively, the benefits of the projects need to be estimated as well as the various costs associated with them. Although there are various methods for prioritizing projects such as incremental benefit-cost analysis, such methods have been criticized for failing to capture the multi criteria nature of the project prioritization problem. Data envelopment analysis has been suggested as an appropriate tool for prioritizing road safety projects while considering the multi criteria nature of this task. The approach can also potentially account for the uncertainty in estimating both the benefits and the costs of road safety improvement projects; this is a critical issue, since failure to adequately account for this uncertainty can lead to incorrect project prioritization and poor decision making. Two methods for incorporating uncertainty into the prioritization process were reviewed, and it is concluded that the Monte-Carlo integrated data envelopment analysis approach was able to give a better approximation of uncertainty. The ultimate aim of the paper is to empirically validate this conclusion with a case study that is the subject of on-going work.

ABSTRACT. The proactive safety approach provides an alternative way of addressing traffic safety issues without using historical crash data. In proactive safety studies, various traffic conflict indicators are employed to capture the risky events that happen more frequently in a traffic stream than the rare and random crash events. Such indicators are commonly known as the Surrogate Safety Measure (SSM), Notably, SSMs allow statistically significant safety analysis for various road infrastructures without waiting for several years of crash data. This paper provides a systematic overview of the studies focusing on proactive safety analyses. Based on the review, it was found that despite the growing interest and developments in proactive safety studies, there still requires further attention, especially in the case of low-middle-income countries. A few promising research gaps are discussed, which will provide future directions.

ABSTRACT. Road traffic crashes have become a noticeable concern in the field of transportation research. A road crash is an unexpected negative outcome of the growth in transport infrastructure sector. Repeated occurrence of crashes at a location leads to the formation of black spot. There are several definitions of black spots practiced in different countries. However, there is no global consensus on the definition of a road crash black spot. A scientific identification of such black spots is one of the initial steps towards development of a safer road network in any country. Thus, in various developing countries like India, the identification of high-risk locations for road traffic crashes can serve as a useful tool for the government to allocate their limited resources more efficiently to curb down crashes. This research has adopted GIS and associated two spatial analysis techniques to identify black spots on a case study metropolitan regional road network in Lucknow in the state of Uttar Pradesh in India. The research uses kernel density estimation to check for the clustering tendency of the crashes. The results have been validated using an alternate spatial analysis tool to check for spatial auto-correlation of crashes.

ABSTRACT. Road safety is the major concern for all countries. Road accidents in India constitutes almost 11% of road accident in India. Due to the significant economic losses and fatalities, road accidents are one of the main factors impeding the advancement of civilizations and economic prosperity. In India, around 60% of accidents occurs on National Highways and State Highways. Whereas, National highway constitutes only 2.03% of road network. The present study aims to identify accidental blackspots on a section of National Highway – 216, Andhra Pradesh State by studying the accidental data provided by the National Highway Authority of India (NHAI) during the calendar year 2018-2020. As part of study, Primary data and secondary field surveys were conducted during road safety audit period. In the present study for identification of blackspots, Weighted Severity Index (WSI) method used. Ranking Method was applied to rank each of blackspot based on WSI. During this study, basic causes of accidents were found out. Suitable rectification measures were classified in two measures; 1) Short-term measures and 2) Long-term measures, suitable measures were applied for each blackspots.Prioritization of blackspots, identification of causal factors and providing correct remedial measures for each blackspot is key for economic strategy.

ABSTRACT. Insights into how travelers use carsharing services can enhance the effectiveness of its operations. However, traditional users’ behavior survey data that involved detailed data collection, such as trip diary, is typically expensive, time-consuming, and prone to errors. In recent years, advancements in big-data techniques have enabled the collection and analysis of a relatively larger volume and variety of travel data with fewer resources and at a much faster speed. In this study, we explore the applications of big data in collecting carsharing users’ behavior in Bangkok, Thailand. The activity identification algorithm was developed to identify the type of activity of each trip made by carsharing users based on a service utilization dataset (August – November 2021), obtained from a prominent carsharing service in the city. The activity identification algorithm is based on the trip stop time, stop duration, and nearby points of interest (POIs). The outcomes of the algorithm are then verified with phone interviews. The outcomes show that the proposed algorithm can be used to comprehend the carsharing user behaviors and can support the integration of carsharing services with other public transportation modes to yield a more sustainable transport system.

ABSTRACT. Time series data that is spatially distributed requires tailored treatments to be analysed, as most time series modelling techniques are designed to handle observations of one unique respondent or location. Unlike classical time series techniques, feature-based methods do not look at the temporal pattern of observations sequentially. Instead, they mine data to develop insights about deeper layers of information. When the time series data is spatially distributed, features of one-time series observed for one location can assist with understating the observations fluctuations in the neighbouring zones. Such complications can be further amplified when imagery time series data as an emerging source of information is analysed. This study first discusses how imagery time series data is growingly used in the data analytics domain. We then elaborate on how complex network methods can be adopted to analyse spatially correlated imagery data in the context of night light data of Iran.

ABSTRACT. Because of its potential environmental and health benefits, cycling as a sustainable mobility mode has attracted increasing attention in recent years. To inform the planning of necessary cycling infrastructure (e.g., bike lanes), it is crucial to analyze and estimate the distribution of cycling activities on urban street networks. To capture spatial autocorrelation of cycling flows, prior studies often resort to classical spatial regression methods, which are limited in accounting for street network structures or uncovering nonlinear relationships. To address these issues, this study proposes a network-constrained graph convolutional network (NC-GCN) model to embed the detailed topological information of the street network for spatial regression. Specifically, the spatial weight matrix can be carefully designed to further incorporate prior knowledge about the street networks. We use cycling data from Washington, D.C. as a case study to estimate link-level cycling flows on the street network using diverse built environment and sociodemographic variables. The results verify the superior performance of the proposed model over the baseline methods, and show that a properly designed spatial weight matrix can indeed improve the prediction performance. The proposed approach can be extended to model different kinds of traffic flows, and guide the design and management of transportation networks.

ABSTRACT. The present work aims to identify the priority areas of interventions for the development of facilities so that the sustainable modes such as walking, cycling, and battery operated motorized IPT facilities are utilized as the first-and-last mile connectivity with the metro stations. The work is demonstrated with respect to a satellite city of Kolkata Metropolitan city which is soon going to be served by metro railway service. Attributes related to safety, security, service characteristics and infrastructural facilities have been selected from literature review and expert opinions which have been ranked by the users according to their importance perception. RIDIT analysis was used to obtain the importance ranking of these attributes. Finally, the heterogeneity in the importance perception of the attributes based on the socio-economic and trip characteristics of the users have been studied. Safety and security attributes achieved highest importance and the basic infrastructural facilities are found to be moderately important to most of the users for all the modes. Age, income, gender and educational background of the commuters are the socio-economic characteristics whereas trip purpose, public transport users, frequency of travel and distance of FLM are the trip characteristics which influence the importance perception of the commuters significantly.

ABSTRACT. The current study examines the priority areas that need improvement to make ferry service more appealing to commuters, demonstrated with reference to the twin cities of Kolkata and Howrah in India. This research proposes the use of a superior data collection mechanism, Best-Worst Scaling (BWS), to obtain data on the importance and satisfaction regarding 20 inland ferry attributes from ferry users. A two-stage analysis is performed to find the areas of improvement in the current work. Gap scores are estimated as a starting step to get an idea about the level of performance of the existing service facilities, while Importance- Satisfaction Analysis (ISA) combined with k-means clustering is used in the second stage for identifying the priority areas. The findings of the gap analysis show that 11 attributes have negative gap scores, which indicate dissatisfaction regarding these attributes, emphasising the need to improve ferry service. The priority areas of improvement include 6 attributes, out of which 4 are qualitative, signifying the importance of including qualitative attributes while making policy decisions to enhance ferry service. Several recommendations are given based on the obtained priority areas of improvement.

ABSTRACT. In many cities, shared micromobility services have become popular. These services contribute to the popularity of car-alternative mobility by promoting the use of micro-vehicles. Bike-sharing and e-scooter-sharing systems are examples of these services. Despite their promising potential, shared micromobility services are still marginal. To unlock this full potential, policymakers and service providers need to comprehend the wider implications of operational strategies of these services within the existing mobility landscape. This paper investigates the implications on demand, operation, and earnings of two strategic decisions: fleet size and pricing of shared bikes and e-scooters. This research relies on an agent-based transport simulation framework of the city of Lyon.

Simulation results indicate that shared micromobility services in Lyon compete against existing travel modes, especially public transit and walk. The extent of this competition is very limited due to the marginal share of shared bikes and e-scooters. Nevertheless, the potential of these services is considerable. Results indicate that this potential is unfulfilled in the case of Lyon and that it can be realized by appropriate strategies on the fleet size and pricing. In the case of Lyon, the current fleet and price strategies are sub-optimal from the users' and operators' point-of-view.

ABSTRACT. Air pollution is one of the most important causes of climate change, leading several countries worldwide to search for and identify solutions to tackle it. One of the most promising measures is the implementation of environmental zones in urban city centers, where the problem is greatest. In this direction, this study proposes the implementation of a zero-emission zone in the center of Athens, following the good practices of other European cities. The study defines the boundaries of the zone, the operational framework and proposes practices that will make Athens more sustainable. A questionnaire is developed to collect citizens' attitudes and perceptions towards the implementation of the zero emission zone, relating it to their daily transportation habits. The questionnaire included a stated preferences experiment to investigate citizens' mode choice behavior traveling to the ZEZ. A mode choice model is estimated showing that travelers are willing to switch to more environmentally friendly modes. In conclusion, the research promotes the reduction of the dependency on private vehicles and the adoption of 'green' transport technologies, while proposing the appropriate infrastructure developments to make the urban center sustainable for its residents and visitors.

ABSTRACT. Despite various motivation policies, recent battery electric vehicle (BEV) penetration rate in the UK is only around 1.8%. Most research analysing electric vehicle ownership in the UK is either based on stated preference data or includes plug-in hybrid vehicles in analysis due to sparsity of BEV ownership data; there is clear lack of research based on household revealed preference (RP) data. This paper aims to develop BEV ownership model using RP household-level data from the UK by discovering influential factors and/or validating findings in the literature. The UK National Travel Survey special licence data is used in this research to estimate series of binary logit models of BEV ownership as function of several sociodemographic, regional, and temporal factors, and discusses related policy implications. Household income, multi-vehicle ownership (due to range anxiety) and overnight parking on street (due to insufficient public charging infrastructure) are influential factors found that align with previous studies. Whereas households with mortgage loan, geographical attributes and certain household composition are new factors identified. We also present a region-specific future BEV ownership prediction model for the UK, which clearly suggests that improving public charging infrastructure, especially in certain regions of the UK, is required for widespread BEVs growth.

ABSTRACT. The development of intercity transportation systems can significantly impact regional economies and national land structures. This study offers a model to evaluate the effects of new high speed rail systems on economic and population structures based on spatial economics (also called new economic geography), which has rapidly developed in terms of theory and computational methods in recent years. We apply the current model to the new Japanese high-speed rail project, SCMAGLEV, and estimate the short and long run economic effects on population distribution. The results of the short run analysis are generally consistent with the intuitive expectation that large effects will be generated mainly in the areas around Tokyo and Osaka, which are the terminals of SCMAGLEV. In contrast to the trend in the spatial distribution of benefits in the short run equilibrium, the population is expected to decline in many regions in the long run. The long run results suggest that population agglomeration can develop in limited areas of the country.

ABSTRACT. The Eurotunnel is one of the largest private infrastructure projects and connects France and the United Kingdom. This paper offers a regional analysis for estimating overall economic impacts of the Eurotunnel on the directly connected regions South-East in the United Kingdom and Nord-Pas-de-Calais in France. Therefore, a counterfactual scenario is generated by using the synthetic control method based on 23 regions of France, the Netherlands and the United Kingdom (NUTS 1 level) from 1975-2015. So, the paper addresses the questions how the affected regions have economically performed compared to without the Eurotunnel. Moreover, the regional impacts due to the existence of the Eurotunnel are calculated based on this counterfactual scenario. Indeed, findings indicate that there are strong and positive impacts after the opening of the tunnel for the first years. However, these initially strong impacts are not consistent over time. Despite positive average economic impacts for the full period, the financial losses of the Eurotunnel can most likely not be compensated.

ABSTRACT. Cities of different sizes and functions in megaregions around the world have shown strong interests in more efficient and intimate transportation connections. Multi-layer regional railway networks (MRRN) have made the connections possible and contributed to regional economic development by improving inter-city accessibility. However, how cities’ economies in a megaregion would benefit from MRRNs over time is largely unknown yet. In this paper, an MRRN including the corridor high-speed railway network (CHSRN), the inter-city high-speed railway network (IHSRN), and conventional and regional railway network is defined and described in detail. Indicators for a city integrating into an MRRN such as Shannon entropy, clustering coefficient, and PageRank node centrality are proposed based on complex-system algorithms. We further design a Spatial Dynamic Durbin model accounting for time lag effects to estimate the impacts of the MRRN on regional economic growth from a spatiotemporal perspective. The results show that CHSRN and IHSRN complement each other in promoting coordinated development of the regional economies in different stages of urbanization and industrialization. Findings from the theoretical and empirical analysis can potentially help understand the way megaregions are reorganized by MRRN connections and achieve long-term balanced economic sustainability throughout the region.

ABSTRACT. The COVID-19 pandemic caused business shutdown worldwide because of which there was a significant reduction in roadway traffic movement and vehicle miles travelled. This, in turn resulted in lower gasoline sales. This paper assesses the economic impact of reduced vehicle miles of travel due to COVID-19 and determines the impact on the revenue generated in the highway trust fund due to reduced gasoline taxes collected in Maryland, USA. An economic loss assessment is performed using gasoline sales and vehicle miles of travel. The effect of declining Annual Average Daily Traffic (AADT) between 2018-2020 is analyzed for the 23 Maryland Counties and Baltimore city, to identity Counties that were significantly impacted due to the declining AADT. Finally, a machine learning model using artificial neural network is performed to predict the significance of various Counties subjected to declining AADT during COVID-19. The results are useful for assessing the economic impact of COVID-19 on roadway improvement projects owing to reduced gasoline sales.

ABSTRACT. Northern Cape has been one of the provinces that make a relatively small contribution to South Africa's gross domestic product. However, there is room to improve the province's contribution through improved connectivity with the rest of the provinces and targeting specific industries with high concentration. The question that remained unclear was how the transport sector facilitates the linkage within Northern Cape and between the Northern Cape and the rest of South Africa. This paper investigated this issue using an approach that employed Network Analysis and I-O. The economic analysis reveals that Northern Cape's Other mining and quarrying sector is the most concentrated. However, the transport and storage cluster is also among the strong sectors in Northern Cape. Network analysis shows that the mining industry, metals, and agriculture are Norther Cape's anchors, while transport and storage are among the few sectors that show significant intra- and inter-regional linkages. The results of this study provide important insights into the industries that should be actively cultivated to maximise their economic contribution. Policymakers can categorise the sectors into different clusters as 'mature', 'star', 'transforming', and 'emerging'; each cluster necessitates a customised policy decision. The transport sector plays a central enabling role.

ABSTRACT. Many provincial and local governments envision the possibility of zero fatalities from road traffic accidents in the near future. Developing a proper accident prediction model to support such a vision is crucial. This study explores determinants of road collisions, emphasizing harsh winter weather. It then compares classical and Machine Learning models for collision prediction. Furthermore, it introduces the most influential factors in crashes concerning severe winter weather. All study parts are performed on the collisions data in Calgary, Alberta, Canada, between 2017 to 2020. It is shown that all the weather attributes are correlated to collisions. It shows the importance of considering weather attributes in accident analysis and prediction. Based on the nature of the collision dataset, which is tabular and heterogeneous, Neural Networks showed higher performances than the other investigated models, with 92% accuracy. The developed models would allow transportation planners to apply these models for evidence-based policy implementation, including new speed limit recommendations. For instance, a speed limit reduction on one of the busy highways from 100 to 90 km/h resulted in a 5% accident reduction and consequently 4.8% less daily CO2 emissions, equal to the amount of CO2 emitted by 10 Canadians in their households per year.

ABSTRACT. Classifying driving behavior can reduce the severity of crashes on the road. Roundabouts are particularly interesting because of the interconnected interaction between different road users at the area of roundabouts. This study investigates driving behavior at roundabouts using a data-driven unsupervised machine learning to classify driving behavior at three roundabouts in Germany. We used a dataset of vehicle kinematics to a group of different vehicles and vulnerable road users (VRUs) at roundabouts and classified them into three categories (i.e., conservative, normal, and aggressive). Results showed that most of the drivers proceeding through a roundabout can be mostly classified into two driving styles: conservative and normal because traffic speeds in roundabouts are relatively lower than other intersections. Results showed that about 77% of drivers who interacted with pedestrians or cyclists were classified as conservative drivers compared to about 42% of conservative drivers that did not interact or about 51% from all drivers. Drivers tend to behave abnormally as they interact with VRUs at roundabouts, which increases the risk of crashes when an intersection is multimodal. Results of this study could be helpful in improving the safety of roads by allowing policymakers to determine the effective and suitable safety countermeasures.

ABSTRACT. A methodology to investigate the safety issue of merging and diverging sections of the toll plazas using high-quality trajectory data obtained from Unmanned Aerial Vehicles (UAVs) is proposed in the present study. The study is conducted at two different toll plazas located in the western part of India operating under heterogeneous non-lane based traffic, making the inter-vehicular interaction complex and critical to study from a safety point of view. The conflict studied are rear-end and angular conflicts using the trajectory data and time to collision as the surrogate safety measure. The ratio of rear-end and angular conflicts at Kamrej is 80:20 and for Boriach it is 73:27. The significant spatial presence of conflicts has been found in 90-180m in diverging, and for merging, it’s 100-210m for both the toll plazas. Conflict modeling using multivariate linear regression to evaluate the conflict risk index (CRI) has been proposed. The correlation between CRI and mainline traffic volume is found negative and the correlation of CRI with speed, the proportion of cars, Heavy Commercial Vehicles (HCVs), and lane change are positive. The study finds the critical safety issues at toll plazas and suggests mitigation techniques.

ABSTRACT. Safety related studies are often hindered by the lack of robust accident data. Consequently, measures proposed based on the underreported accident data with might be ethically unbiased until another road accident due to the same cause is observed again. Traffic conflict technique bypasses the dependency on road accident data and provides proactive means of assessing road safety. In the present study, empirical trajectory data over four signal cycles from four different isolated signalized intersections is used to study rear-end conflicts. Then using several traffic parameters, rear-end conflict probability is modelled to develop real-time safety assessment models and work as a safety performance function. Two surrogate safety measures are sued in this study. Additionally, after model development, a policy of speed restriction is tested for its effect on mitigating rear-end conflict probability. A positive results in decreasing the rear-end conflict probability for individual vehicle and also the complete traffic stream is observed.

ABSTRACT. This paper explains dilemma situations in autonomous driving. It critically assesses the various moral and legal aspects based on different existing legal frameworks. With the help of several illustrative examples, it provokes critical thinking and finally presents the author’s views on if the existing legal framework is competent enough to appropriately address the moral aspects of dilemma situations.

ABSTRACT. Land use is an important factor that cannot be ignored in trip distribution forecasting. An accurate and reasonable trip distribution method for construction projects is the key content to play the role of traffic impact analysis (TIA). In order to fully consider the land use characteristics and improve the accuracy and applicability of the trip distribution method in TIA, a distribution forecasting process of trips generated by construction projects is proposed based on a joint model of destination and mode choice. After establishing a comprehensive variable set, the joint model is calibrated according to the Shanghai fifth comprehensive traffic survey. The calibration results show that the connection variable (logsum) is valid, and the area of commercial and business buildings is the most important variable affecting travellers’ destination choice in the morning peak. Finally, a specific project case in Yangpu District is selected, taking car travel as an example. The mean relative error of the predicted turning traffic volumes and road traffic volumes are 22.04% and 15.65%, which verifies the validity of the proposed method. This research is helpful to improve the trip distribution method in the TIA, and ensure the healthy development of urbanization construction and urban renewal.

ABSTRACT. Traffic congestion often occurs in the exit ramp area of expressway.The systematic study of its congestion influencing factors is extremely important to improve the effectiveness of road networks. Both the traffic status of the connected expressway and ordinary road need to be considered at the regional level. And it should be analyzed at lane level rather than at the cross-sectional level. By analyzing traffic parameters including traffic flow, lane operating capacity and speed etc., this paper constructs seven variables to build panel regressing model. The model is selected to do the analysis for each lane of the expressway in the exit ramp area. The main congestion influencing factors in the exit ramp area are identified from the seven variables based on the regression results. The data is from loop detectors of North-South Expressway exit ramp area in Shanghai. The results show that the influencing factors which have a significant effect are exit ramp traffic flow and ratio of flow to lane operating capacity in ordinary road connected by exit ramp. The outermost lane is more affected by ramp approach traffic than the inner lane near the centerline of the road. It provides reference for the refined traffic management of expressway.

ABSTRACT. Traffic microsimulation modeling is growing in demand due to its easy applicability and its efficiency in checking the effectiveness of any traffic management system prior to its application. In developing countries, the application of traffic management systems becomes complex due to the heterogeneous nature of traffic in these countries. Hence it becomes necessary to calibrate the microsimulation platform before applying any traffic management system to it. In this study, an approach for calibrating VISSIM for heterogeneous traffic conditions is developed. The methodology was applied to two intersections in Ahmedabad city. The sensitive driving behavior parameters are identified by carrying out multiple sensitivity analyses by considering capacity as a measure of effectiveness (MOE). In order to check the effect of group parameters on MOE, a two-way ANOVA method was used. The study identified eight sensitive parameters affecting MOE. Based on these eight parameters, two equations with respect to the intersections were developed using linear regression. The optimum value of the parameters is obtained by the Genetic Algorithm by keeping 95% confidence level. Validation is done by calculating GEH statistics and RMPSE of the traffic volume.

ABSTRACT. The imbalance problem can cause models commonly used to study model choice, such as logit models, to produce biased estimates for the least selected alternatives and consequently have high prediction errors. On the other side, the data collection process in many applications is costly and time-consuming. This paper presents a technique to reproduce data from a travel mode choice experiment and generate new observations similar to the original ones. Specifically, we use the generative model known as Conditional Variational Autoencoder (CVAE). We empirically evaluate our approach using three famous travel mode choice datasets. Then, a Multinomial Logit Model (MNL) was estimated with the original and augmented data for each dataset. The results showed that using the CVAE algorithm approach for augmented the dataset improved the overall predictive performance of the MNL model, moreover, significantly improved the sensitivity and F1-Score of modes that were less commonly used.

ABSTRACT. Level of Service (LoS) is the most common measure of effectiveness in evaluating highway performance. The knowledge of LoS is crucial to traffic engineers for effective planning, designing, analyzing, and operating a roadway system. This study assesses the performance of four-lane divided rural highways by considering the traffic speed and density parameters. These performance measures are used to quantify the LoS and develop the respective thresholds. The traffic data was collected from the six Indian National Highways in both directions of traffic using an infrared sensor-based device. The clustering technique was used to analyze and estimate the LoS threshold values. From the k-means clustering analysis, the optimum number of clusters was decided. Further, the traffic speed and density data were clustered into LoS categories based on the silhouette values. The study results reveal that with decreasing traffic speed and increasing traffic density, the traffic condition varied from LoS A, representing a free-flow condition, and LoS F representing a congested condition. These LoS thresholds that are computed using the k-means clustering method could benefit other roads with similar traffic situations.

ABSTRACT. The cybersecurity of Connected and Autonomous Vehicles (CAVs) is a complex dynamic challenge involving various interconnected factors of diverse nature that cannot be accomplished through hardware or software integration. It is the property of the entire system components involved in the CAV-based Intelligent Transportation Systems (ITS). There is no formal model that dynamically assesses CAVs cybersecurity in a consolidated framework to address technology challenges, human threats, and public cybersecurity awareness. Potential cybersecurity prevention techniques are primarily illustrated for particular circumstances without taking into account the whole picture of CAVs operating in ITS. To address this knowledge gap, this study aims to develop a System Dynamics based Stock-and-Flow-Model to address technology challenges (software risks, hardware constraints, network limitations, communication safety, and log files), human threats (hacker's capability, criminology theory), and public cybersecurity awareness. The model considers the relationships between these pillars in ITS operation to envision emergent long-term behaviours as well as indirect consequences. The proposed model's structure and behaviour are tested and used to perform scenario analyses by four functional metrics: hacking attempts, hacks defended, communication safety, and CAV adopters. The variations of these indicators spotlight the enhancement techniques for a robust cyber framework.

ABSTRACT. Transportation is at the heart of almost all economic infrastructures. Proper planning of transportation infrastructures is required in delivering efficient, low risks, and high benefits to the people. In the early stages of such projects, it is critical to evaluate various proposals and immediately discard those which do not pass the requirements for further consideration. In this study, an excel-based tool that can calculate the possible benefits of a transportation project based on a preselected set of criteria was developed. The inputs would come from the output of a transportation simulation model. This tool will process the inputs and contrast the benefits against the associated costs, where the comparison is in monetary units. The tool has demonstrated its use in the tasks of LGU transport planners. Various seminars and trainings have been conducted to introduce the tool to the target users. Moreover, a user manual and video tutorial have been developed to further aid the users.

ABSTRACT. Understanding the travel mode choices of commuters in Mobility as a Service (MaaS) is crucial to improving the service level of MaaS. This paper presents users' travel utility functions in terms of MaaS characteristics, including travel comfort, travel time, travel carbon emissions, and travel costs. Based on the proposed utility functions, a multimodal integration choice model (MICM) is proposed to target multimodal combination travel and modal path integration choice in MaaS. It contrasts with a single-modal step-by-step choice model (SSCM), which targets conventional travel scenarios. Using the travel navigation data of the Baidu Map, numerical examples compare the MICM with the SSCM. Sensitivity analyses concerning the number and the value of time (VOT) of commuters are presented. The results show that MaaS will balance the user flow for each mode, and in congested scenarios, it would facilitate users to shift to sustainable travel modes. For medium-VOT and high-VOT users, MaaS system outperforms conventional travel system regarding user utility, carbon emissions, and public transportation operator income. While for low-VOT users, it has no superiority. Therefore, policymakers implement MaaS are helpful for reducing negative utilities. For low-VOT users, suitable reward mechanism can increase users’ engagement, which will contribute to the MaaS development.

ABSTRACT. To improve the resilience of urban transportation hubs facing fire disaster, it is vital to evaluate their fire resistance under different resources allocations schemes. In this paper, in order to obtain the optimal resource allocation schemes for high-speed rail station under a simulated fire disaster scenario, a network data envelopment analysis (NDEA) method is developed. A case study involving the Beijing South Station is carried out. A comparative analysis of the assessment results of different schemes reveals the importance of considering fire resistance resource allocations. It is found that the proposed DEA method has a more accurate evaluation ability and provides insights for the allocation of fire resistance resources in transportation hubs. Analyzing the index data of the relatively optimal plan shows that several optimal schemes have differences in improving the resistance of the transportation hub and the high index in a certain aspect cannot make the fire resistance effect optimal. It indicates that multiple aspects should be considered in the allocation of fire resources for the Beijing South Station. This is important for transportation hub managers to consider the influences when allocating fire resistance resources.

ABSTRACT. Highway work zones lead to an increase in crash risk. Implementing temporary traffic control countermeasures and understanding drivers’ risk perception can mitigate these risks. Controlled experiments in a driving simulator were used to study several temporary traffic countermeasures’ effects on speed. These include variable message signs, dynamic speed displays, rumble strips, and lane widths. A questionnaire was devised to catch drivers’ risk perception on typical highway work zone layouts variables. A factor analysis was conducted to find the underlying variables for various highway work zone layouts presented in the questionnaire. A linear mixed-effects model was used to capture the effect of the studied countermeasures on speed, as well as the correlation between the participants’ questionnaire answers and their speeds in the driving simulator considering the latent variables from the factor analysis. The results reveal the most dangerous highway work zone layout variables and the best mitigation ones according to the driver’s perception. Participants that drove more frequently drove at a higher speed in the driving simulator and the higher the perceived risk by the drivers the lower their speed. Variable message signs and rumble strips at the entire work zone show great potential in reducing speeds.

ABSTRACT. Characteristic of traffic flow changes due to COVID-19 pandemic. Then prediction of traffic flow during COVID-19 pandemic is left as an issue. To find the solution, firstly, changes of detected road traffic flow (DRTF) compared to that of 2019 under the same conditions in Toyota city are analyzed. Generally, the DRTF decrease. Monthly change rate of the DRTF fluctuated during 2020 in 83.6%~98.3%, however, they keep relatively stable during 2021 in 88.7%~93.2%. Change rate of one-day-average DRTF for different weekdays, and for three long holidays also have different trends in 2020 and 2021. Moreover, change rate of one-day-average DRTF for different time of state of emergency declarations (SED) have special characteristics. Secondly, regarding the analysis above, a series of Long Short-Term Memory (LSTM) Models which consider impact of COVID-19 is developed to predict one-day DRTF. The model with parameters of day of week, if long holiday, if during COVID-pandemic, if during emergency declaration, number of infected people of previous day, and turn of day in one week according to volume of traffic flow has best performance.

ABSTRACT. Car sharing is one of the shared mobility services that can potentially cause a reduction in car ownership. Since car ownership is influenced by a wide array of socio-demographic factors beyond car sharing, the association between car ownership and car sharing is problematic. Therefore, the present paper resorts to the 2012/2013 until 2020/2021 waves of the German Mobility Panel: a treated group of car sharing subscribers is identified and related car ownership levels are compared with those of a control group, considering a wide array of socio-demographic variables. Observed differences are still strong and they can therefore be safely associated with car sharing membership. Additionally, the panel nature of the data allowed for studying the patterns of car sharing subscription and unsubscription together with the changing levels of car ownership. An asymmetry of behaviors emerged, since the observed decrease in car ownership when subscribing is stronger than the increase when unsubscribing. It is then shown how the net balance in terms of number of substituted cars is changing according to subscription and unsubscription patterns, even fixing the annual growth rate of subscribers. Additional scenarios are finally proposed assuming different annual subscriber growth rates, according to recently observed trends.

ABSTRACT. While travelling, accidents make us think of our safety and the mode of transport. The choice of mode of transportation to travel the initial and final part of the trip is influenced by factors like time, frequency, cost, service quality, safety and more. While all the variables have been dealt with in literature, soft factors like attitude and perception of users have been investigated in limited studies. The research intends to identify the influence of safety perception on mode choice for first and last-mile connectivity and examine whether the perception of the traffic safety of the commuters impacts the mode choice for the first and last-mile connectivity for the mass transit system of Lucknow, India. A primary survey is performed to collect the required data, which is analysed with the help of correlation and multinomial logit regression. The analysis shows that factors like vehicular condition, safety precautions, driver characteristics, and supporting infrastructure need to be investigated to improve the safety perception of commuters. These factors establish the relationship between a commuter's perception of safety and their mode selection, forming a more sustainable mass transit feeder system by promoting and enhancing factors that discourage public transportation use.

ABSTRACT. Citizens take part in different activities to satisfy their needs, to invest in their socio-economic progress, participate in social and health activities that improve their well-being. However, activity participation is influenced by many factors in the built environment, but also individual’s attributes. Herein we analyze activity participation and travel through sequence analysis. This method explores sequences of daily activity and travel employing techniques from the sequencing of events in the life course of individuals. Studying sequences of daily episodes (each activity and each trip) considers the entire trajectory of a person’s activity during a day while at the same time considering the number of activities, order of activities in a day, and their durations jointly. We applied this method to a sample of residents in the Metropolitan Area of Barcelona (RMB) in the 2018, 2019 and 2020 EMEF Travel Surveys. The EMEF2020 deserves a particular analysis since activity patterns are expected to vary compared to pre-COVID19 spread. We have focused on that fragmentation in activity participation over the mean among persons in specific gender, age, activity and transportation mode.

ABSTRACT. Assessment of travel behaviour is one of the prominent research purposes in current literature for which predictive choice models have been widely utilized. Though these models provide substantial information on the decision-making process, there is little account in the literature on how to evaluate and validate the prediction performance of the same. Therefore, it is imperative to pay attention to the validity of models which helps in extracting information from the observational studies. There are several internal validation techniques which check the performance of model on independent data more accurately than considering the naïve approach of using the same training data for evaluation. We consider and compare several techniques like in-sample, split-sample, cross-validation, and bootstrapping method for this purpose. Further, various absolute accuracy measures were adopted to evaluate the predictive performance. We found hold-out validation techniques perform better to provide optimistic results when compare with apparent performance with full-population model. Our study posits a procedure to test and display model performance which would greatly assist researchers and practitioners in understanding the generalizability and transferability of the model. This study will be useful to the transport practitioners to focus on the validity of model results equally to the developing innovative models.

ABSTRACT. Although the road funding framework in Namibia has been regarded as an exemplary model for developing countries, recent evidence has shown that The Road User Charges (RUCs) generated through the Roads Fund to supplement the fiscal budgetary allocations are not sustainable as the charges are not efficiently priced to generate optimal funds. Hence, this study was aimed at exploring alternative financing models for roads for Namibia and other developing countries. The Road Network Evaluation Tool (RONET) model was applied to conduct a strategic assessment of the road network funding requirements and analyse the extent of the funding gap on both the primary and total road networks. Further, a scenario-based evaluation of alternative financing models was performed. Study results showed that the road user charges, particularly the fuel levy is set too low to generate sufficient revenue to meet the optimal funding scenario for the road network in Namibia. In addition, the study found that the introduction of a Distance-Based RUCS on the primary road network in Namibia with private sector participation is potentially feasible and could help capture some of the costs of road use that are currently not captured by the road user charges.

ABSTRACT. With the development of communication technology and V2X infrastructures, connected and automated vehicles (CAV) have great potential for increasing traffic operating efficiency. In urban areas with signalized intersections, it is crucial to plan CAV trajectories according to the collected ambient vehicle states and the signal timing. To address this issue, this paper studies the centralized two-dimensional trajectory planning (CTTP) problem before an isolated intersection. Both the longitudinal trajectory as well as the lane-changing timing and sequence are involved in the planning. Firstly, we elaborate an integer programming model, which can acquire optimal solutions directly. For computational tractability, we further propose a two-stage optimization framework for practical implementation. The first stage assigns vehicles to periodic green phases through a vehicle assignment algorithm and tree-based heuristic search algorithm; the second stage plans vehicle trajectories through an optimal control model. A rolling horizon scheme is utilized to deal with the randomized issues of varying traffic. The proposed framework is evaluated through simulations conducted in SUMO, which demonstrates that the proposed trajectory planning framework can significantly reduce the delay and increase the saturated throughput. Moreover, the computation time is negligible, even in cases with a large scale of vehicles.

ABSTRACT. Due to the facilities presented by air transport, it has been growing more and more over the years. However, the airline industry is also a major generator of pollutants. Thus, airport environmental sustainability represents a relevant issue for society because when absent, its negative consequences interfere not only with airport users but also with the environment used by all. In this context, this article aims to evaluate the sustainable performance of Brazilian airports registered concomitantly in the second and third editions of the project "Sustainable Airports" of the National Civil Aviation Agency (ANAC). We also analyze what needs to be improved for the project to be a monitoring instrument and not only a marketing tool. So, it is necessary to establish a metric, deepen the criteria, and use the as a basis the 2030 Agenda as a basis to assess the sustainability of airports in Brazil. It is also important to note the requirement for airports to register in the annual editions for better project efficiency and the need to have a standard for the evaluation criteria of airports in the editions so that we can compare the evolution of airports throughout the editions of the project.

ABSTRACT. From an airport perspective, it is important that sustainable employee surface access plans are informed by employee stakeholder views, attitudes, and preferences. A comprehensive Bristol Airport employee journey-to-work survey was performed during the summer of 2022 with 326 responses received from 39 different employers, including 107 from the airport operator. The most popular travel choice amongst respondents was single occupancy petrol or diesel vehicles, which represented 62% of all employee journeys. The remaining 38% consisted of single occupancy hybrid/electric journeys (15%), Bus trips (13%), Multiple Occupancy vehicle trips (5%), Cycling (2%), Walking (1%), Booked taxis (1%) and Rail/Bus combinations (1%), representing a significant proportion given the airport’s regional location. Factors affecting modal choice related to overall trip cost and convenience, with the environmental impact of travel choices holding a growing but limited significance. The topography of the airport hinterland and the rural nature of the transport network were considerable influences affecting modal choice. Although more sustainable choices are growing, financial or other incentives would need to be provided to compensate for perceived changes to travel costs and convenience, with the most sought-after amongst Bristol Airport employees being free or discounted public transport and support for electric and hybrid private vehicles.

ABSTRACT. This paper analyzes the different climate policies that are used by the EU in the aviation sector.The efficiency and acceptability depend on the strength of the international agreements (Paris 2015, CORSIA 2020) and on the implementation of the policy within the EU. Five different policies are discussed: carbon taxes, tradeable emission permits, the implementation of the CORSIA agreement, Sustainable Aviation Fuels (SAF) blending mandates and fuel efficiency standards for new aircrafts. The Paris and the CORSIA agreements are both weak agreements where, in the absence of sanctions, the implementation depends on the will of the political majority of the moment. For intra EU aviation the insertion of aviation in the EU-ETS with auctioned emission permits is the most efficient and it can result in net zero emissions in 2050. Subsidies for R&D in fuel efficiency and new fuels have a positive spillover via better aircrafts and better fuels for the non-EU aviation. SAF mandates are inefficient but are more acceptable for the airlines and intensive air transport users. The EU’s current implementation of CORSIA i would command to use a permit price higher than the EU – ETS permits.

ABSTRACT. Incorporating environmental awareness into consumer purchase decisions can play an impor- tant role in moving the economy towards sustainability. Consumers’ incentives in this area remain understudied. We integrate the doubly randomized preference trial (DRPT) and the randomized conjoint experiment to identify the heterogeneous impacts of providing carbon footprint informa- tion on consumers’ choice among hypothetical long-haul international airline itineraries. DRPT allows us to identify heterogeneous effects even where the consumer types are not observable. We use primary data obtained via an online survey conducted in Japan (N=32,610). The results indicate that targeted provision of information significantly influences consumers’ purchasing de- cisions. We define the consumers who choose to observe carbon footprint information rather than mileage accrual rate information in making ticket purchasing decisions have higher environmental awareness, and find that the provision of carbon footprint information increases the purchasing probability of consumers with higher environmental awareness by 12.3%. When the level of carbon emissions increases by 50%, respondents with higher levels of environmental concerns are 17% less likely to purchase a ticked than those for whom environmental concerns were not a priority. Our results have implications for design and effectiveness of environmental awareness campaigns in transport sector.

ABSTRACT. As gateways in the air transport network and interfaces between modalities, airports serve a critical role in sustainable development. Targeting the world’s 150 busiest airports in 2019, this paper aims to extrapolate the alignment level of global airports with the 17 SDGs and to further investigate the factors affecting such alignment. The finding suggests that 58% of airports are not aligned with the SDGs, while 2% and 17% are aligned at a low and medium level, respectively. In contrast, 23% of airports are recognized as highly engaged, which not only embrace a series of dedicated actions to the SDGs but also propose associated indicator frameworks to closely monitor and track their progress towards these goals. In addition, the 17 SDGs reveal differences in terms of their tendency to be aligned by airports. Among the airports aligned with SDGs, there is a significant consensus reached regarding SDG 13, SDG 9, and SDG 8, with over 90% of airports choosing these three SDGs for alignment. The outcomes also signify that airports with higher passenger traffic volumes and located in Europe are more likely to align themselves with the SDGs.

ABSTRACT. We estimated the effect of surface metering technology deployed at Charlotte Douglas International Airport (CLT) by the National Aeronautics and Space Administration (NASA) and the Federal Aviation Administration (FAA) on fuel and CO2 savings. We employed a difference-in-differences strategy, covariate-balancing methods, and a fixed-effects model. Our estimates from the daily panel of US carriers from November 2015 to November 2019 suggested that about 12.241 kg (95% confidence interval (CI) 19.948 – 4.358) of fuel and 37.702 kg (CI 61.441 – 13.422) of CO2 could be saved per flight even when the single-engine taxiing (SET) rate was as high as 75% during the entire deployment phase. At the same time, our results suggested a concerning pattern: the fuel and CO2-saving effects of the technology were not observed when compared to slot-controlled airports.

ABSTRACT. Logistics systems play a fundamental role in facilitating the movement of goods within a country. Maritime transport and logistics, as a subset of the nation’s logistics systems, makes a significant contribution towards economic development of the country. This strategic importance motivates many countries to develop and implement maritime logistics policies to improve their national economies. However, those policies often fail to achieve their intended result due to the complex and complicated nature of the maritime logistics systems, largely stemmed from interactions of multiple actors working in the systems, such as freight forwarders, port terminal operators, and shipping lines. This paper adopts a value chain perspective in order to simply outline those complex natures of the systems by identifying existing interrelated logistics activities of maritime logistics service providers that are expected to create a value to the economies. A conceptual framework is established from comprehensive literature reviews with the purpose of analyzing the role of maritime logistics systems in the national economic development from a value chain perspective. A proposition drawn from this conceptual framework could be used as a basis for an empirical investigation to better understand the nature of complexity being embedded in the maritime logistics systems in general.

ABSTRACT. Procurement relations are one of the areas where sustainability can have the most visible impacts on firms. Ocean transport is one of the most widely outsourced services globally both by shippers and by freight forwarders, as container ocean transport is never carried out by shippers using their own ships, in contrast to bulk transport. However, how logistics firms use sustainability criteria to select ocean transport service providers and how sustainability contributes to value creation between shippers/freight forwarders and ocean freight transport service providers has seldom been investigated. This article investigates value creation through quality improvement and sustainability practices in ocean freight transport. It makes use of a case study of an ocean carrier, combined with interviews and survey data to investigate how liner shipping companies can make use of high-quality and sustainable operations to provide their clients with better service and to create logistics value. A novel aspect of this research is the use of sustainable supplier management concepts in the context of maritime logistics. Sustainable sourcing explains how the sustainability requirements shippers have in sourcing ocean freight services define procurement relationships and how shipping companies can use sustainable procurement strategies to contribute to value creation.

ABSTRACT. The benefits of ports as vital elements of global transport systems are undisputed and widely covered in the scientific literature, but the fact that costs and benefits are asymmetrically distributed between the port city and its hinterland is less often addressed. The purpose is to inventory port-city interface literature, define port-city development stages and analyse how the port affects the surrounding city. The generations or stages are denoted First – Land-sea interface; Second – Expanding industrial and commercial centre; Third – Logistics node, and Fourth – Distributed terminals. The ways, in which the presence of a port affects a city is structured along economic, environmental and social sustainability. The discussion takes a Middle and Low Income Country perspective, with a focus on Mombasa, Kenya, and it is summarised in a table. The table provides a mapping of typical positive and negative port-city interactions based on the port-city development stages and aspects grouped along the three main pillars of sustainability.

ABSTRACT. The tanker freight market is highly volatile and unpredictable, creating opportunities and risks for operators. The observation of historical data reveals that there are times of extreme deviations of freight rates from their mean values. Those periods have not been analyzed thoroughly in the relevant maritime literature. This study employs Extreme Value Analysis (EVA) to model the stochastic behavior of tanker freight rates at unusually high - or low - levels. Following the Block-Maxima approach, the study provides estimations of the probability of extreme values of the Baltic Dirty Tanker Index (BDTI). To the best of the authors’ knowledge, this is the first time that this methodological approach is implemented in the context of the tanker freight market. The findings of this research can assist operational and investment decisions in the tanker sector, within the framework of ship Life Cycle Assessment.

ABSTRACT. Autonomous inland shipping is introduced to increase inland shipping competitiveness and promote the modal shift towards sustainable transport solutions. This innovation has the potential to disrupt the existing inland shipping industry paradigm. This study identifies the autonomous inland shipping innovation characteristic according to the diffusion of innovation framework by Rogers (2003). This study uses a literature review methodology to collect data. Moreover, this study suggests a framework and stakeholder analysis based on published articles for a better understanding of autonomous inland shipping according to current knowledge. The results reveal that the topic is still developing, and there are opportunities to facilitate the industry's improvement.

ABSTRACT. Seaports are perceived as multimodal hubs of the logistics supply chain where various transport modes intersect to exchange goods shipped by high capacity vessels. Increasing trade and capacity constraints are making this area a major contributor to GHG emissions. To plan and conduct successful GHG management programs, it is critical to develop an appropriate assessment approach that fits well with the operating and geographical context of the given port. Several models and methodologies for assessing GHGs are available for port contexts, but their generalization is challenging for many reasons, notably because of the specific features of traffic within the port. Therefore, this paper presents an assessment model for road transport emissions in the urban port context based on an in-depth study of the traffic per port area and on parameters drawn from several real data sources. The output showed the pattern of GHG emissions by zone and provided an outlook on how policymakers could achieve GHG reductions plan. An extension of this model to the city area surrounding the port is under discussion to achieve a suitable model for city side traffic emissions. Furthermore, adopting a real-time microscopic model, in the future, may better support decision-making about GHG management.

ABSTRACT. Waterway maintenance plays an important role in efficiently transferring goods. The maintenance decisions, including dredging, depend on the sediment accumulation that is highly dependent on the shoaling rate. The shoaling caused by tidal movement or channel characteristics, can change the dredging depth. Therefore, a better understanding of shoaling rate distribution is a requirement to perform dredging more efficiently. This study proposes a wide range of statistical methods to analyze the model distribution of shoaling rates at reach and sub-reach levels along the Ohio River. The shoaling data is generated from the Corps Shoaling Analysis Tool (CSAT) developed by the US Army Corps of Engineers. This paper investigates the distribution shape and degree of symmetry of distribution to specify the appropriate distribution model for shoaling rate. It also measures the fitting performances. The results show that the behavior of sub-reaches is different from that of the reach and depends on the location.

ABSTRACT. This paper investigates the possibility of using Short Sea Shipping (SSS) as a sustainable modal alternative by analyzing data collected from shippers in the New York State Capital Region. To this effect, qualitative and quantitative approaches were jointly used. The qualitative analysis focused on exploring in-depth interviews with the decision-makers regarding the drivers and the barriers to firms shifting to SSS. The quantitative efforts include estimating discrete choice (ordinal logit) models to assess the influence of four key governing aspects (leadership buy-in, emergency logistics, public policy, and sustainability) on the probabilities of shifting to SSS supported by the findings from the qualitative part. This paper also includes a comprehensive description of various variables, factors influencing the current mode choice, shippers’ perceptions, and willingness to use SSS. The results showed that firms currently having higher truck share showed fewer chances to switch to SSS unless in emergency situations. Unfortunately, sustainability is the least valued by most of the participants in choosing SSS. Hence, lower costs and better service are essential. The ordinal logit models provide a potential tool for policymakers and freight planners to estimate the probability of firms choosing SSS over the current mode.

ABSTRACT. The competitiveness of a company depends to a large extent on the innovations it implements. Digital innovations provide solutions through which shipping companies may improve on efficiency and performance potentially leading to changes to their business model. These changes come with risks which often are not properly assessed, especially those that will eventuate during operation. Using grounded theory approach, relative risk management data was collected from two shipping companies and combined with data retrieved from relevant publications leading to the formulation of a risk register framework to guide the risk management process. The need for an unbiased risk assessment was also highlighted, while further research is needed with respect to the impact of risk assessment on digital innovation adoption in the shipping industry.

ABSTRACT. In near coastal environments, nautical charts provide crucial information for navigation and routing both in real-time operations and during planning stages. Cost of data collection as well as capacity constraints in the processing pipeline make reliable bathymetric information in such areas sparse. Prioritization rules can help guide the efforts to where information is the most valuable. AIS data provide accounts of real ship movements, indicating both desirable paths and minimum depths. We propose a statistical model for combining sparse bathymetric soundings with AIS observations for improved prediction of depths for generation of feasible transportation corridors. The method relies on viewing AIS draughts as censored observations of the true depth. A case- study is performed for the southern archipelago of Gothenburg using the program R-INLA. Non-stationarity caused by having boundaries with known (zero) depth and holes (land) in the domain is handled through discretization. Varying amounts of AIS data, ranging from none to 1824 observations, are used in the experiments. Results show predicted depths within the range of data values, and that inclusion of AIS data serve to push the field down to ensure that traverseable areas are predicted as such revealing corridors in narrow passages where bathymetric soundings are lacking.

ABSTRACT. Shipping on the St. Lawrence has always had to confront issues such as water levels and ice conditions. In the past these challenges were addressed by major engineering solutions, such as dredging and the construction of canals and dams. Today, information technology, particularly digitalization, is being applied to these problems as well as new challenges such as collisions between ships and cetaceans. Some consider these developments as a step in the development of an information maritime highway, that is a precursor to the introduction of automated shipping. It is evident that the technologies provide information on a wide range of environmental conditions in real time that enhances the safety and commercial operations of shipping. It is also clear that the diversity of environmental conditions along the 1,600km extent of the St. Lawrence River require different types of technologies. A major challenge, however, is predicting future conditions from the observed data that can be used in the loading of ships in foreign ports that will not enter the St. Lawrence River until many weeks later. As with weather forecasting, the accuracy of predicting river conditions from earlier observations falls off after 4-5 days.

ABSTRACT. Improving shipping operational efficiency is a way toward maritime transport decarbonization. This requires a thorough planning and scheduling of ship and port operations, which can be supported by advanced analytics tools. This paper proposes a methodology for monitoring the vessel arrival process from a bulk port perspective using deep learning sequence models and Statistical Process Control. The proposed solution uses the predictive model to get a vessel's sequence of arrival times and applies statistical control charts to monitor their variability. This approach can be used to provide insights into the vessel arrival process and enable the adoption of some operational measures for reducing ship emissions such as the virtual arrival policy.

ABSTRACT. As assets being part of the social fixed capital, ports can be considered as a public good that companies combine with other private inputs to provide goods for final consumers, thus contributing to the welfare of the communities that use those ports. As a consequence, port authorities’ strategies usually include the governance of port assets with the intention of maximising their positive effects on terminal operators and final consumers. From this perspective, this paper analyses the impacts on social welfare deriving from the vertical integration processes emerged in the last twenty years in the liner shipping sector, and that seem to be intensifying in this post-pandemic period, affecting not only terminal activities, but also other port services as well as land-based logistics services. By using a game-theoretical framework, the present analysis shows how the presence of vertically integrated terminals could pave the way for progressive integration, especially if port authorities aim at maximising the social welfare generated by the port system. In term of industry implications, this research findings imply that port expansions by means of integrated terminals might occur in waves, particularly in the nowadays liner shipping sector mainly characterized by few oligopolistic players vertically integrated with terminal operators.

ABSTRACT. This paper proposes an original contribution to measure impact of a new high-speed rail line on tourist attractiveness, based on the Sud Europe Atlantique (SEA) rail line example. The originality of this research lies in tourist attractiveness measured by accessibility indicators and the correlation between accessibility variation and touristic facilities development analyzed by a principal component analysis. By “attractiveness” we refer to accessibility variation by rail mode. The tourism facilities are appreciated by tourist accommodations and two approaches are considered. The first refers to occasional customers in a recreational travel and includes “holiday accommodations”. The second approach focuses on second homes, used by their owners on a regular and continuous time for week-ends, holidays or other stays. The tourist attractiveness is thus measured by a correlation between accessibility indicators and tourist accommodations variations. A lack of correlation is observed between the positive accessibility variation and the number of holiday accommodations for touristic areas based on outdoor and recreational tourism. An exception is observed for urban and business tourism. Tourism facilities are clearly correlated with travel gains generated by the high-speed line. The development of second homes is correlated with observed travel time gains.

ABSTRACT. There are more than 100,000 kilometres of planned and operative High-Speed Rail (HSR) lines in the world. The largest network is in China, followed by Spain, Japan and France. The HSR network in Italy includes less than 1000 kilometres in operation and about 120 km under construction. The paper focuses on the HSR travel demand, with an emphasis on the development of models simulating the run service choice among existing alternatives by users travelling between a given origin-destination pair. The research contribution concerns a framework for the identification of users, as well as the development of choice model in the above-mentioned dimension. The framework is composed by two phases. The first concerns the construction of the choice set of alternatives, analysing the time series of the rail services tickets, and with the identification of user’s choices. The second deals with the specification, calibration and validation of a run choice model. The proposed framework has been experimented on the relationship Rome-Milan (Italy), through the calibration of a run choice model belonging to Random Utility Models (RUMs). The work aims to support transport planners and decision-makers in the evaluation of future investment in HSR lines and services with methodological and modelling tools.

ABSTRACT. Based on the high-speed Railway data from 2003 to 2019 and the panel data of three urban agglomerations, this paper empirically analyzes the impact of high-speed railway operation on the development scale and agglomeration situation of regional logistics industry by using the multi-time-point Difference-in-Differences model. The results show that: first, the opening of high-speed railway has significantly promoted the development scale of logistics industry in the three urban agglomerations, but has a certain inhibitory effect on the agglomeration of logistics industry; Second, through the comparative analysis of the three urban agglomerations, it is found that the opening and operation of high-speed rail has a significant positive impact on the development scale of the logistics industry in the Beijing-Tianjin-Hebei and Pearl River Delta urban agglomerations, but has no significant impact on the industrial agglomeration. The opposite is true for the Yangtze River Delta. Third, the opening of high-speed railway can promote the development scale and industrial agglomeration level of urban logistics industry with high administrative level, and restrain the urban logistics industry with low administrative level. The results of this study have some implications for strengthening the deep integration of high-speed railway and local logistics industry.

ABSTRACT. The purpose of this study is to assess accessibility and its spatial equity of the Chinese high-speed rail (HSR) network. The potential accessibility measurement was used to calculate accessibilities of prefecture-level cities with HSR stations in 2015, 2018, and 2021. Defined spatial equity as the disparity of accessibility distribution, Theil index is applied to analyze spatial equity and its changes, then decomposed Theil index into within-group and between-group disparity based on geographical location and cities’ administrative level. Results show HSR accessibility presents a distribution pattern of high in the southeast and low in the northwest, the spatial equity of HSR accessibility was improved from 2015 to 2021. When grouped by geographical location, the Eastern region has the best spatial equity, while the worst spatial equity region has changed from the Western region to the Northeast region; the total disparity is mainly composed of the within-group difference of the Eastern, Central, and Western regions. When grouped by city’s administrative level, provincial capitals have worse spatial equity in 2015, but have better spatial equity in 2018 and 2021, the difference between provincial capitals and other cities gradually decreases, the contribution ratio of between-group difference is larger than that based on geographical locations.

ABSTRACT. This paper investigates the saved travel time (STT) of two short haul city-cluster high-speed rails (C-HSR) in China, in the competition with road transport and long distance high-speed rail (HSR) trunk lines. We analyze its correlation with passengers’ travel distance distribution based on the actual passenger flow. The results suggest that C-HSR has competitive advantage for haul distances between 31 km and 160 km. It depends on both the station to station distance and the out of vehicle time, whereas the latter has greater influence on shorter corridors. The reasonable ratio of the out of vehicle time to the in vehicle time is between 0.4 and 1.4. The distribution of C-HSR passengers’ travel distance is in line with STT. The distances of most C-HSR trips are within the range of C-HSR’s competitive advantage. We use the questionnaire approach to support our theoretical analysis as well. The empirical evidence is consistent with the analysis of the theoretical model. The policy implications of the conclusions are operation schemes of C-HSR and even long distance HSR lines and the suggestion for C-HSR stations’ site selection.

ABSTRACT. Recent disruptions have revealed the vulnerability of complex global supply chains (SCs) to exogenous risk events, highlighting the importance of resilient SCs notably after the widespread impact of the COVID-19 pandemic. The implementation of logistics and SC resilience strategies (SCREST) is a fundamental way to enhance the resilience of SCs. This study investigated the willingness of Japanese companies in different industrial sectors to implement SCREST, analysed the impact of the pandemic on their willingness, and identified the factors influencing their willingness. Primary data were collected through a questionnaire survey from 549 Japanese manufacturing companies nationwide from March to April 2022. The results showed that the willingness of companies to implement SCREST during/after the pandemic was 7% higher than that before the pandemic. Logit models estimated with the collected data revealed that factors such as the logistics strategy of the company and obstacles to the implementation of SCREST influenced the willingness to implement SCREST both before and during/after the pandemic.

ABSTRACT. Purpose – This paper analyzes the adoption of current technologies in logistics services based on a case-study of an automation solution for logistics relationship management. Design/methodology/approach – This study is based on a stepwise qualitative research design. First, a three-part desk research is undertaken. The first part identifies the contemporary trends in logistics services by carrying out an extensive literature review. The second part maps out the current expectations regarding technology implementation potential and to gain insights in best-practices regarding contemporary management tools and practices that leverage technology trends. The third stage debuts with retrieving the current practices regarding the LSP-client relations and the SLA/KPIs used. The later third stage of this study is extended over 4 case-studies to determine boundary conditions for value innovation in logistics relationship management through technology-enabled contractual governance and value co-creation. Findings – This study indicates that while LSPs recognize the potential of technology trends like AI, blockchain, or synchromodality, the current implementation practices are still only focused on data integration and early-stage digitalization. Originality/value – This study clarifies the fundamental functionalities and customer-added value of a tool that leverages technology to manage the contractual relations in logistics.

ABSTRACT. Supply chain management includes strategic, tactical, and operational decisions for long, medium, and short-term planning. Strategic decisions such as network design and operational decisions such as last-mile routing have mutual implications. Modelling these decisions separately can lead to sub-optimal solutions. Model these decisions simultaneously has been addressed as a Location Routing Problem. This paper aims to do a critical literature review to identify the methods used to solve the LRP, as well as challenges and research opportunities. Following a semi-systematic literature review approach, the results show that the solution strategies are with single-stage, two-stage, and even three-stage models. On the other hand, the solution methods focus on exact methods, heuristics, and metaheuristics. The challenge of modelling different decisions simultaneously, with the appropriate method, is complemented by the need to include new variables and urban logistics trends. Three research opportunities are proposed from the literature review. Continuous approximations to address the last-mile distributions when making strategic network decisions could have methodological and practical advantages. Environmental and social objectives should be included in addition to the economic ones. The proposed methods and algorithms should be applied in real cases as a reference for future replications.

ABSTRACT. The cross-country ones are subject to more diverse and unconventional disruption risks due to the unstable geopolitical conditions, terrorist attacks, and complex landscape and extreme weather events, thus calling for resilience-related investments from different countries. However, such resilience investment made by one country to deal with such unconventional disruption risk is very hard to be verified by other countries (i.e., non-verifiability). This paper establishes an integrated economic model to analytically examine countries’ joint resilience investments on the cross-country transport infrastructure in presence of non-verifiability. Specifically, there is one “investing country” who constructed the infrastructure which is also used by a “host country”. Our analytical results suggest that the first-best investment and market outcomes for the global welfare maximization can be achieved if the resilience investment is verifiable. The non-verifiability is, however, found to cause a downward distortion in the resilience investment and an upward distortion in transport price when the probability of the disruption is higher such that the resilience investment only partially covers the potential loss. On the contrary, when the probability of disruption is low so that the resilience investment can lead to the full loss coverage, the first-best outcomes can still be achieved without any distortion.

ABSTRACT. The construction of China’s extensive high-speed rail (HSR) network is driven by various motives of different participants. This study employs a spatial econometric model to examine the motivation of local officials behind the construction of HSR stations. We employ a comprehensive dataset consisting of information about HSR station construction, the promotion of officials, and the economic growth rate in 246 prefecture-level cities in China. The findings suggest that local officials are not making their decisions regarding HSR stations solely on conditions in their own cities. The construction of HSR stations is largely affected by the peer effect arising from geographic adjacency, economic adjacency and administrative adjacency. This is mainly because China’s local officials are engaged in the Promotion Tournament based on Yardstick Competition. Political promotion strengthens the peer effect. Further examination shows that external learning and fiscal competition have triggered the peer effect. In addition, the fact that no directional learning between developed and underdeveloped cities reveals the severity of the peer effect in the construction of HSR stations. This paper has also offered several policy implications based on empirical analysis.

ABSTRACT. This paper analyses the potential for battery-electric vehicles (BEVs) in the heavy-duty truck (HDT) market, based on an empirical case of the pre- and post-haulage (PPH) of containers to/from an intermodal terminal in Sweden. Data analysis from an entire fleet of 21 trucks serving the terminal over a full year reveals that there is a large potential for BEVs already, given the current generation of BEVs with battery capacity around 400-500 kWh. Results show that it should be possible to switch at least 50% of the fleet immediately, rising to 75% in a couple of years as battery capacity increases and more fast chargers are available. The case shows that the PPH intermodal market is ideal for early adoption of BEVs, with a lower gross train weight (GTW), short-medium distances per trip and several round trips to and from a central location where the fast chargers are located. Moreover, as 40% of HDT transport in Europe is made up of trips of under 300 km, it is not only the PPH market but a significant portion of regional HDT routes that could switch, providing the opportunity to save millions of tonnes of carbon emissions per year in the short term.

ABSTRACT. The forest transportation sector is a significant source of GHG Emissions. Industrial professionals aim to shift towards more environment-friendly practices to help reduce the impact of it. Electrification is relatively new to forest transportation as fewer studies describe its influence. Due to the lack of presence of such vehicles on-road, this study investigates various opportunities and barriers to the adoption of electric trucks in forestry to achieve the emission reduction goals of Canada. It also looks at the recent developments in heavy-duty electric trucks to identify emerging technology areas. By analyzing research papers and patents, this paper reviews relevant studies in battery electric trucks in 3 phases, namely strategic, tactical and operational planning respectively. It also highlights the different industrial applications in forestry where electrification brought about a watershed. The forest transportation sector has the potential to become carbon-negative by investing in electric trucks, but achieving net-zero emissions might not be realistic without changes in policies and incentives.

ABSTRACT. This paper developed a methodological process to estimate traffic attractiveness perspectives of alternative intermodal freight routes combining Rail and Short Sea Shipping services avoiding circumnavigation of peninsulas. The proposed approach was applied to the railway connection linking the Greek seaport of Alexandroupolis with the Bulgarian ports of Burgas and Varna to constitute an alternative land bridge connecting the Mediterranean with the Black Sea. A comparative analysis allowed a preliminary estimation of the unit cost and travel time for container transport was carried out for the two alternatives, i.e. the “Cost of a Maritime Route crossing the Straits” and the “Cost of Intermodal Sea-Rail Route using the Corridor”, for two indicative routes (OD pairs) and two different scenarios regarding additional transhipment. The paper further enlarges the scope of traffic attractiveness combining operational decision-making approaches with strategic and policy considerations.

ABSTRACT. The decarbonization of the US transportation sector presents a considerable challenge for the freight railroads, whose operations are energy intensive and networks span tens of thousands of track-miles. We present a sequential framework to address the network deployment and sizing of the refueling infrastructure required by alternative fuel propulsion technologies. This paper presents two optimization problems to locate and size (i.e., specify the capacity of) alternative fuel refueling/charging facilities on existing rail networks. To illustrate the framework we consider the deployment of battery-electric locomotives and charging facilities on an aggregate network of three Class I railroads. Relative to current diesel emissions estimates, the scenario considered offers a 31% emissions reduction under the current electric grid scenario and an 80% decrease in emissions in a renewable electric grid case. Our framework runs extremely efficiently and provides interpretable results at every step of the process. This framework also offers significant modeling flexibility as components can be altered to address different deployment objectives or operational considerations.

ABSTRACT. This study explores the impact of remote work on business productivity at a transportation service provider and identifies relevant variables to consider for workplace and workforce configuration. The goal of the study is to understand: How does a remote workforce impact business productivity? This is investigated through construction of an in-depth case study of a transportation service provider. The work assesses data from overall customer satisfaction scores as well as departmental level data from accounting, claims, operations, and customer experience departments. The results indicate remote work affects different departments differently. This research reveals that in departments where the work is transactionally focused and does not require immediate response, a remote workforce might not affect productivity. However, in departments such as operations, claims and customer experience, where completing the work depends on timely interactions with customers, suppliers and co-workers, the results show increases and decreases in demand and productivity that do not follow a clear pattern. The work then uses environmental comfort theory to identify relevant variables for further consideration as TSPs set out to determine the most productive workplace and workforce configurations.

ABSTRACT. Berks County, Pennsylvania, USA is emerging as a regional center for ecommerce warehousing development due to the county’s proximity and accessibility to population centers and low-cost available land. The county’s growth trails that of its neighboring counties that have already seen explosive warehousing growth. These developments bring job opportunities and tax revenue, but also have brought challenges to the communities where they are located. This first phase of our project seeks to understand the impacts of these developments through comprehensive analysis of news reports from the local newspaper in Berks County, the Reading Eagle. Published articles were examined to determine the main community concerns related to warehousing and to better understand the processes for warehousing project approval and development. Using three primary case studies and unique findings from individual project proposal events, we identify key stakeholders in warehousing development, the regulatory policies in place in Berks County, and expected impacts of the warehousing and distribution center development in Berks County communities.

ABSTRACT. The rise of e-commerce and proximity logistics is fueling a strong demand for logistics spaces in urban areas. The punctual development of a few urban logistics projects is not enough to absorb the demand. The challenge today is to increase the supply of land and space dedicated to urban logistics. In this paper, we examine the changes in the role of public authorities regarding urban logistics production. They are investing new urban planning tools to support this growing demand. Besides traditional urban planning tools such as planning and regulations, logistics urban design recently appears as another way to develop urban logistics within urban. The latter is still under-used due to the lack of tools to estimate the logistics needs of the project, i.e. the flow of goods generated by the inhabitants and activities of the future project, but also due to the lack of a process that would allow the sizing of an adapted logistical facility within the urban project. Our paper presents an experimental method to integrate logistics in urban design process, which we will illustrate with a case study in Paris.

ABSTRACT. The supply chains of consumer goods and production have been weakened by ever stricter environmental regulations, aimed at benefiting the transition to Net Zero in the transport sector. European cities are implementing urban traffic restrictions to limit access to city centres and are considering new schemes to make their transport and mobility systems more sustainable. Therefore, planning sustainable urban logistics has become a key element in the ecological transition of dense urban areas, to a great extent driven by the emergence of e-commerce. Consequently, France has set up “urban logistics hotels”, generally located between the borders of cities and residential districts, as a new hybrid concept that integrates urban logistics with more efficient installations and a mixed use of space. This scheme is completed by new concepts of urban logistics areas, better adapted to local needs, better integrated in the urban landscape, and closer to consumers. The aim of this article is to shed light on the state of progress of the implementation of this new concept of urban integration in France, establish synergetic relations with other emerging concepts, such as mobile and ephemeral micro-hubs, dark stores, micro urban logistics hotels, etc., and consider new opportunities in this sector.

ABSTRACT. Firms located in urban areas struggle with constraints on space, congestion, safety, pollution, and varying stakeholder demands. These constraints place pressure on logistics activities. For cities, events are a great revenue generator, create peaks in tourism and boost the local economy. Events are complex with similar characteristics to temporary projects such as construction. The complexity is driven by short turn-around times, varying goods requirements and unforeseen occurrences needing flexibility. Coupled with the complexity, event venues must also consider efficiency, sustainability, and client satisfaction for the overall success of the event. Hence it is critical to examine how solutions such as consolidation centres, can be applied to event venues to improve sustainability. To examine the impact of a consolidation centre on an event venue a combination of two frameworks have been used, the Actor-Resource-Activity (ARA) and Materials-Flow-Mapping (MFM). The ARA framework looks at a firm as a network of interconnected parts while MFM examines a specific process to evaluate the efficiency of each step. The application of the frameworks on the case study firm, Svenska Mässan, evaluates the potential of integrating a consolidation centre. The study demonstrates the successful application of the frameworks to identify opportunities for greater efficiency and sustainability

ABSTRACT. Urban consolidation centers (UCCs) have become an integral part of the city logistics system. This study aims to identify factors affecting public support for the implementation of UCC in Hanoi City, Vietnam. In other words, the authors evaluate whether UCC is believed to be a constitutive element of sustainable development of the city logistics system of Hanoi. To accomplish such objectives, the study employed a data sample from an extensive empirical survey of 142 representatives from freight transport companies and logistics services providers, traffic management authorities, and research institutions in the field of transportation and logistics. The key findings showed that positive expected effects on transport organization and operation of urban supply chain significantly increased public support towards the development of UCC in Hanoi, whereas the effect of UCC on urban road safety seemed to be of no concern. Another noteworthy finding is that barriers to UCC implementation seemingly hold little to no influence over public support for UCCs development. The study is expected to be the first step to a decision support system for city logistics measures focusing on the UCC initiative in Vietnam.

ABSTRACT. Building (urban) logistic networks is complex. It also includes the question of network design: Using a direct (one-tier) transport system from the depot to the customer. Or is it better to implement a two-echelon distribution system, transporting the goods with large vehicles to a transshipment hub near to the customer and smaller vehicles for the last-mile distribution. These decisions must be made by the Logistic Service Provider (LSP). In this study, we investigate the behavior of an LSP in an agent-based simulation framework with different plans: direct delivery, and delivery via a hub. Depending on different input values, e.g. fixed and variable costs of the vehicle, or costs for the hub, the LSP performs its planning and selects the plan with the best score. Tour planing at different stages of the LSP’s transport chains is done by solving a Vehicle Routing Problem (VRP). As a result, we have shown, that the LSP selects the best plan in an artificial grid scenario and in different simulation settings, with different number of jobs, cost settings, and a vehicle-type specific cordon toll. In the next steps, we will apply it to existing case studies in large cities, such as Berlin, Germany.

ABSTRACT. With the rapid growth of the on-demand logistics industry, large-scale pickup and delivery with late penalties problem has become widespread in various time-critical scenarios. This problem has proven to be an NP-hard problem. Hence, the computation time and resources required to solve it increase exponentially with the growth of size. As a result, it is burdensome for the exact algorithm and heuristic method to generate a high-quality solution instantly. Machine learning seems to be a possible option due to the advantage of offline training. However, it is difficult to solve large-scale problems due to the lengthy training time, heavy computational cost, and training instability. Thus, this paper proposes the two-stage learning-based method composed of the clustering stage and the routing stage to tackle this problem. The clustering stage builds upon the attention mechanism by introducing a graph embedding layer on the input, which captures relationships among customers and classifies them into different vehicles, while the routing stage adopts a well-trained model to generate a route for each vehicle. Experiments show that the model, trained on small-scale problems, generalizes well to larger-scale problems, and achieves superior performance compared with Google OR-Tools, with an extremely short computing time.

ABSTRACT. With the consideration of energy storage tender cars in freight rail, an economic order quantity framework is proposed to optimize the payload, and therefore the number of energy storage tender cars with respect to the trip characteristics and technology parameters. The varying costs of locomotive, battery, charging, and delay, as a trade-off between payload and energy storage tender cars, are estimated based on industry and official data sources in the United States. Three linehaul examples and a network-wide analysis of the American Class I freight rail network demonstrate its practical use and the benefits of coupling multiple battery tender cars. The framework enables the industry to prepare and plan technology rollouts and investment decisions, as well as formulate the best-case scenario for comparing with other energy technologies, to support decision-making in rail decarbonization.

ABSTRACT. This article addresses a street sweeping problem that extends the class of multi-depot arc routing problem by integrating a flexible assignment of end depot for each working shift. A unique team of specialized vehicles starts each shift from a depot, visits the required arcs and returns at the end of each shift to a depot. The service in the next shift should start from the end depot of the previous one. An additional new constraint imposes that the highway arcs must be serviced during a night shift while all others arcs (boulevard, street, etc.) can be swept during both day and night. The aim of this arc routing problem is to find optimal shifts that satisfy these two practical aspects, along with other constraints such as maximum shift duration. The problem is motivated by a real-world application that has not been previously studied in the literature. A mixed integer linear programming model is formulated with the objective of minimizing the total travel time and tested on newly generated instances based on Cordeau’s multi-depot vehicle routing problem instances. The results show a generation of total travel time savings up to 12 % compared to the single depot arc routing problem.

ABSTRACT. New business models are currently being developed in the context of truck freight transport, which influence sustainability and play a key role in reducing traffic and emissions. However, there are few studies related to the influence of shared freight transport driven by Industry 4.0. One of the problems of freight transport by truck is that a large percentage return empty to their starting point after deliveries, which means significant economic losses and environmental pollution. Many organizations need to transport their goods but lack the right truck for their needs at the right time and at a reasonable price. This leads to the search for a better freight service based on sustainable logistics to optimize operations. This research explores the case of a start-up based in Canada, whose goal is to provide a simultaneous service by acting as an intermediary between different parties (Carriers and Shippers) in the quest for more sustainable and efficient transport through the deployment of a smart platform. The platform aims to optimize the process of the two parties. This study applies a multi-strategy tools approach to analyze the business model and address the long-term sustainability and impacts of technology enablers on these new enterprises.

ABSTRACT. Careful management of traffic signal phases can significantly reduce congestion and fuel consumption. It enables increased mobility and is already used in many public transport services, making small modifications to the phases of a cycle to modify traffic lights and facilitate the flow of certain vehicles. In this research, we collaborated with the technology information managers of the City of Trois-Rivières (Québec, Canada), a heavy-load carrier, and a technology provider to implement a freight signal priority management system for heavy-duty vehicles. We built a large-scale detailed simulation of the city center where an industrial partner operates and introduced signal priority strategies to improve operations and mobility of their heavy-duty vehicles. The idea is that when these vehicles stop at red lights, they incur high consumption to regain speed and cause congestion in the traffic behind them due to their lower acceleration. Detailed computational experiments demonstrate that this strategy generates significant gains for the partner fleet and, if properly managed, has no negative side effects for the surrounding traffic.

ABSTRACT. The Macroscopic Fundamental Diagram (MFD) represents an increasingly established model for assessing the quality of traffic flow in networks. However, the uniqueness of an empirically estimated MFD cannot be guaranteed due to the problem of detector selection. Instationarity and varying flow patterns make it difficult to select the link flows that are representative of the traffic state in the whole network. This paper developed a new method for selecting loop detectors that represent a particular traffic state of a road network. The method relies on a metric of heterogeneity characterizing the role of a network link over the time of a day. The dispersion indicates the heterogeneity in traffic conditions and the dynamic role of each time interval. The heterogeneity-weighted saturation level of links is used to determine a ranking of links. The high-ranked links in the ranking represent the most homogenous sample of subset links. The study used the loop detector data of Zurich and London and a simulated network to compare both equal (classical) and dynamic weights (proposed) by selecting the sample links based on different saturation levels. Moreover, associating the saturation level with the heterogeneity level specified the links creating the heterogeneity in the road network primarily.

ABSTRACT. In this paper we look at the forecasting of traffic flow on a major highway in the Netherlands impacted by road maintenance works, examining the effects of lane closures on intensities per vehicle category. We apply several forecasting methodologies such as Prophet, Harmonic Regression, Seasonal Autoregressive (SAR), Seasonal Autoregressive Integrated Moving Average (SARIMA) and compare it against a seasonal naive baseline model. We observe that SARIMA performs better than other models across all forecasting metrics for all sensors. This is mainly because of its capabilities of capturing linear trends and seasonality. There is also an opportunity to further improve the forecast accuracy of the SARIMA model by incorporating holiday information as seen in the Prophet model. Overall, the analysis showed that the road works and holidays are two features that have more influence on traffic flow, which should be considered as main factors when carrying out future road plans. If multiple areas are affected, the K-means model can be adopted effectively to cluster the sensors into groups to minimize traffic disruption.

ABSTRACT. The through and right-turn shared lane is widely designed to increase the capacity of through traffic, but it can also cause delays for right-turn vehicles. This paper presents a dynamic control method for the shared lane that prioritizes right-turn vehicles during the beginning of the cycle, and subsequently allows through traffic to queue in the shared lane for saturated discharging. The traffic wave model is employed to reveal the dynamics of the traffic flow under this control, and to derive relationship among major traffic parameters. Constrained by the major relationship, a linear programming approach to minimize the total queue length is developed to determine the proper value of control parameters including shared area length, subordinate signal time lag, and shared or exclusive duration. Sensitivity analysis on the control parameters toward different arrival rates and through flow ratios are implemented. Comparisons are conducted among the dynamic shared lane, the fixed exclusive lane, and the fixe shared lane. Results show that the dynamic control method results in lower delay for both through and total traffic.

ABSTRACT. Although many studies based on traffic simulations have been conducted to evaluate the impact of the behavior of autonomous vehicles on general surrounding vehicles and the traffic flow in mixed situations, few empirical studies based on actual measurement data on public roads have been conducted. In this study, the characteristics of the following vehicle behavior for leading autonomous buses (ABs) at basic road sections and signalized intersections were analyzed using video data obtained from demonstration experiment in Maebashi City, Gunma Prefecture, Japan. The characteristics of the vehicle behavior on basic road sections are classified into three parts: the following, passing, and overtaking behaviors. The behaviors of ABs were compared with those of non-autonomous buses. For the following behavior, by developing a car-following model for leading ABs comparing the estimated parameters of the model with those driven by a human, the influence of ABs on the subsequent traffic flow is evaluated quantitatively. In addition, we analyzed the behavior of general vehicles following an AB at signalized intersections and confirmed the difference in time -headway based on the turning movements at intersections.

ABSTRACT. To meet the zero-pollution target on noise by 2030, it is necessary to develop mobility management policies that directly act on noise exposure. More in general with proper designs of traffic management strategies, several objectives may be achieved, such as travel time savings and reduced impacts. Furthermore, in the context of Cooperative, Connected and Automated Mobility (CCAM) data collection concerning vehicles and traffic status estimation contributes to providing users with accurate and reliable suggestions in terms of travelling/driving information/assistance. The focus of this paper is on the implementation of a traffic control framework in the context of connected vehicles (CVs) including the minimization of externalities and in particular the combination of traffic dynamics optimization and noise pollution minimization. This study proposes a multi-objective optimization framework that aims to minimize the total time spent and noise pollution in a fully connected transportation system. In terms of numerical applications, the optimization framework was implemented on a five-node network where once the vehicles approach the control zone they are assumed to be fully connected, and information is exchanged between each vehicle and the traffic signal controller. Results highlight that in terms of optimization, the coordination method must be adopted.

ABSTRACT. Transit Signal Priority (TSP) is a control strategy that can reduce the delay of public transit by adjusting the timing and phase design of signalized intersection(s). However, upon a high traffic volume, TSP may significantly increase the delay for non-priority vehicles. Hence, it is an essential issue to adjust the TSP logic at different demand levels. V2X (Vehicle to Everything) communications have been built or tested in recent years to collect vehicles’ locations and speeds and thereby dynamically adjust signal control strategies. In a V2X environment, this research proposes a framework to implement TSP control along the segment of an LRT (Light Rail Transit) route in real time by adopting a rolling horizon approach, seeking to minimize the total weighted delays of LRT trams and vehicles. Based on V2X communications, signal states and queue lengths can be collected/estimated. Dynamic programming is further employed to compute the optimal control strategies. The test site over five consecutive intersections is constructed to verify and validate the proposed control framework. The proposed TSP control framework ensures the progression of LRT trams and significantly decreases the delay of non-priority vehicles by 70% compared to a general TSP.

ABSTRACT. In this work, the NextLocation algorithm is presented for estimating the vehicle's location each second using the last vehicle's real-time speed and location and the historical speed and location of vehicles in the surrounding area and time of the last vehicle's real-time location. The algorithm takes the real-time location and speed of the vehicle and selects the vehicles close to it (in time and distance) in the historical data set, then averages their historical instant speeds. The average speed is used for estimating the vehicle's location in the next second. The NextLocation algorithm estimates the vehicle location in milliseconds, since it only needs to perform geographical selections and basic computations, making it ideal for real-life scenarios. A study case is presented in a data set containing 6,900 locations, and discussions about the algorithm's accuracy are presented. The NextLocation can be used on a web map for live tracking vehicle locations and also could be used by transit operators for monitoring purposes. However, NextLocation does not consider the accuracy errors generated by the GPS devices installed in the vehicles and does not consider reroutes of breakdowns which might limit the usability for transit operators

ABSTRACT. The risk induced by extreme traffic loads on bridges was rarely investigated and the existing methods require computationally expensive elaborations that are not compatible with a real time risk management. Traditional approaches to reduce risk suggested the optimisation of bridge maintenance plans. Conversely, approaches that real-time evaluate and manage the risk are missing. Moreover, the integration of emerging prediction models, such as Artificial Neural Networks, was never explored. This study fills the previous gaps by proposing a three-block methodology. It adopts Weight-In-Motion systems to collect site-traffic load data, formulates a probabilistic Risk Prediction Model to estimate frequency and severity of bridge failure events according to Eurocodes, and simulates an Intelligent Transportation System (ITS) architecture to apply real time management actions. The methodology was tested on 2.5M+ vehicles raw WIM data gathered along the ring road of Brescia (Italy). Bridge failure events resulted significantly more frequent than that prescribed by Eurocode, and factors of compliance with Traffic Code mass limits prescriptions had the more significant effect on risk predictions. The findings suggest a greater attention when permits for extremely overweighed vehicles are issued, as well as the implementation of enforcement strategies and ITS-based architectures for the real time risk management.

ABSTRACT. The reliability of public transport is a significant reason whether people choose it over other transport modes. Roadworks, i.e., mandatory road maintenance, can cause delays on vehicle journeys in parts of the network, thus generating missed transport connections. To sustain the reliability of the public transport system, it is important to understand effects these delays cause. This study explains a method that allows to model delay effects to the network using GTFS-data. The developed method allows a simple workflow to calculate how different delays on different locations affect the reachability of the areas. The method is tested in two case areas in Finland. Based on the case areas in this study, the results indicate that a 3-minute delay occurring for the departures from city centre only seldomly appears as a total travel time delay longer than the calculated delay. However, for some parts of the city that rely on transfer connections, even a 2-minute delay will result in missed connections, and thus, longer travel times.

ABSTRACT. A review of the existing research has proven that effective intervention in the developed world may not be equally successful in the LMICs, especially when the social, cultural, and economic conditions are different. As a result, realistic and relevant changes are required for LMICs to use countermeasures that worked in the developed world. Therefore, documentation of systematic reviews of the evidence for LMICs is vital for identifying and quantifying the effects of interventions. In the present study, an attempt was made to document the effectiveness of flexible poles on horizontal curves with restricted sight distance. In this regard, a quasi-experimental design with control groups was adopted with 12 high crash locations on the two-lane undivided highway in eastern India. The systematic safety planning highlighted instances of a high share of head-on crashes and overtaking at high speed on the curves. The insights from the safety study suggested the installation of flexible poles along the centreline of the curve. The observations suggested that although flexible poles can be used to segregate traffic from opposing directions and restrict overtaking at sites without adequate sight distance but for traffic with a high share of two-wheelers, they may not be as effective.

ABSTRACT. This study aims to enrich the knowledge of modeling the speeding likelihood at road level with an innovative attribute named percent of speeding observations (PSO). The GPS trajectories collected by the taxis in the city of Chengdu, China are adopted to extract the speeding behaviors and obtain the PSO. The road design and traffic control factors of the speeding likelihood are related to the PSO through beta models. Spatial correlation and heterogeneity are additionally accounted for to relax the model over-dispersion. As a result, five Bayesian beta models are proposed, inducing Beta model, Beta Logit-Normal model, Beta intrinsic conditional autoregressive (ICAR) model, Beta Besag-York-Mollié (BYM) model, and Beta BYM2 model. Analysis results show that the Beta BYM2 model performs better than other models in terms of data-fitting. According to the model estimates, spatial correlation is the main reason for the model variability, which can be properly handled by introducing the structured component in the modeling. The roads with more lanes and roads linked by elevated roads are found to increase the speeding likelihood, while higher speed limits, intensive intersections, traffic congestion, and roadside parking are associated with lower speeding likelihood.

ABSTRACT. The present study attempts to investigate the influence of applied time pressure on the development of drivers’ stresses and the changes in driving behavior on highway and urban sections by utilizing physiological data collected from wrist-worn wearables and vehicle trajectory data collected from GPS data logger equipped in an ego vehicle. A Gaussian mix model-based clustering approach specifies three distinct stress levels developed while driving under both time pressure and without time pressure conditions. Results of this study indicate that driving stress increases under the influence of time pressure conditions and the increase is more in urban sections than on the highway. The study reveals that the observed speed may be the result of the developed stress under no-time pressure; however, under time pressure condition, speed might become the reason behind generated stress along with surrounding traffic characteristics. Additionally, the driver moved in a higher speed under no time pressure than time pressure conditions as the driver’s stress level reduces from high to low level. The inferences from the study therefore direct towards the implementation of a suitable strategy for improving safety, system design and automated monitoring of driving performance for providing an overall safe environment to the drivers.

ABSTRACT. Traffic emissions are one of the main sources of air pollution and the major source of atmospheric pollution, causing significant risks to human health. Therefore, driving behavior may affect air pollution through several distraction activities. State-of-science models can simulate the behavior and emissions of the individual vehicles on a road network. The use of microscopic simulations enables finding acceptable reasons for traffic composition, flow congestion, and the volume of exhaust gases. We aim to explore whether driving behaviors impact environmental air pollution, traffic flow, and safety implications. This study focuses on car-following behavior in the context of distracting activities. The parameters of the GM were estimated under various distraction scenarios using data collected with an experiment conducted with a driving simulator. The estimation results show that drivers are less sensitive to their leaders while talking on the phone and especially while texting. The estimated model implemented in a microscopic traffic simulation model. The simulation results show deterioration of traffic flow with texting and talking on the phone: average speeds are lower, and COV of speeds are higher. The impact on the emissions of, fuel consumption,CO_2,〖and NO〗_X, increased when drivers are involved with distraction activities such as texting.

ABSTRACT. Traffic crashes not only result in loss of lives but also have a substantial amount of social cost associated with them. Identification of Traffic crash hotspots is of utmost importance for an effective road safety management program. This study aims to identify and prioritize traffic crash hotspots using a GIS-based framework. The study area was taken as Punjab because of its 3rd highest accident severity among all states in India. Accident hotspots were plotted, and severity-based spatial analysis was carried out using Getis Ord Gi* statistics. Two kinds of crashes were studied: All crashes and Pedestrian crashes. The spatial autocorrelation gives a z-score of 32.312, a p-value of 0.00, and Moran's Index of 0.1335. The hotspots obtained were further prioritized region-wise and in an intra-city manner based on the Crash Severity Index (CSI). According to the evaluation of hotspots by region, Sangrur, Hoshiarpur, and Fatehgarh Sahib are the top three hotspots (High clusters) in Punjab; Gurdaspur, Pathankot, and Rupnagar are significant coldspots (Low clusters). Based on the Crash Severity Index (CSI), individual crash locations (for all crashes and pedestrian crashes) were prioritized as a result of the intra-city Hotspot study.

ABSTRACT. Road safety has been a topic of research interest for many years, which has concerned city planners and governments around the world. Road safety research has been specially focused on high-income countries with big cities, and so it is important to carry out these investigations in middle-income countries, to reflect different behaviour that owes to cultural and infrastructure differences. The present document is based upon an Exploratory Data Analysis (EDA) between traffic tickets and crashes, using data collected by traffic police, between 2013 and 2021, in the city of Manizales, Colombia. Descriptive statistics and their corresponding visualizations were carried out among absolute yearly, monthly, and weekday variations in both tickets and crashes. The different types of categories in the databases included the amount of certain crash severities, their absolute and relative variations in years, months, and weekdays, the type of service that got tickets or crashed, type of vehicle that got a ticket or crashed, type of crash victim, and type of infraction for the ticket. Results show that tickets and crashes have been declining through the years, tickets peaking in February, and crashes in May, but with no clear trend.

ABSTRACT. Around the world, the analysis of highway accident data is employed to improve safety measures. In the accident data sets, the time of the accident is often the moment the accident is reported to the control center. However, this may not accurately reflect the pre- and post-accident traffic conditions. This study aims to enhance accuracy by utilizing high-resolution temporal and spatial traffic data to analyze the traffic pattern leading up to the reported accident time. By examining the traffic flow condition from upstream to downstream and considering the traffic pattern at the upstream detector of the accident, a more comprehensive understanding of accidents can be achieved. The identified accidents are then summarized based on accident rates, vehicles involved, and accident type, aligned with the corresponding traffic conditions.

ABSTRACT. Road traffic accidents are the main cause of mortality, morbidity, and disability for children globally as well as in the United Arab Emirates. Although vehicle occupants account for the majority of children involved in traffic crashes in developed countries and the UAE, injuries sustained by child vulnerable road users are usually more severe due to a lack of protection compared to child occupants. These injuries often result to long term suffering for the children and even disabilities in some cases thereby posing a severe economic and public health burden on the population. However, despite the very high severity of child VRU injuries, studies on traffic injuries in the UAE have mostly focused on vehicle occupants for both children and adults. To the best of our knowledge, there exists no dedicated study on child vulnerable road users in the UAE. Additionally, the UAE government is promoting active transportation among children in a bid to curb childhood obesity in the country. Hence, this study was undertaken to examine the factors contributing to traffic injury severity for child VRUs in the UAE. This will help in enhancing the safety outcomes of child VRU traffic injuries among children in the country.

ABSTRACT. The focus of transportation planning is primarily on adult needs and abilities, neglecting children. Children's daily travel destinations differ from those of adults. Children's walking speeds and abilities limit their travel distances. Furthermore, fear of traffic danger can also prevent children from travelling independently. At intersections, children can change directions, however, they may also experience conflict with other road users, limiting their travel options. The objective of this study is to understand to what extent children’s independent travel accessibility could be limited by the level of traffic danger at intersections.

Using open data, the methodology for this study has two key steps. First, “dangerous” intersections for children (8 to 12) were identified in a specific area of the city of Montreal based on three major traffic danger components, available in the dataset: speed limit, road class and design and traffic control. The second step involved the calculation of children’s accessibility on foot ( the number of destinations within a specific distance) with and without dangerous intersections considered as barriers. We find that children's accessibility differs when traffic danger is taken into account, which could deter children and their parents from walking to their destination.

ABSTRACT. SARS-CoV-2 was a pandemic that affects traffic flow and its safety. To understand the long-term percussive effects on road traffic crash, this study tried to compare the situation before and after SARS-CoV-2 pandemic in Budapest city. It considered data from May/20/2018-December/31/2021that accounts around 12208 road traffic crashes. To analysis the frequency and severity of road traffic crash the study used percentage frequency distribution and severity index. The study indicated that during the SARS-CoV-2 pandemic the road traffic crash was reduced by 20.15%. In both cases rare end collision was probable cause of road traffic crash that resulted during daytime. Crashes were highly factored by road user particularly by driver. The maximum road traffic crash was registered between 15:01-18:00. Even if the amount of road traffic crash happen due to alcohol consumption was small (<6%) of total road crash; the rate of alcohol consumption during SARS-CoV-2 pandemic was slightly increases. During SARS-CoV-2 pandemic the rate of road traffic crash was reduced with high-speed traffic maneuver in Budapest city. Improper use of road traffic sign, road pavement condition, lack of respecting proper sight distance were main causes of road traffic crash. Meanwhile, the distributional impact of careless driving increases after SARS-CoV-2 pandemic.

ABSTRACT. This paper focuses on how working from home was affected by the COVID-19 pandemic in 2020 and 2021. The literature asserts that the pandemic increased working from home and reduced commuting trips. This evidence is based on different types of surveys, where the focus is on changes in commuting trips and mode choice. This paper takes another approach by using Norwegian registry data at the individual level. The analysis demonstrates that the extent of job changes reduced during the pandemic and that the likelihood of changing workplaces was reduced in areas with a high number of COVID-19 cases. Hence, the effect is the opposite of the findings in the literature. The decline is the largest in the service industries, where the possibility of working from home is good, and lowest for industries that produce physical products. The effects in very place-based industries, such as primary industries, manufacturing, and construction, show a small and positive impact. Hence, any increase in homeworkers is, in contrast to surveys, not visible when considering registry data.

ABSTRACT. Based on Bike-sharing system (BSS) data for Toulouse, Lyon, and Montreal, we study the Covid-19 impact on relevant variables of BSS use. Our results show significant changes related to longer travel distance, which would be explained by those users who use the BSS at peak hour. Also, after Covid-19 outbreak, there is evidence about higher willingness to use the BSS in adverse weather conditions (such as rain and wind), lower substitution with the public transport system in Lyon, and a recovery and even a slight increase of BSS trips for Toulouse and Lyon respectively. In our opinion, these results have the potential to represent permanent changes in user’ habits, being an excellent opportunity to make specific investments in this system and thus strongly promote the bicycle use and its permanence

ABSTRACT. On March 16, 2020, all transport and economic activities in Metro Manila came to a halt as the Enhanced Community Quarantine (ECQ) order was issued for the entire Luzon island of the Philippines to mitigate the spread of the COVID-19 virus. The Bayanihan to Recover as One Act or Bayanihan 2 is an economic stimulus and recovery law authorized by Congress on September 11, 2020 mandated active transport and allocated 1.3 billion Pesos for the installation of a bike lane network in Metro Manila, Cebu, and Davao. In July 2021, the government announced that Metro Manila has more than 313 kilometers of bicycle lanes, complete with concrete delineators, flexible rubber bollards, and other safety features meant to encourage biking. This paper explores the development of appropriate bike-to-work models for Metro Manila using secondary data analysis. Two available bicycle survey data conducted during the COVID-19 pandemic were utilized. The results of model estimation using structural equations modeling approach indicate that a latent construct pertaining to the idealness of a bike route is a significant factor in explaining bike-to-work decisions. There is a need to explore the conduct of fit-for-purpose surveys and appropriate choice modeling in promoting bicycle commuting in the country.

ABSTRACT. Recent research has reported travel behaviour changes during the COVID-19 pandemic. Speculatively, these short-term disruptions in travel may lead to new habit formation and longer-term travel behaviour changes for young adults belonging to generations Y and Z. Focusing on post-secondary students within Greater Toronto and Hamilton Area, Canada and using longitudinal data collected in fall 2019 and spring 2022, we examined the post-COVID 19 travel behaviour changes and explored whether these changes are associated with their socio-demographic characteristics and life events experienced over the course of pandemic. A significant proportion of public transit and active modes users switched to cars for commuting post-pandemic. Some socio-demographic characteristics such as age, living situation, work hours and access to cars were significantly associated with these mode changes. An increased use of active modes (walking and cycling) was mainly observed in downtown areas while car use was more apparent in suburban areas. Students who joined workforce after completion of education between 2019 and 2022 shifted their commute mode from public transit to cars significantly, implying some influence of this life event on commute mode changes, in addition to pandemic-induced changes. Future transportation planning and policy implications, and directions for future research have been discussed.

ABSTRACT. The outbreak of the pandemic in 2020 has caused an unforeseen situation that significantly changed individuals’ travel patterns around the globe. The transmission prevention measures that were put in place have had both short- and long-term effects on people’s activity systems and their daily travel patterns. In order to investigate the pandemic’s effects on travel patterns and activity systems, a web-based questionnaire was developed and distributed in Montreal, Canada, in April and May of 2020. In addition to questions about activities before and during COVID-19, a section on how people anticipated travelling in the post-pandemic era was also included in the questionnaire. This research presents insights into how people are planning to travel in the post-COVID period utilizing K-means clustering and Multinomial Logit (MNL) models. the data gathered from the survey resulted into 1620 completed questionnaires, out of which 1597 were valid. This investigation offers crucial insights on anticipated changes in travel frequency, use of public transportation, and use of bicycles throughout the post-pandemic era. The findings of this study will help planners and policymakers create plans that will better prepare the cities for the post-pandemic era by taking into account the projected changes in people’s travel patterns.

ABSTRACT. Risk perception of footpath and road crossing facilities influences a pedestrian’s route choice and crossing decisions. Rasch analysis, a modern psychometric technique, can be used to understand the variations pedestrians’ risk perception. This paper presents an application of Rasch analysis to evaluate the risk perception of pedestrians with respect to the built environment features of the road used by them. Subjective built environment data was obtained from 426 pedestrians in Delhi, India. Rasch technique is used here because it could compute pedestrians’ performances with respect to the safety constructs. The results indicate that safety perception influences walking. The Wright map revealed that most of the safety related constructs are beyond the safety thresholds of even the most capable pedestrians. This suggests that the general pedestrian environment in Delhi is hostile for walking. From the analysis, it was also evident that the survey questionnaire required revision. The low person separation and reliability implied that the number of safety items were not sufficient. This paper also sheds light on how the results from Rasch analysis indicate necessary revision in survey questions and can be useful for early researchers who are about to begin their survey questionnaire design.

ABSTRACT. Development in discrete choice modelling has been dominated by Random Utility Maximization approaches due to their ease of application and high economic interpretability. However, this model assumes that decision-makers perform an in-depth information search process implicitly and instantaneously. It has not been investigated in detail whether the information search process (ISP) of transport users is in depth or breadth-first in a public transport choice context, a gap that this research aims to fill. To this end, the ISP of public transport users has been characterized in three stated preference surveys with click-tracking, which were pivoted concerning morning peak trips and varied in the number of areas of interest shown (AOI). These values were hidden and only one attribute at a time was made visible, and clicks were recorded to evaluate the respondents' ISP. Three main conclusions can be drawn from the findings. First, the pattern of searching for information in breadth-first predominates independently of the AOIs displayed. Second, more searches are performed than the amount of information displayed and this value increases at a decreasing rate with increasing AOIs. Third, the most likely transitions during the deliberation process are those that arise from breadth-first searches.

ABSTRACT. Commuters in developing countries, in particular, South Africa (SA), spend up to a third of their income on commuting trips using public transport (PT). However, it is assumed that PT in SA is unsecure and unsafe owing to crime in and around terminals, poorly maintained vehicles, and reckless driving. The purpose of this paper was to investigate the interrelations of perceived security and safety with using public transportation for commute trips and non-commute trips in large cities of Southern Africa, represented by Johannesburg. The findings revealed that insecurity when using PT, direct experience of crime while using minibus taxis, the indirect experience of crime in the PT by night and in the trains, lack of police and/guards in the public transit system, poor quality vehicles and infrastructure were the factors that significantly influence public transit ridership for commute trips. Additionally, experiencing crime in a bus, availability of transit stops, vandalism and graffiti were found to influence public transit ridership for non-commute trips. Young people perceived security and safety risks less than older people. There is evidence of captive users of public transit continuing to use PT even though they experience crime incidents.

ABSTRACT. Existing studies have found aggregate human mobility patterns on the measures of trip displacement, distance, duration, and staying time. However, little is known about commuters’ timing preferences on their trip scheduling, such as how passengers organize their departure time for expected arrival time. To fill this research gap, this paper attempts to ascertain how commuters’ travel time budget preference changes with travel cost (i.e., ride distance and ride time) in morning peak commuting trips based on the mass transit transaction records from Nanjing, Suzhou, and Chengdu. Specifically, we define two metrics, the first is unit distance travel time budget and the second is unit time travel time budget and we find simple but robust scaling laws that depicts how commuters’ preference reacts to the metrics. Additionally, we use two determinants to describe the penalties (no-penalty, late-penalty, and early-penalty), the first one is scaling law of unit distance TTB and the second is the time window for last mile time budget. Our insightful findings are useful to theoretically scale commuters’ mobility patterns in the morning peak hours, help congestion management, and transit-oriented development (TOD).

ABSTRACT. The municipality of Oslo, Norway, has set an ambitious political goal, i.e., that all traffic growth after 2019 inside the city-border should be in the form of public transport or active transport modes. To device efficient policies, a key factor is to understand how a potential change in the transport system affect transport demand. The purpose of this paper is therefor to estimate a direct demand model to be used in analyzing and planning public transport in Oslo. The estimated model will be built from the very simple to somewhat more advanced models with the explanatory variables included in the analyses chosen from theory and previous research. The paper shows that it is possible and appropriate to construct a simple, cheap (construction and maintenance) as well as significant empirical model where the demand for public transport is a function of generalized travel costs. These types of models are applicable in the early phase policymaking of urban transport systems.

ABSTRACT. The urgent need to optimize operational efficiency, boost ridership, enlarge effective communication technologies, and improve customer convenience has led to the emergence of on-demand transit (ODT) services. ODT can be advantageous in several ways, including reliability, improving mobility, cost-effectiveness, and reducing the need for multi-transit services. This paper analyzed the trip patterns of on-demand services and quantified the impacts on ridership by the Difference-in-Difference method. The pattern analyses showed that the origin-destination flow patterns are concentrated in large commercial and dense residential areas with significantly reduced travel times including the waiting times and in-vehicle times. Furthermore, the econometric analyses yielded positive relations between the ridership and the on-demand transit services for the overall transit network while the effects vary with specific landuse zones. Results indicated the potential of on-demand transit services to benefit passengers and improve ridership.

ABSTRACT. Route search data, which are typically saved in public transportation route search systems, record the potential travel plans of searchers. Such route search data are expected to serve as a reliable source of information to predict travel demand. However, although route search data merely represent latent demand, their relationship with the actual traffic demand is not known. The purpose of this study was to identify the relationship between the number of route searches and the number of actual public transportation users to predict traffic demand using route search data. For this, both route search data and transportation IC card data were analyzed for the Kotoden lines that operate in the Kagawa Prefecture, Japan. By adopting an approach that combined bivariate state-space and weighted regression models, we extracted the varying hidden relationships between the two seemingly unrelated data types and modeled the behaviorally related parts. The results revealed a positive correlation between sudden surges in the number of route searches and transportation IC card use.

ABSTRACT. The study focuses on two previously neglected customer groups for MaaS offerings: families and active elderly and analyses how their mobility practices as well as needs and constraints fit with selected mobility services - carsharing, ridesharing and micro mobility. The results come from an qualitative study conducted in 2020 in two German case cities, Berlin and Leipzig. We identified two mobility perspectives: active maintenance of mobility, i.e., maintaining personal mobility as best as possible as people age; and family mobility, characterized by the impact of responsibilities and coordination tasks related to family members. The two mobility perspectives are described in terms of characteristic mobility practices as well as needs and constraints. Then, we analyse how the selected mobility options meet their needs. We conclude that the approach provides a lens to identify weaknesses and requirements for current and future mobility services. For both perspectives, none of the mobility options presented is something that would significantly improve their situation. Reasons lie in the lack of focus of MaaS on the needs of their users, so mobility services should in future be better oriented to the needs of the large customer groups of active older people and families.

ABSTRACT. This study develops an agent-based intelligent MaaS simulation model comprised of three types of agents (i.e., MaaS fleet unit, travelers, and central intelligent mobility assignment module). The novelty of this assignment process is that it implements an intelligence module accounting for the past system performance to make a future assignment decision in favor of both sides of the operation. This study processes 24-hour trip requests extracted from Nova Scotia Travel Activity (NovaTRAC) survey data on a real-time basis. Two scenarios (1-D and 2-D assignment) are compared using the cost criteria such as total waiting time, empty time, and idle time. 1-D scenario refers to mobility assignment emphasizing demand side only and 2-D scenario formulates mobility assignment balancing demand and supply sides. Results indicate that a MaaS fleet of 350 units is the most balanced fleet in both scenarios. However, 2-D optimization reduces the overall supply cost by 25%. Moreover, 2-D operation demonstrates a higher utilization of the fleet over a large period whereas the 1-D design guarantee a higher fleet utilization only during the peak period. Results of this study provide a benchmark for assessing more complex MaaS operation scenarios which will further aid in advancing the operational MaaS ecosystem.

ABSTRACT. This study examines heterogeneity in envisioned activities in AVs using a rich survey dataset (N=3,258) collected in four regions of the southern United States from June 2019 to March 2020. We perform a latent-class cluster analysis (LCCA), which identifies a few distinctive combinations of preferred in-vehicle activities, separately for one group of respondents asked about hypothetical alone trips (N=1,932) and another group asked about hypothetical family trips (N=1,326). The alone-trip model identifies Work-oriented (26.1%), Leisure-oriented (24.4%), Vigilant (33.9%), and No-ride (15.6%) classes, and the family-trip model reveals Solitary-or-absorbed (32.2%), Interact-or-relax (29.5%), Vigilant (26.3%), and No-ride (12%) classes. Members of each latent class share unique preference profiles for in-vehicle activities, which differ from those of the other classes. With rich information available in the survey on individuals’ characteristics, AV-related attitudes, and expected use patterns of AVs, we explore implications for value of travel time saving (VOTTS), forms of AV adoption, and travel-behavior changes in an AV future. In brief, this study adds new insights to the current knowledge on travel behavior in a future with AVs, and it provides suggestions for policy and planning that would help prepare us for such a future.

ABSTRACT. Transport is major source of CO2 emissions and therefore, there are many different actions and changes in the sector to decrease the emissions. Some of these affect directly to mobility costs for users and a method is needed to both estimate the size of the change, as well as which users will be the ones affected by the change the most. In this study, a method is created using two data sources, Finnish car fleet dataset and National Travel Survey, to estimate the costs of mobility and CO2 emissions per kilometre for different transport modes and user groups. In general, 90% of Finnish mobility costs for domestic land passenger transport is due to private car transport, where the rest 10% is divided evenly between public transport on rail, public transport on road, and taxis. On average, Finnish people pay 48 cents per car kilometre and 14.75 euros per day for the use mobility between all transport modes. The model both allows the overview of current costs as well as calculation of how these will change if a set of new policies affecting the prices are presented in the system

ABSTRACT. The research reported in this paper sheds light into an important and overlooked aspect of urban freight management: the impacts of the decisions made by shippers, receivers (both commercial establishments and households), city governments, the real estate sector and other agents--referred to as non-carrier agents, or NCAs—on the generation of freight externalities. The paper is based on the insight that, since freight carriers must meet the constraints set by these agents, their decisions could force the carriers to create externalities above and beyond those that the carriers would generate if they had complete control over their operations. As part of the research, the authors: identify those NCAs’ decisions that could negatively affect the operational performance and the externalities produced by freight carriers; use standard game theory to identify the equilibrium solutions for the various interactions at the core of the key decisions that affect urban freight operations; discuss potential techniques to allocate responsibility for the generation of externalities among the NCAs involved, and use Shapley Value to allocate the responsibilities for the freight externalities in a number of numerical experiments inspired by real-life situations; and outline ways to holistically improve the overall performance of urban supply chains.

ABSTRACT. The precise impact of fare subsidies is not well understood, particularly in the Global South, where low-income populations are the biggest users of these systems. We analyze an alternative public transport subsidy scheme in a developing economy: the public transport system in Bogotá. Currently, the city provides a fare discount for low-income users of the public transport system, which has been shown to no longer effects incentivizing their use. Therefore, we propose a subsidy scheme in form of a voucher to improve the effectiveness of a policy aiming to increase public transport ridership. Using a controlled field experiment, in which a randomly selected group of frequent public transport users received during four months a public transport voucher, we estimate the causal mechanisms of providing cash transfers to travel cards in a public transport system on travel behavior and derived their welfare. Our empirical analysis yields two main results. First, the proposed subsidy scheme encourages public transport use, particularly during weekdays. Second, using a consumer surplus measure, we found evidence that the voucher is effective in inducing positive welfare effects on commuters while a fare discount is not.

ABSTRACT. This study defined the users' behaviors of autonomous vehicles (AVs) and human-driven vehicles (HVs) based on the time allocation model and proposed a small-scale microeconomic model for AV policy evaluation, which enables to calculate of the benefit in the road network under the mixed flow of AVs and HVs. The representative users of AVs and HVs are assumed to consume composite goods, leisure time, and road transportation offered by AVs or HVs. The transportation service considers the congestion effect and is determined by solving the multiclass traffic assignment model under the mixed flows. The previous studies addressing AVs assume the heterogeneous values of time (VoT) of AVs and HVs, which are given exogenously. This study does not give VoTs exogenously but considers the heterogeneity of the disposable time and income of AVs and HVs, respectively. As a result, the impact of a multitask effect in AVs on the users' utility and the benefit can be estimated. We performed a numerical test in a test network to verify the proposed model and examined the relationship between indirect utility, AV penetration rate, and AV performance.

ABSTRACT. This paper depicts the expected economic effects of new motorway projects on local business ecosystems to support decisions. Key objective is to present an evaluation methodology approach to assess the impact in three main areas: employment and staffing; new income generated; and the enlargement of the key business sectors linked with the transportation project implementation and operation. Methodologically, the depiction of economic footprint based on Input-Output modelling framework and a series of key performance indicators were introduced to assess the project performance in a given economic system in terms of regional targets and objectives coverage. The case study is an ex-ante analysis of four new motorways as part of the Greek Motorway Network, which is part of the European Motorway System improving the connectivity between south and north European Inland Transportation Corridor (TEN-T). Results provide evidence of the existence of long run cointegrating relationship among socioeconomic development, infrastructure investment, employment conditions, a strong relationship between investments in transportation infrastructures and economic enlargement for specific business sectors. Conventional wisdom is to present a coherent approach appropriate to apply to relevant projects, providing support to decision-makers, planners and managers regarding the short- and long-term effects of a transportation project on one hand.

ABSTRACT. The objective of this paper is to study the spatial distribution of economic establishments (and their freight consumption) as a function of proximity to the economic pole of metropolitan areas. To this effect, regression models for characterizing how establishment density, Freight Trip Attraction density, and Freight Trip Production density vary as they move away from the economic pole are computed. Two different methodologies are tested for the models: Ordinary Least Squares (OLS) and Quantile Regression models for six Metropolitan Statistical Areas (MSA) in the U.S. The models can be interpreted as demand functions for space. Despite the differences in size and population of the six MSAs, the resulting models show commonalities. Establishments that are oriented to provide services tend to be located closer to the economic pole. The results show how the sectors of (1) information, (2) finance and insurance, (3) professional and technical services, (4) management of companies, and (5) health care and social assistance are the industries that prefer the most to be located near the economic pole. The results also show the advantages quantile regressions have vis-à-vis OLS.

ABSTRACT. Value capture is a popular policy to recoup a portion of the additional value public transportation infrastructure investments convey to local residential property. Estimates of the value infrastructure and estimates of the value walkability convey to local residential property are scarce. Novel multiscale, local models which free independent variables to simultaneously manifest at different scales of analysis greatly improve specifications to estimate the value walkability conveys to local residential property. Results from an analysis of years of residential property transactions within walk distance of heavy rail stations imply systemic value from walkability is not available for capture. Overall, stakeholders confront myriad challenges to replicate what value is available for capture given the distinct cluster of residential property where additional value from walkability is available for capture.

ABSTRACT. This paper evaluates whether or not there a sprawling phenomenon to the spatial patterns of warehouse establishments in the four metropolitan areas (Dallas, Houston, New York and Philadelphia). The trend of warehouses to move away from the urban centers to more suburban and exurban areas is referred to “logistics sprawl”. To understand and analyze this logistics sprawl, the logistics establishments data (from the County Business Pattern survey conducted by the U.S. Census Bureau) were collected and mapped for two years (2012 and 2019). The standard deviational ellipse area from the barycenter for all warehousing establishments was calculated and compared between the years of 2012 and 2019. This shows that logistics sprawl is experienced by warehouses strongly in the Dallas and the Houston areas, quite strongly in the Philadelphia area, but not in the New York area. This paper discusses if logistics sprawl is a global trend by comparing these results to previous works on logistics sprawl. This paper contributes to the existing literature because it provides a comparative and multiscalar analysis of these four metropolitan areas and two megaregions (Texas Triangle and Northeast Corridor).

ABSTRACT. This research develops the first analytical model to support Freight Efficient Land-Use (FELU) design and planning considering the effects land-use decisions have on supply chains. To do so, an optimal facility location model with entropy maximization is developed. The model minimizes the social costs associated with supply chain activity and simultaneously finds the most likely freight tour flow assignment for the delivery tours. Two test cases based in New York City are discussed in which different industry sectors are modeled to identify the optimal locations of distribution centers. The results show how there is a tradeoff between being close to the main attractors of cargo, how expensive the location cost is, and the operational costs of distributing the cargo. In addition, a variation of the model is developed to incorporate the notion of environmental justice in the facility location problem with freight tour assignment. The results of this variation of the model protected vulnerable areas from being selected as optimum locations for distribution centers. The goal of this research is to improve land-use regional planning processes by providing a methodology that captures the interconnection between land-use location decisions and their impacts along supply chains.

ABSTRACT. E-commerce is simultaneously creating a new retail landscape through digitalization and new consumption and distribution practices (virtual access to a wide range of products, instantaneity, omnichannelity) and a new freight landscape. The company Amazon embodies all of these developments in retail and e-commerce, being a dominant player in the e-commerce sector. This research therefore focuses on the evolution of Amazon's logistics system and in particular the geography of Amazon's warehouses, marked by an expansion of the spatial coverage of the warehouses and by a functional specialization of this logistics system. This empirical spatial analysis makes it possible to identify through cartographic representations several spatial logics for the establishment and extension of Amazon's logistics system: 1) a dual spatial rationale of networking and concentration of logistics warehouses, with the development of clusters of warehouses around major transport infrastructures and the creation of a more or less fine mesh of warehouses, particularly urban logistics areas; 2) a dual spatial rationale that focuses both on the outskirts of metropolitan areas and on dense urban centers; 3) an emergence of regionalized logistics strategies.

ABSTRACT. The transport sector is responsible for about a quarter of the total CO2 emissions in Europe. The European climate law makes it mandatory for the EU to achieve the climate target of reducing emissions by at least 55% by 2030 and achieving climate neutrality by 2050. To achieve these goals, the technological innovation of vehicle propulsion systems and the extensive use of energy from renewable sources are key elements. Within this framework, passenger rail transport assumes strategic relevance. In the case of non-electrified railway lines, where highly polluting diesel trains currently operate, the use of green hydrogen for rail train traction purposes is one of the most environmentally sustainable options. This paper analyses an adaptive power flow management strategy for an urban railway train whose powertrain consists of electric motors powered by a hydrogen fuel cell stack hybridised with electrochemical batteries. As a case study, a simulation of the proposed railway train hydrogen fuelled operating on an existing non-electrified suburban line crossing the city of L'Aquila (Italy) was carried out. The main components of the vehicle powertrain are dimensioned and the hydrogen consumption is estimated.

ABSTRACT. CO2 emissions generated by international air transport correspond to approximately 2% of total global emissions. Aiming to generate sustainable growth in the sector, the International Civil Aviation Organization (ICAO) has developed a basket of technological, operational, and use of sustainable fuels measures to increase 2% annual efficiency by 2050 and carbon neutral growth from 2020. In addition to this basket of measures, ICAO developed the Carbon Offset Reduction Scheme for International Aviation (CORSIA) to allow emissions to stabilize at levels observed in 2020. Moreover, ICAO asked its Council to explore the feasibility of defining a long-term aspirational goal (LTAG) for international aviation. Market-based measures, such as CORSIA makes air transport more expensive and hinder the growth of developing countries that generally do not have adequate air transport infrastructure. This article aims to demonstrate how Brazil has implemented several operational measures that have reduced emissions of millions of tons of CO2. These measures, together with performance-based management initiated in 2022, tend to gradually increase the efficiency of the air transport system and contribute to reducing emissions without harming the country's economic growth.

ABSTRACT. While the impacts of weather on transportation systems have been studied in terms of resilience and its characteristics, little is known about the effect of such events on cycling travel demand. In this paper, we aim to evaluate the resilience of cycling demand in the face of increasing generalized travel costs caused by link obstructions resulting from flooding after rainfall. Our proposed method identifies the blocked links of an urban road network at different levels of cumulative rainfall and estimates the demand for bicycle trips. The method was applied to different cumulative rainfall scenarios in São Paulo, Brazil. The results demonstrate a resilience value exceeding 0.96, indicating a high level of adaptability. Furthermore, the robustness of the cycling demand closely approached the maximum number of trips achievable in the absence of rainfall. Notably, the resourcefulness of the demand ranged between 32 trips per hour and 292 trips per hour. Our findings reveal a direct relationship between cumulative rainfall and cycling demand, driven by the obstruction of cycling network links. These insights can inform policy design and infrastructure development aimed at promoting bicycle ridership within the studied context.

ABSTRACT. This paper investigates the use of alternative fuels in international aviation and maritime transport within a 1.5C scenario. The global energy supply and demand model POLES is applied to carry out a current policy and a 1.5C scenario and to determine the development of the aircraft fleet and ship fleet with regard to their engine types and their potential fuel use. The fuel mix of international bunkers in 2050 is determined based on the shares of engine types within the aircraft fleet and ship fleet and the competitiveness of alternative fuels.

ABSTRACT. The COVID-19 pandemic has led to a major downturn in the aviation industry that has not only affected international flights but also domestic aviation. Airlines have adjusted their timetables accordingly, but load factors have remained low. This has resulted in a loss of profitability and a large increase of greenhouse gas emissions of individual air passengers. In order to prevent airlines from closing routes, governments have provided subsidies. However, these subsidies are in sharp contrast with the climate goals of many countries. This study explores the impacts of the COVID-19 pandemic on the domestic aviation sector in Finland based on actual passenger and landing data. It takes the changes in environmental impacts resulting from the demand shift cause by the pandemic into account. In addition, this study considers the replacement of existing aircraft with those powered electrically, in order to address the significant drop in demand due to the COVID-19 pandemic and provide an alternative for a green recovery from the pandemic. Finally, based on our findings we provide a series of policy recommendations.

ABSTRACT. Travel is an activity everyone carries out in their daily life. While travelling, air pollution exposure is likely to impact commuters’ mode / route / departure time choice. Various review studies on air pollution have been done in the past, but the aspects of its impact on travel behaviour is absent. In an effort to close this gap, this study carried out an extensive review of 63 studies to document the influence exposure to air pollution has on travel behaviour. The findings reveal that (a) the highest instances of behaviour change was observed when users shifted their routes, (b) USA and China have carried out majority of the research in this arena, (c) real-time information plays a vital role in lowering the air pollution exposure of commuters, (d) there are negligible studies related to assess user awareness of air pollution and how it may impact their travel behaviour, and (e) in-depth research on this topic is required in developing countries where air pollution levels are at an alarming stage, and worsening further. Finally, this analysis offers viable methods, which integrate Transportation demand management (TDM) measures and technology, for providing a clean travel environment to the commuters.

ABSTRACT. The establishment of the Emission Control Area regulations has led to changes in the trajectory and speed of vessels. These changes will inevitably affect the emissions produced by vessels. This paper uses Automatic Identification System data combined with pollution emission models to track the emissions of vessels in different regions within five consecutive years (i.e. 2012 to 2016). A number of important insights are revealed throughout the conducted analysis. Firstly, although the emissions of vessels sailing within the ECAs have been significantly reduced after the establishment of the ECA regulations, the ECA regulations have led to an increase in ECA boundary and Non-ECA emissions, resulting in an ECA boundary effect. Secondly, the implementation of ECA regulations led to an increase in the global CO2 emissions. Finally, the ECA regulations caused different types of ships to have diverse impacts on global emissions. Combining the ECA boundary effect and the impacts of ECA regulations on global emissions, various policies should be formulated according to different ship types to adequately address the deficiencies of ECA regulations. The present research study provides a theoretical and empirical basis for assessing the efficiency of ECA regulations and generates a different perspective for reducing pollution emissions globally.

ABSTRACT. In recent years, China's motor vehicle fleet has been increasing and the environmental pollution problem caused by exhaust emissions has become more serious. The key to motor vehicle exhaust emission control lies in the identification and management of a small number of high-emission vehicles. With the use of vehicles and the aging of exhaust treatment devices, the exhaust emissions per unit time or unit mileage of vehicles will continue to increase. This phenomenon is exhaust emission degradation. We establish an exhaust emission degradation model, which can provide a reliable basis for more accurate identification of high-emission vehicles and prediction of urban motor vehicle exhaust emission status. This study analyzed the overall technical distribution and pollutant emission characteristics of in-use light-duty gasoline vehicles in Nanjing based on the annual inspection data of Nanjing in 2018.Based on the investigation of the deterioration influencing factors, a linear deterioration model is established to reflect the deterioration trend of vehicles with different technical conditions. The average deterioration level of vehicles under different emission standards was taken as the model benchmark, and the influence of engine displacement, compression ratio, and average annual mileage on deterioration was quantified in the form of correction coefficients.

ABSTRACT. International agreements and European policies insist on the importance of reducing transport externalities. This contribution economically valuates the transport externalities generated along the Italian side of the Brenner axis, belonging to the Scandinavian-Mediterranean corridor. The aim of this analysis is twofold: to understand whether the evolution of travel demand in the last decade may fit the European objectives on transport externalities, and to forecast the expected impacts in 2030 and 2040 under alternative scenarios. The results of our analysis do not reveal a clear trend in the last decade: Rather than a generalised reduction, a redistribution of costs among categories is visible, with lower impacts from local pollutants and higher congestion and accident costs. In the future, the expected increase in travel demand will likely impact these externalities, and a further increase in road congestion and accident costs is foreseen, which is not expected to be fully compensated by the reduction of air and GHG emissions owing to the increased efficiency of the vehicular fleet, even in the case of massive electrification. The modal shift from road to rail and the digitalisation processes are requisite for better management of road traffic and a reduction in overall costs along the corridor.

ABSTRACT. The travel and activity restrictions related to COVID-19 dramatically changed the lives of Canadians, with important implications for well-being. This study analyzes the impacts of housing characteristics, local accessibility, and quality of active transport infrastructure on individuals’ life satisfaction during the lockdown. Data was collected through a Canada-wide online survey fielded in November 2020 (n=618), during the second wave of the pandemic. The survey captured information on travel behavior and activities during lockdown and perceptions of neighborhood characteristics, together with self-reported life satisfaction and housing characteristics. An exploratory data analysis followed by an ordered logistic regression was performed to assess the determinants of life satisfaction during lockdown. Findings reveal that access to a private yard as well as park space and sidewalks which are wide enough to maintain social distancing were key determinants of life satisfaction, whereas dwelling size was not. Building on previous research on life satisfaction and travel behavior, this study highlights the benefits of providing high-quality transport infrastructure and access to nearby outdoor spaces, specifically for those without access to a private yard. The findings are of relevance to support resilient cities that better meet the needs of all individuals.

ABSTRACT. Pedestrian level of service (PLOS) has been evaluated by means of relating measurable characteristics of urban sidewalks with a perceived comfort, satisfaction, pleasure, quality of service, or stress. However, these terms have been interchangeably used as PLOS proxies. Can these terms be used to identify a more powerful service or performance variable expressing pedestrian perceptions? We conducted a survey in 30 sidewalks in Bogotá and using a MIMIC model, we related the objective attributes with a latent variable that explains the previously mentioned terms which we named Sidewalk Perceived Service or Performance (SPSP). The aims of this paper are (i) to test if the previously mentioned terms can be used to identify a latent variable (i.e., SPSP) and (ii) to identify the objective measured attributes of the built environment explaining this latent variable considering different types of land use. We identified and defined the latent variable using the subjective and objective attributes of the built environment and interactions of these attributes with land use. This paper can be used to improve the pedestrian infrastructure in urban areas and sidewalk performance measurement, uncovering how SPSP can be identified and objectively defined.

ABSTRACT. The existing literature shows the built environment is associated with walking but does not indicate the importance and non-linear effects of the built environment on different walking purposes in developing countries. This study applied gradient boosting decision trees to disentangle the relative importance and non-linear effects of the built environment on walking duration for commuting, errands, and recreation in Shanghai, China. After adjusting for socio-demographics and walking preferences, the built environment collectively showed a slightly stronger predictive power on walking for commuting and errands than other predictors. Among built environment elements, road density and land use diversity have the greatest predictive power for walking for commuting and for errands and recreation, respectively. Moreover, population density, land use diversity, road density, distance to the city center, number of transit stops, and greening rate have non-linear effects on all types of walking. These results are valuable when planning walkable cities.

ABSTRACT. Covid-19 accelerated “pop-up” cycleway initiatives in cities across the world, which are often contentious for the business community in affected streets and neighbourhoods. Brisbane converted parking lanes to form the CityLink Cycleway in its central business district. While the project was positively received overall, there was vocal business opposition, primarily on the grounds of loss of parking and loading bays. A set of field surveys collected 303 valid responses: 44 from businesses, 247 from customers, and 10 from delivery workers. The results show businesses erroneously perceive customers’ travel modes, overestimating car usage, and underestimating the mode and expenditure share of customers who walk, use public transport, or ride bicycles or powered mobility devices. Customers and delivery workers had more positive responses about the cycleway, while businesses expressed mixed reactions. Retailers had a less accurate picture of their customers' modes of travel, than those running restaurants and cafés, as did business owners/managers who drove to work. Respondents’ suggestions for city centre access improvements were mixed, especially regarding crowding. The overall positive responses captured by the study demonstrate there is a strong case to retain the CityLink Cycleway longer-term. However, there are legitimate concerns from businesses and other users regarding loading bays.

ABSTRACT. Transit is an essential component of our modern societies’ transportation modes. Using transit first requires accessing one of its entry points. The conditions under which access to station is made are very decisive of the overall quality of transit networks. Still, there is little work that specifically focus on access path to transit nodes, their impact on the overall attractiveness of the transit network or the efficiency of the transit nodes’ catchment areas. This paper proposes a methodology to identify and caracterise subway stations’ catchment areas using walking network. Various indicators to assess the quality of these areas are hence proposed. The paper illustrates that efficiency of catchment areas vary a lot across the Montreal subway stations and that improving access to those important transit nodes would increase the amount of people having prime access to this important transit network.

ABSTRACT. The poor quality of public transport services is one of the main causes of social exclusion for people living in suburbs. Public transport companies tend to allocate few financial resources in these areas, offering transport services with low frequency, poor accessibility, poor reliability, and high waiting times at stops. Recently, microtransit appeared to be an effective solution to improve the travel experience of non-drivers in suburban areas, especially for non-commuting trips during off-peak hours. This paper aims to present a multi-step methodological approach for designing microtransit services to satisfy the mobility needs of people living in low-density suburbs. Conducting a SP survey and developing a four-step travel model, the demand was estimated as input for the service modelling. The combined use of GIS and macrosimulation software leads to identifying the best fleet size to satisfy the trip requests and set a fare. The method was applied to a case study to design a new microtransit service with flexible routes and on-demand stops for a suburban area in Palermo, Italy. The results highlight how introducing a microtransit service could change the mobility habits of people living in suburbs, improving their travel experience, and enhancing accessibility to amenities and public transportation hubs.

ABSTRACT. The COVID-19 pandemic led Malta to declare a partial lockdown on the 12th March 2020. In this paper we aim to reveal the emotions and the differences in the daily travel and activity patterns that were experienced by parents and their children during this time. We use data collected from an online questionnaire. Cluster Analysis was performed on the sample to determine population profiling. Following this, we thematically analysed the narratives related to the revealed travel activity patterns of the group of participants with children in their household. The findings showed that mothers and parents between the ages of 30-49 carried the most responsibility because activities shifted in-house; this group was labelled as “down to earth”. A content analysis revealed that parents suffered from anxiety due to restricted access and fear of contagion. Parents who did not suffer from anxiety were enjoying their family and home during the partial lockdown. The discussion includes recommendations to improve mobility and activities in extreme situations like a pandemic, among families with children and concludes with suggestions for future work.

ABSTRACT. Urban sprawl has caused various problems for city governance, such as traffic congestion, inefficient land use, and unaffordable housing prices, during the expansion of several metropolitan areas in the world. To prevent or mitigate such problems, proper planning of suburban areas is critical, where the prediction of the development trajectory into the future plays an important role. Herein, intricate interactions between the development of transportation systems, land use, and socioeconomic evolution may exist. This study seeks to capture the key interactions/relationships driving the development of Taoyuan Region, a fast-growing spillover region of Taipei, Taiwan, since 2015. Considering data availability, this study focuses on Taoyuan and Zhongli Districts, two major city centers of Taoyuan Region. Panel data analysis is conducted for preliminary exploration to identify key factors influencing the regional development of the two districts. The simultaneous equation model is further developed to capture the interactions between transportation systems, land use, and socioeconomic development from 2015 to 2019. The accuracy of the model is validated based on the prediction of the regional development in the first half of 2020, which shows reasonable prediction, suggesting the findings of this research be a reference for the authorities of urban and transportation planning.

ABSTRACT. Freight transportation is critical to the economic competitiveness and long-term viability of metropolitan regions. However, it is one of the activities that produce the most negative externalities, including greenhouse gas emissions. The study of the relationship between freight transportation, land use, and demand management is critical for promoting enlightened policies that increase the social benefits of supply chains while avoiding their undesirable effects, such as climate change. Nonetheless, the tools available to public planners for incorporating freight transportation into their analyses are limited. In this context, the goal of this paper is to highlight the impact that freight demand management strategies and freight efficient land uses can have on increasing urban freight accessibility. In this study, the authors suggest two measures of accessibility (an isochrone-based model and a gravity-based model) to analyze the spatiotemporal variation of freight accessibility in the New York City metropolitan statistical area for four sectors— retail trade, accommodation and food services, transportation and warehousing, and e-commerce. Results indicate that accessibility measures provide valuable insights towards policymaking, particularly to policies that target land use (e.g., location of warehouses), and policies that aim to shift the traffic of freight vehicles to periods with less traffic congestion.

ABSTRACT. To combat urban challenges such as air pollution stemming from excessive vehicle use, policy makers have adopted various driving restriction policies (DRPs) worldwide. Although previous studies have extensively justified the effects of citywide DRPs on air quality, little attention has been paid to urban core-focused license-plate-based DRPs (UCLDRPs), which have gained increasing popularity among major cities. To bridge this gap, we carried out an empirical evaluation of the short-run effectiveness of Shanghai's UCLDRPs in improving air quality using difference-in-differences (DID) modeling approaches on high-frequency air quality data. The results show that UCLDRPs did not significantly improve the air quality of urban cores (the inner ring area), while worsening the air quality of surrounding zones (the 5km buffer area). The concentration of major pollutants increased by 27%-31% and Air Quality Index rose by 17% in the buffer area. Moreover, 45% of unrestricted time hours witnessed higher concentrations of pollutants including CO and PM10 after the implementation of UCLDRPs.

ABSTRACT. Beginning in 2008, the EPA used a combination of national and state Diesel Emission Reduction Act (DERA) grant funds to encourage ports to retire aging drayage trucks. In the year 2010, the Port Authority of New York and New Jersey (PANYNJ) implemented its Port Drayage Truck Replacement Program (TRP) to improve air quality near the port. As of October 2022, 935 old trucks were replaced. Despite its importance, little is known about the program’s impact on local air quality, including which groups may have most benefitted. This paper examines the effectiveness of the port environmental policy by observing the changes in NO2 and PM2.5 concentration levels of vulnerable groups living near the port terminals. I use local air pollution levels and demographic information at the census-block group level. I employ Event Study with spatially autocorrelation adjusted standard errors. I find that air quality after TRP implementation generally improved for the near-port populations, who are likely to be lower-income Hispanic or Latinos with higher asthma rates. These findings imply that the current policy to accelerate to electrification is critical but diesel mitigation policy is needed as an intermediary solution to lessen the environmental disparities for the vulnerable and disenfranchised communities.

ABSTRACT. In the carbon neutrality background, this study focuses on economy and policy methods to reduce congestion and carbon emissions. By supplying limited amount of personal carbon allowances (PCAs), this study explores the expected effects of PCAs policy on commuters’ travel mode choices in transportation systems. We compare the congestion situation before and after the policy. Also, we assess its positive influence on transit priority. Besides, in this study, we analyze the impact of the total amount of carbon allowances on the effectiveness of the policy. For public acceptance, we consider not only the effectiveness but also fairness of the policy. We use the Pareto optimization approach to find the optimum total amount of carbon allowances. Numerical examples show that carbon allowances distribution and trading policy are very efficient in traffic management. It can effectively reduce car use and directs travelers to public transportation modes.

ABSTRACT. To increase urban space livability and sustainability, a Low Emission Zone (LEZ) imposes access restrictions based on vehicle pollution standards. In several cities, the absence of public support has reduced the effectiveness of this measure or even prevented its application. This paper aims to understand factors prompting and hindering acceptability of a LEZ in a medium-sized city and evaluate future impacts toward sustainable mobility habits. To provide a comprehensive view, several approaches were applied to data collected from a survey administered to stakeholders in Padova (Italy), where a Limited Traffic Zone (LTZ) is currently enforced. Results indicated that an effective strategy to increase public support is demonstrating how the current LTZ could generate benefits for society and environment, and how the new intervention could contribute to increase them. Car drivers are the strongest opposers to the LEZ, however the awareness of its potential positive impacts could prompt stakeholders to substitute their polluting vehicles. Lastly, supporters of the new regulation currently accessing the area by car could decide to use other travel means, only if effective alternative mobility options are provided. However, potential mode changes could occur only for infrequent trips, thus limiting the consequent benefits of this new mobility behavior.

ABSTRACT. An urban low-emission transportation system is dynamic and complex, with various socio-economic and vehicular characteristics, infrastructure, and other factors. This study is centred on holding out detailed research on systems dynamics concepts. This paper analyses the complicated dynamics of the relationship by building a metropolitan low-emission transport system. This research aims to create a System Dynamics (SD) design using STELLA to figure out the fuel consumption and vehicular emissions released from the transport sector in the horizon year 2028. The study considered Lucknow city, the capital of Uttar Pradesh in India, as a case study to simulate the low-emission urban region. The average air quality in Lucknow is satisfactory. Air pollutants such as Carbon (CO), NOx (NO2), PM (PM2.5 and PM10) are causing minor breathing discomfort to the sensitive people in the city.The annual fuel consumption in the city for private transportation was almost 87% of the total vehicular fuel consumption. A scenario planning of increasing public transportation and simultaneously controlling the growth of private transportation showed a decrease of nearly 42% in Energy consumption and a nearly 21% reduction in emission levels in private transportation.

ABSTRACT. In this study we explored the possible changes in passenger behavior on transit stations due to disruptions such as COVID-19 and the impact on station performance. A trade-off is observed between the reduced risk of virus transmission through increased physical distancing and subsequent negative impact on a station’s performance. To evaluate this trade-off, a simulation model of Marlborough station in Calgary, Canada was developed using PTV Vissim. Passenger behavioral changes were implemented by manipulating the Social Force Model (SFM) parameters within the simulation model. The impact from these changes were measured by the developed model and was simultaneously validated with the theoretical expectations derived from equations on the SFM parameters. Alternative station designs were simulated and tested to allow separated flow of passengers in different parts of station such as pedestrian bridges and stairways. The results from the study found that pedestrian physical distancing had a profound negative impact on the transit station’s performance. However, these effects can be addressed through simple low-cost station modifications. Ultimately, the results of this study can be used as a reference for transit authorities to develop mitigation strategies against possible resurgences of COVID-19 or other infectious diseases.

ABSTRACT. The rise of e-scooters has opened debates about their benefits and burdens. Main concerns are centered around whether e-scooters are replacing walking or transit trips. Attention has also been given to the risk of accidents and injuries for both users and non-users. Questions less-frequently asked, however, are how people enjoy and perceive e-scooter trips and whether there are any differences between shared and privately owned e-scooters. We gathered data through an internet-based survey in the United Kingdom and use descriptive statistics and a Structural Equation Model (SEM) to interrogate characteristics, perceptions and behaviors of e-scooter users and their links with travel satisfaction. As the main outcome variable, the SEM incorporates subjective satisfaction with travel measured using an adjusted version of the Satisfaction with Travel Scale. Results show that owners of private e-scooter perform more trips and travel longer distances than users of shared e-scooters, that leisure at the destination is the primary purpose for shared e-scooter trips while going home and going to work are the main trip purpose for private e-scooters, and that e-scooters trips are mainly replacing walking and transit trips. Results from the SEM suggest that trips on private e-scooters have higher levels of satisfaction.

ABSTRACT. This paper investigates the status-quo of food insecurity among the population residing close to transit in various parts of the United States of America (USA). The data from the 2020 National Health Interview Survey (NHIS) collected by the National Center for Health Statistics (NCHS) of the USA are analyzed in this research. Logistic regression is carried out by treating food insecurity as the dependent variable and socioeconomic variables such as age, income, education and dependency on the Supplemental Nutrition Assistance Program (SNAP) as independent variables. Food insecurity is assessed with aggregated information on four aspects of inputs from those respondents who live near a transit: 1) worry food would run out, 2) food didn't last, 3) couldn't afford to eat balanced meals, and 4) cut the size of meals or skip meals. Findings suggest that respondents who live close to transit in the US and are from large central metro counties of the Northeast, South and West states showed an increase in food insecurity if they were below 65 years of age, had income below country’s median income or their educational attainment was below bachelor’s degree. Significant association was found between food insecurity of respondents living close to transit.

ABSTRACT. Access to healthcare is key to well-being. To obtain a nuanced picture of how healthcare travel varies across patients, individualized healthcare travel research is needed. Hospital choices and healthcare travel choices are closely intertwined. Most studies focused on separate hospital choices or healthcare travel mode choices, for certain segments of patients, making it difficult to derive clear profiles of patients. A latent class model with covariate was built to identify different patient types that exhibited distinct hospital choices and healthcare travel behaviour. Attitudinal factors were included in our model to form clear-separated clusters. Finally, four categories of patients were identified: bypassing public transit patients, car-oriented patients, near-hospital patients, and non-downtown hospital patients, which differed in sociodemographic, healthcare-seeking behaviour, and public transit accessibility. A great share of non-downtown hospital patients indicates that low-level hospitals were able to attract patients residing in the outskirts, with chronic disease, and female patients with high healthcare travel frequency. The behaviour of bypassing and non-downtown hospital patients requires improvement in quality and public transit accessibility of tertiary hospitals in non-downtown districts. Our study contributes to a better understanding of the market segments of patients, and tailored healthcare and transport policies to meet patients’ healthcare travel demand.

ABSTRACT. In recent years, the recurrent destructive natural disasters (or natural hazard impacts) which occur worldwide have had a major impact on the society, economy, and security. Natural hazard impacts are being experienced as severe traumatic events and happen almost every day. The entire disaster management cycle from prevention, preparedness emergency management, response and recovery affect and impacts peoples’ behaviour, psychology, emotions, spirits, attitudes, and values as has been reported and outlined in this study. The purpose of this paper is to review the literature on the human and psychosocial factors associated with natural hazard impacts, with a specific focus on human factors related to floods and fires, on adult survivors, while also examining the crisis response management and evacuation process. It was considered timely appropriate to undertake an update and enrich this topic area.

ABSTRACT. Transportation is one of the most pronounced sources of noise pollution in urban areas. Frequent and excessive exposure to noise may negatively impact human behavior and performance which may also result in hearing damage especially for noise levels above 70dB. Philippine standards provide little emphasis on noise generated from traffic, with no local transportation noise models that can be applied in noise regulation or project evaluation. Equivalent sound pressure levels (Leq) along nine selected roads in Metro Manila were collected to determine whether the resulting noise levels are within the existing allowable standards. Multiple linear regression (MLR) and artificial neural network (ANN) models were then estimated to relate transportation noise to its contributing factors such as vehicular volume and vehicle mix, among others. Results show an average Leq of 70.806dB, which is not significantly greater than the 70dB threshold, nor the 75dB stipulated by local standards. The developed MLR and ANN models exhibited reasonable accuracy with R2 values of 0.88 and 0.85, respectively. Given the strong correlation of transportation noise with total traffic volume and percentage of heavy vehicles, a recommended mitigation measure is to restrict access of heavy vehicles along select thoroughfares or impose time periods allowing road access.

ABSTRACT. Considered as the most ambitious program in the Philippines, the Public Utility Vehicle Modernization Program (PUVMP) requires transport cooperatives to replace their old jeepney with modern units. This however requires massive financing, and the government only provides very limited equity subsidies. This paper examines the impact of service contracts on the financial capacity of transport cooperatives to replace their fleet of old jeepney units. Using qualitative data drawn from interviews and surveys with 12 transport cooperatives, we investigate the effect of service contracting on the ability of transport cooperatives to access financing in terms of loans from banks. We find that long-term service contracts can enhance the level of confidence of transport cooperatives to service debt. Our work presents a novel mechanism to mobilize financing from private banks for the reform of the informal transport sector.

ABSTRACT. The present paper presents an analysis of the recent concession policies undertaken to foster transport investment in Brazil. As fiscal restrictions have increased in severity, this investment has dwindled below the levels necessary to maintain the existing network and to develop and expand. Consequently, private investment has become an mandatory option. This paper analyses the concession policies and contracts implemented in Brazil and highlights the limitations of this option. The paper reveals that the loss of capacity for the planning, design, and management of complex contracts has led to the government’s growing dependence on the private sector, whereby contracts are designed and performed according to the financial interests at the expense of public ones. By analyzing the issues of transport funding, the paper addresses a circularity problem: regional growth requires infrastructure investment, the viability of which depends on regional growth. As a response to the described shortfalls in transport infrastructure investment, the paper concludes by proposing an innovative institutional framework that foresees a more integrative planning and investment programme in infrastructure, industry, and public services.

ABSTRACT. Efficient logistics of fertilizers play crucial role in ensuring availability to farmers when and where required. Being an essential commodity, planning, production/import, distribution, movement, pricing, and related activities of fertilizers are regulated in India. Logistic cost of fertilizers is very high due to complex distribution network, infrastructure bottlenecks, and regulations. This paper identifies cost inefficiencies in the supply chain through stakeholder interactions and field visits. Shortage of railway wagons during peak season and high handling costs are identified as key challenges. This paper examines feasibility of moving bagged fertilizers in 20’ISO containers on railway flats and compares costing with conventional railway wagons presently being used. Movement of 25% of imported fertilizer cargo from Mundra port (approx. 1 million metric tons per annum) to selected 19 destination railway terminals is taken as a case study. The results indicate that container movement is economically feasible for long-haul movements.

ABSTRACT. Decarbonizing the transportation sector is one of the key challenges to reduce greenhouse gas (GHG) emissions and meet EU Green Deal 2030 targets. In this paper forecasts for 2030 are developed to evaluate tank-to-wheel GHG emissions reduction potential for the Italian road transportation sector. This study used the Avoid-Shift-Improve (ASI) approach to build an “High decarbo” and a “Low decarbo” scenario, based on different hypotheses on exogenous variables (e.g., GDP) and penetration rates of measures and policies already in place promoting sustainable transportation (e.g., subsidies for electric vehicles). This approach is meant to be consistent with the “deep uncertainty” regarding key economic and social variables in this period. Results indicate that a decarbonization process of the Italian road transportation sector is already underway, but “Low decarbo” forecasts lead to a 9.3% reduction of TTW GHG emissions compared to 2005 levels, far from UE Fit for 55 goals of 40%. However, under favourable hypothesis GHG emissions might be reduced by 30.3%, almost meeting EU targets. Furthermore, passengers and freight show a very different behaviour. The main conclusion is that the transport system evolution has to be constantly monitored to check the decarbonization trajectory and constantly adjust policies to this end.

ABSTRACT. Curve geometry is the most significant variable for any highway geometric design. The highway alignment includes various curve geometric features affecting the operation and safety of the driver/vehicle. Therefore, it is essential to identify the factors that cause the highway section’s operation and safety. With this, the study aims to develop an operating speed prediction model as a function of curve geometry and vehicle dynamics. The present study selected National Highway (NHs-953) from the hilly terrain as a study section. From that, 30 curves were selected for data analysis purposes. Next, vehicle speed data were collected using the well-calibrated radar gun on the selected curve. A total of 16,200-speed sample was collected. After that, a linear regression technique was adopted to model vehicle operating speed. The model results revealed that curve length positively correlates with vehicle operating speed. In contrast, deflection angle, curve sharpness, weight-to-power ratio, and vehicle dynamic value negatively correlate. Then, various goodness-of-fit measures and the Taylor diagram were used to validate the developed model. Lastly, the sensitivity analysis is carried out to check the effects of curve sharpness and vehicle dynamics on the driver speed choice behavior.

ABSTRACT. The present study aims at developing a saturation flow estimation methodology for non-lane based mixed traffic streams, which is necessary for the capacity estimation and signal design of signalized intersections. The methodology involves formulating a base saturation flow model for mixed traffic streams and adjusting it to the site conditions using adjustment factors. Base saturation flow is described as a function of width using the concept of unit saturation flow. Further, the traffic characteristics affecting this base saturation flow are developed as adjustment factors. The proposed model is calibrated using field data collected from sixteen signalized intersections across five cities in India. These saturation flow values from the field are used to calibrate the developed width-based base saturation flow model. Further, adjustment factors for bus blockage, blockage by right-turning vehicles and initial surge are developed considering the discharge behaviour of vehicles in mixed traffic conditions. Agreement of the model with the field observed saturation flow value indicates the reliability of the developed saturation flow model in mixed traffic streams. The developed model is specifically helpful for engineers and planners dealing with non-lane based traffic conditions wherein the discharge pattern in the field does not comply with the ideal discharge curve.

ABSTRACT. Unsignalized intersections operate on the basis of gap acceptance. In developing countries, the drivers are aggressive in accepting gaps and they accept small gaps to merge into main traffic streams. This fast and aggressive behavior causes dilemma among drivers whether to cross or not to cross. The dilemma is affected by parameters such as speeds, vehicle type and intersection features. The study also explores a physiological parameter called driver’s impatience (DI), which quantifies the behavior of the driver after they have rejected a series of available gaps. The result also shows that drivers often get impatient and accept smaller gaps as they reject more gaps before accepting the next one. As a result, accepting smaller gaps by the driver increases the risk of crossing conflicts and shifts the dilemma zone nearer to the intersection. The aspects of the turning vehicle type is also incorporated and modelled into a binary logit model including speeds, gap size and vehicle types. The results may be used for the development of ADAS models in heterogeneous driving conditions for developing countries.

ABSTRACT. This paper examines the intention to use autonomous vehicles (AVs) in Bangkok, Thailand, where the level of readiness for AVs in terms of infrastructure, technology, and regulation may represent other developing countries where individual preferences and operational environment are generally different from more developed countries. We analyzed survey data of 797 respondents in the Bangkok Metropolitan Region, using a modified Technology Acceptance Model. The model incorporated additional factors, including trust, perceived risk, and operational environment of AVs, as they could affect the intention to use. We found that all latent constructs, i.e., perceived usefulness, perceived ease of use, trust, and perceived risk, were significantly associated with the intention to use. Trust was found to be the most powerful factor; it directly increased intention to use the vehicles, and indirectly increased intention to use through improvement of perceived ease of use and reduction in perceived risk. Such findings imply that familiarizing the general public with such technologies might help to improve trust and promote AVs adoption. The results also suggested that to promote the use of AVs in developing countries, the operating environments in areas where AVs are allowed should be well designed and regulated to ensure confidence of the public.

ABSTRACT. The present study demonstrates a methodological approach using which a key set of attributes from a comprehensive list of attributes affecting the adoption of Plug-in Hybrid Electric Vehicle (PHEV) is prioritized based on consumers’ perception in a typical Indian context. Delhi and Kolkata, two Indian megacities were selected as study cities for analyzing conventional car owners’ importance rating towards 22 attributes affecting PHEV choice. Initially, using Kruskal-Wallis H-test, the heterogeneity in consumers’ importance rating for PHEV-related attributes was investigated across different population subgroups. The results indicate a significant difference in perception for various attributes between the two cities. Hence, two separate models were developed using Exploratory Factor Analysis (EFA) to identify the latent factors influencing consumer perception towards PHEVs. Finally, based on EFA and Grey Relation Analysis (GRA), purchase cost, safety, air conditioning, battery warranty, public charging availability, battery recharging time, and tailpipe emission were identified as the key attributes affecting the adoption of PHEVs in the Indian context. The key attributes could be used for the formulation of effective policy suggestions for car manufacturers and the government to make PHEVs more appealing among Indian consumers and could be used for designing stated preference experiments for valuing the attributes.

ABSTRACT. The transport sector is one of the largest emitters and fastest-growing source of GHG emissions. A focus lies on urban areas in the Global South, where high population growth and urbanization rates increase transport demand. In this context, we assess the adoption of a new technology, electric three-wheelers, from a socio-economic perspective by modeling three-wheeler drivers’ interest to switch to electric vehicles (EVs). We use stated-preference data (N=152) collected in Dar es Salaam, Tanzania. Our results show that: (i) the vast majority of drivers (82.2 %) are interested in transitioning to EVs; (ii) anticipated cost savings increase interest in EVs; (iii) the financing and/or ownership of the vehicle and the availability of guarded night parking are relevant adoption factors; and, (iv) most of the interested drivers are organized in driver unions that are typical for informal transport markets. We conclude that policymakers should focus on charging infrastructure and the provision of financing schemes to foster the uptake.

ABSTRACT. The use of variable message signs (VMS) is an effective method for providing drivers with real-time traffic information. Drivers being aware of the real-time traffic condition of the system, allow drivers to explore different route options and balances the road network to reach equilibrium in a very short time. In developing countries most drivers don’t use vehicle in-built navigational systems, the use of VMS is more important. This study develops a methodology to identify the optimal locations to establish a Variable Message Sign system for corridor level traffic balancing. The study compares the multi-user class trip assignment result from a calibrated, macroscopic trip assignment model for a typical road network. It identifies the locations to place VMS to divert traffic to have both user and system optimization. The validity of the strategy was tested through a case study of traffic entering the Colombo, Sri Lanka from East-West corridor. 6 major locations for corridor level diversion using VMS and 7 minor locations to support the major diversion using auxiliary signage boards were identified. The results show that with 30% of potential diversion vehicles directed through VMS, a 10% vehicle reduction in the Rajagiriya section and 18% in Malabe could be achieved.

ABSTRACT. Urban bus systems are becoming increasingly important as urbanization and traffic volumes increase. Travel time is an important component of this system. Providing accurate information about the future is essential for improving user satisfaction and optimizing the use of existing facilities. With the implementation of automatic vehicle location (AVL) systems for monitoring bus locations, it is possible to access bus traffic data, which is helpful for forecasting. Analyzing AVL data from Tehran, Iran, this study compares a statistical approach to a deep learning approach for predicting inter-stop travel time. According to the results, deep learning outperforms the statistical model in travel time prediction. Additionally, the sensitivity analysis shows that arc lengths and directions are the most significant factors in travel time predictions. The developed models can predict travel times in transit applications with reasonable accuracy. Developing countries with similar public transportation systems and mobility characteristics can use the findings to improve bus services.

ABSTRACT. Modern freight transportation relies on trucks delivering millions of packages daily. There is limited research on urban infrastructure service quality, particularly signalized intersections for truck traffic use. Trucks experiences different service levels due to their low maneuverability, acceleration and deceleration. As India's economy grows rapidly in turn, resulting high truck demand in turn requiring truck service quality examination. This study collects traffic, geometric and conglomerative data from five Indian cities with 30 signalized intersections and 105 approaches. Truck drivers' satisfaction is collected at city outskirts where truck traffic is significant. Truck Level of Service (TLOS) is modelled using variables which have statistically significant correlation with perceived satisfaction score using Spearman correlation analysis. Generalized Additive Models (GAMs) use these variables as inputs. It is a intermediate modelling approach to black box machine learning algorithms and simple statistical models; which has a strong capability of handling the non-linearity in the perceived scores. In this study, six parameters affect TLOS, while some manuals use V/C ratio or control delay only for LOS estimation. Final GAM-TLOS model shows high accuracy with 0.92 R2. GAM-TLOS scores for service classes A-F obtained by linear interpretation of Likert Scale is valuable tool for Planners and designers.

ABSTRACT. Everybody has an equal right to access opportunities, and public transportation is one way to get this access. Including equity in public transportation systems contributes to developing sustainable cities. Brazilian public transportation has been gradually losing demand, causing chaos in terms of mobility and financing of the system. This paper aims to evaluate public transportation equity by analyzing the demand and supply relationship. Using supply data from public transportation, smart card demand, and socioeconomic data, we proposed an approach to diagnose the customer level of service and estimate the potential excluded demand. We applied this approach in Jaraguá do Sul, Brazil. The results show that 85% of the population has access to public transportation. However, only 33% is the low-income population, i.e., the two lowest-income quartiles. In addition, the service is poor or missing for 53% of the lowest-income quartile of the people in the morning peak, which has the best supply service of the day. Findings showed the approach's applicability during the public transportation planning process to provide a more equitable service. Moreover, the identification of potential excluded demand shows areas for improving the service offered to increase the demand for public transportation.

ABSTRACT. China has witnessed a significant imbalance in socio-economic development with its rapid urbanization. Increasing attention has been given to transport equity. However, most of the current research in China are empirical studies utilizing definitions and measurements of equity largely originating from Western countries. Due to China’s unique social institutions, conventions and development conditions, Western transport equity theories may not be fully applicable in China. This research develops a conceptual framework of transport equity suitable for China’s socio-economic conditions, grounded on a critical review of transport equity literature from both China and Western countries, and wider equity theories combined with literature on Chinese traditional culture and political institutions. A discourse analysis of transport documents along with semi-structured interviews with Chinese transport practitioners are introduced to ensure the conceptual framework can be operationalized for guiding transport practices in different-sized Chinese cities. As well as identifying the range of benefits and burdens to be distributed, and clarifying which disadvantaged groups to focus on, we found the proper distributional principle should be maximizing the development prospects of disadvantaged groups, while for cities with limited capability and resources, the principle of ensuring a baseline for every citizen to meet their basic needs is more practical.

ABSTRACT. We evaluate two schemes of service contracting (SC) program implemented for the first time in the Philippines: gross-cost and net-cost. Using an automatic vehicle location (AVL) dataset generated using a mobile application, we examine the supply and performance of jeepney, a form of paratransit, on 20 routes during the pandemic. Ten of these routes are under gross-cost, and the other ten are under net-cost. Our evaluation suggests that gross-cost SC has resulted in more kilometer-run travelled, more arrivals at the stop, shorter headway duration, which are indicative of increased supply, compared to net-cost. However, we obtain mixed results for metrics associated with performance (headway regularity, dwell time and route compliance) for gross- and net- cost. We recommend that for SC to maximize its impact and raise performance, the government should set standards on metrics associated with fleet management and enforce strict compliance. Since SC is typically applied for the management of formal public transport, our work represents a novel contribution on the application of SC on the management of paratransit in the Global South.

ABSTRACT. The public transport systems in most developing countries in Southeast Asia are usually unreliable and inefficient. This results to reliance on innovative but informal form of transportation such as para-transits that operate with restrictions. Para-transits such as tricycles are the most in demand transportation mode especially in Southern Iloilo, Philippines. To be able to regulate tricycle operations in the area since they are not allowed to use national roads, the study recommended solutions based on the guidelines of the local public transport route planning (LPTRP) manual. The study investigated the existing public transport services in Southern Iloilo and proposed route service improvements while regulating tricycle operations along national roads. Primary data used came from the Household Interview Survey conducted in 2018 which were analyzed using Simple Category Analysis (SCA) to estimate the average trips generated in the household. Proposed improvements include introduction of different PUV services and modification of existing services particularly tricycles. These proposals were modelled using the transit assignment methodology in EMME software and evaluated using the LPTRP standards specifications. Proposed service operation and route improvements are expected to provide efficient and reliable service to commuters in the study area.

ABSTRACT. This paper addresses the paradoxical role of subsidy when it becomes malignant generating inefficiency and inequity. The implicit subsidy, when becomes perverse, are difficult to assess as there is no comprehensive method to evaluate. The rationale for introducing subsidy in transport services is to correct the market failures, negate the negative externalities, and improve the ratio of benefit to cost. This paper probes into the explicit and implicit cost of using private car, bus and two-wheeler and exposes the unfairness meted out to public transport by way of lower share of taxes, policy incentives and the huge implicit subsidy to private vehicles, the latter being in the guise of opportunity cost of using the road and related infrastructure by the private vehicles. Results indicate that private vehicles not only experience more than double the amount of subsidy availed by buses, these also simultaneously impose multiple negative externalities on public transport by negatively impacting their operability. This paper offers a set of tools which could bring the implicit subsidy in the formal pricing regime and would thus help in mobilising resources for the development of public transport infrastructure through ring-fencing.

ABSTRACT. This paper addresses the key elements for public transport reform, which are essential in the larger agenda of improving urban mobility in developing world cities. The paper discusses the typical organization for public transport in developing countries along the lines of competition in the market. It analyzes gender implications because transport meets women’s travel patterns and demands poorly. The critical elements of reform for improving public transport are changing to competition for the market and the way operators are remunerated. Stakeholder engagement and consultations are critical elements in making reforms politically viable. Reforms imply changing risk allocation and remuneration and protecting operators that invested from predatory competition. Formalizing contractual relationships and labor formalization are also parts of the reforms. As reform advances, cities realize they need a city-wide approach through selective areas. Reforms are about internalizing the externalities present in the competition in the market arrangement. Formalizing labor is one example of internalization. Formal labor costs much more than an informal one. Formal labor, however, delivers quality and safe service. Subsidies are needed in many cases to cover higher costs while keeping fares affordable, particularly for the poor, some women, and other users who are transferring.

ABSTRACT. In the Philippines, tricycles are the most prevalent modes of transportation that feeds and supplements other modes of transportation. In Panay Island, there are different provinces that has different physical and economic status which can affect the number of tricycles. This study aims to analyze and assess the current tricycle service operation and practices and municipalities in Panay Island. It also aims to determine the relationship between the socio-economic and physical characteristics of the community to the number of tricycles operating in each municipality, while also being able to characterize the supply and service operating characteristics of the existing tricycle service. Spatial maps are also developed using QGIS and analysis is performed using Microsoft Excel. Results show that factors such as road length, population, annual average income, number of schools, employment rate, and number of households are mostly positively correlated to the number of tricycle units in the study area. The study also shows that as other factors increase in the study area, the number of tricycle units would also increase. A tricycle zone is created for Roxas City. The various zones were created by considering the clustering of roads and buildings, the presence of a tertiary road and landscape.

ABSTRACT. The accessibility and convenience of transit services vary widely throughout major, auto-dependent cities. Despite growing evidence of their significance, questions exist concerning how transportation equality concepts are integrated into planning processes. Also, having access to reliable transportation is essential for full social involvement, and growing evidence shows the adverse effects of limiting access, especially for low-income populations. There are disparities in accessibility and mobility afforded by transit services in major, car-dependent cities. There is growing evidence of the relevance of transportation equality, yet issues remain concerning how to include transportation equity concepts in planning procedures. Reliable transportation is essential to social inclusion, and growing evidence shows the costs of inadequate service, especially for low-income neighborhoods. In addition, several other studies aim to redefine what is meant by "equity." Policymakers take key mobility features and geographical and socio-demographic variance into account to ensure fair transportation planning that balances national goals and regional needs. Lastly, this research suggests using driving automation technology as one of the most anticipated advances in a transit-friendly system.

ABSTRACT. Promoted for their contribution towards decarbonising transport, encouraging modal shift towards active travel, and improving physical and mental health, bikeshare schemes (BSS) have developed rapidly worldwide. However, under-performing schemes, vandalism of stations, alongside equity concerns related to unfair access and use for disadvantaged communities, has placed pressure on BSS operators and local authorities to manage both social and economic objectives. It has been found that barriers to use for disadvantaged users include: price, inconvenient walking distance to docking stations, concerns about personal safety and vehicular traffic as well as limited integration with public transport. The barriers to use related to socio-economic status, therefore, are interrelated with characteristics of the built environment. Understanding the factors associated with low or high levels of BSS usage is necessary to inform decisions on bike distribution, pricing, station location and promotional strategies. The aim of this paper is to review the literature concerning the socio-economic and built environment determinants of BSS use. The implications for codes of practice are discussed, as well as a future research direction. This pertains to policy for scheme expansion and implementation, as well as the location of docking stations, including transferability to cities who do not currently operate a BSS.

ABSTRACT. With population increasing in urban areas and an observed trend of increasing effects climate change impacts around the world, it is becoming increasingly more important to come up with measures for climate change adaptation centered around cities. This study examines the urbanization in a section of Circumferential Road 5 (C-5), Philippines and its effects on the traffic volume, carbon emissions, and climate change impacts. Results show an increase in emissions as urbanization in the study area increased. Significant correlations are also seen in carbon emissions and sea surface temperature; sea surface temperature and maximum sustained winds of tropical cyclones entering the Philippines, respectively. With an established indirect correlation on the possible implications of urban expansion to climate change impacts in the study area, Critical Transport Infrastructure concepts can be applied in for C-5 to help mitigate economic loss and disruption to vital logistics during climate events

ABSTRACT. In this study we (1) analyse the reliability of a new measurement of perceived walkability (i.e., the Short Perceived Walkability Scale), (2) examine the determinants (i.e., walking motivations, built environment, and socio-demographics) of perceived walkability, and (3) analyse the effects of perceived walkability on walking behaviour and walking satisfaction. The data from this study comes from the European project “WalkUrban”, and data has been collected at the end of 2022 in Gothenburg (Sweden), Dortmund (Germany), and Genova (Italy). The data of this project will be analysed in the first part of 2023, and presented at the WCTR 2023 conference in Montreal.

ABSTRACT. As the first international metropolis in China, the rapid economic growth brings about a continuous influx of population, and the urban traffic operation is facing new challenges. Shanghai puts forward the goal of accelerating the integration of rail transit in metropolitan areas and gradually forming a Shanghai metropolitan area with Shanghai as the center and radiating suburban new cities and neighboring cities such as Suzhou and JiaXing. At present, there are some problems in rail transit in Shanghai metropolitan area, such as imperfect development, a mismatch between supply and demand, unclear functional level,and imperfect policies. Under the background of "Shanghai 2035" in the new period, this paper explores and studies the coordinated development of multi-level rail transit in the Shanghai metropolitan area, taking higher quality development and high-quality life as the fundamental foothold of planning and implementation, highlights the world, faces the future, and always adheres to the highest international standards and the best level with a broader vision.

ABSTRACT. Private cars are a key component of personal mobility. They however consume a lot of space when parked or travelling and generate numerous externalities. They are among the most visible mode of transportation both due to their size, which has increased over time, and to the infrastructures on which they rely to park and move. This paper proposes new metrics to consider the space and energy consumption of cars in cities. Road network data is used to evaluate the network coverage. Car trips from travel surveys combined to car fleet datasets are used to evaluate the surface (2D) and volume (3D) footprints of cars over time and across space. The energy footprint of car trips is also evaluated, namely regarding the activity and the duration of the activity they allow to reach. Results show the important transformation of the car fleet and the increasing 2D and 3D footprint they have. They also demonstrate that larger car can reduce parking capacity, increase congestion, and prevent energy savings.

ABSTRACT. Individuals modify their behavioral strategies through repeated experience and learning. Therefore, it is necessary to consider the information-learning and forgetting mechanisms in repeated choices. In this study, we propose an evacuation behavior model that describes how an individual's preferences change dynamically due to learning and forgetting information and past decisions. Focusing on the two dynamics in the learning process, we formulate a dynamic discrete choice model for decision-making during evacuation using the recursive logit model. The utility function of the model is updated by acquiring new information and forgetting the old one. We conducted a repeated intervention and observation experiment of evacuation choice in Tokyo and estimated the model parameters using the obtained data. The estimation results assuming latent classes revealed heterogeneity in the individuals' learning process, so opposite behaviors could be chosen even when the same information was given.

ABSTRACT. China and India are among the world's largest auto markets and carbon emitters. Both countries have considered policy levers affecting fuel prices, car prices, and fuel economy to reduce car sector emissions. This study estimates new car buyers' responsiveness to policy levers and drivers, including income. We also estimate rebound effect and feebate effectiveness. We developed a joint discrete-continuous model of car choice and usage based on revealed-preference survey data from 8000 new car buyers in India and China who purchased cars in 2016-17. Conditional on buying a new car, the fuel consumption is relatively unresponsive to fuel price and income, with magnitudes of elasticity estimates between 0.12 and 0.15. For both markets, segment-level direct fuel consumption elasticities relative to car price and fuel economy range from 0.57 to 0.65. The rebound effect on fuel savings due to cost-free fuel economy improvement is 17.1% for India and 18.8% for China. A revenue-neutral feebate policy, with average rebates and fees of up to 15% of retail price, resulted in 0.7% fuel savings for both markets. Although the feebate policy's rebound effect is low (7.3% for India and 1.6% for China), it is not an effective fuel conservation policy.

ABSTRACT. Online food delivery (OFD) has changed the restaurant industry, altering consumption and travel behaviors. Yet the rapid growth of OFD and its effects on transportation emissions and travel behavior raises important questions about its environmental impact. Our research examined the effects of OFD adoption on restaurant trip frequency, travel distance and travel mode by investigating three types of impacts, including (1) substitution, (2) induction, and (3) modification. We conducted a questionnaire survey in Bangkok to collect data on consumer OFD usage and restaurant trip behaviors. The restaurant trip reduction model was formulated by using ordered logistic regression. The result from the model indicated that OFD adoption significantly substituted the frequency of restaurant trip. Comparative analysis between OFD trips and consumers’ alternative restaurant-related behaviors by considering travel distance and travel mode revealed that OFD trips generated more CO2 emissions by a strong induction- and modification-effect. Specifically, we found that the average CO2 emission per OFD order was 314.7 g CO2-eq. This was notably higher than a consumer’s alternative behaviors, which emitted approximately 217.5 g CO2-eq per trip.

ABSTRACT. Long distance passenger travel has received rather sparse attention for decarbonisation. For England, we find that only 2.8% of passenger trips per capita are for long distance travel, but they account for 61.6% of the miles and 73.3% of the carbon emissions from passenger travel. This highlights their importance for decarbonising passenger transport. Per capita, long distance miles have also been increasing over time, trending in the opposite direction to shorter distance travel. Flying for leisure and social purposes are the largest contributors to long distance miles and emissions, and these miles continue to increase, too. Overall, per capita travel emissions are decreasing – very slowly – primarily driven by efficiencies in service delivery, modal shifts and reductions in domestic travel demand (although aggregate emissions are not reducing). For travel demand related initiatives to reduce carbon emissions, long distance travel – especially flying – offers orders of magnitude larger emission reduction elasticity (in terms of % emissions reduced/ % trips disrupted) compared to urban travel, which suggests a proportionate policy approach is necessary. (please ignore the other paper -no 5032- submitted to a different group by mistake)

ABSTRACT. Walking has been the dominant transport mode for many centuries. Although walking is not usually seen as a transportation mode, every human trip begins or finishes with walking. Pedestrians form the largest single road user group and also are the most vulnerable and we are all pedestrian as some points in our journeys. Whilst walking is recommended as part of physical activity, it is necessary to provide a conducive and safe walking environment. The aim of this qualitative research is to examine pedestrian infrastructure availability and accessibility on urban highways with a focus on Lagos-Ikorodu corridor in Lagos State. The methods used were direct observation, field measurement, interview, and the use of GPS. The results were analysed using descriptive analytical technique. The studies investigated the availability of pedestrian infrastructure and determine the level of its accessibility to pedestrians on in the study area. The findings showed that there are insufficient pedestrian infrastructures in the study area and the awareness rate is also low. The study therefore recommends among others the concept of “5 Es” (Engineering, Expansion, Education, Enlightenment and Enforcement as a way to enhance the safety of pedestrians on urban highways.

ABSTRACT. BRT system is a low-cost, flexible-implementation public transportation (PT) system. Kabul, like many Asian cities, is plagued by a lack of effective public transportation infrastructure. Therefore, Kabul Municipality (KM) conducted a preliminary survey in 2017 to understand residents' attitudes toward the growth of the PT system by introducing BRT system. They revealed that people are interested to switch from present PT modes (bus, minibus, and microbus) to the projected BRT system. The purpose of this paper is to determine whether the deployment of a BRT system affects the reduction of existing PT modes. This research introduces a BRT system in Kabul city along a specified route that considers high travel demand via travel demand modeling and forecasting (four-step-method) and estimates the degree of low-capacity PT vehicle reduction using the trip assignment and modal shift result from the inquiry and KM survey. Finally, the outcome indicates that the BRT system has a consequential impact on reducing low-capacity PT vehicles.

ABSTRACT. Based on a dataset of all individuals with a home address in Flanders and Brussels (Belgium), the paper unravels the socio-economic profiles of zero-car households and sheds light on their residential environment. Furthermore, the study explores the proportion and size of voluntarily car-free households and households that are carless due to constraints. Four groups of zero-car households are identified: firstly, 29.2% are carless and are characterised by vulnerable socio-demographic characteristics. They reside in an area that lacks a decent public transport offer and simultaneously deal with limited household budgets. The second group consists of people who can benefit from adequate accessibility levels due to their residential location that is characterized by a high node value (33.6%). Like the former group, vulnerable socio-demographic profiles are overrepresented. Members of voluntarily car-free households account for 14.9% of zero-car households. Regarding socio-demographic characteristics, this group sharply contrasts with the carless one. Finally, 22.3% combine low accessibility with high incomes. The paper highlights that despite the evidence that zero-car households are strongly present in city centres, the share of zero-car households living in remote areas should not be neglected, and that carlessness can be considered as a proxy for vulnerability.

ABSTRACT. In recent years, the debate on a real diffusion of driverless autonomous vehicles has been growing, also thanks to the advancement of technologies that led to the creation of increasingly efficient prototypes. In this respect, while driverless transit is a reality in the case of railway fixed guideway systems, few steps have been taken in the actual implementation of automated road transit (i.e., buses). Tests have been conducted during the last decade, but most of them show that there is still no structured knowledge of the acceptance of users regarding this type of system. In particular, in Italy, some pilot projects have been carried out, but they have never resulted in surveys that characterize the acceptance of the system by the population, analyzing its distinctive features compared to other international practices. In this paper, the results of a survey conducted on a real test experience of an automated shuttle in the Italian city of Bari are presented. The aim is to investigate the acceptance towards the system and analyze its relationship with the population’s socio-demographic characteristics and current mobility habits. Results provide first insights into the willingness to use the system, but also pave the way for more in-depth investigation.

ABSTRACT. Sustainable Urban Mobility Plans (SUMPs) or similar documents of 17 European capitals and the European SUMP guidelines have been studied by text analysis techniques to identify development tendencies in a time and cost-effective way, without the need for traditional techniques of deep semantic analysis. In line with previously defined frameworks, cities have been classified according to size and mobility clusters of their countries. Besides traditional statistical indicators, Category Term Frequency (CTF) indicator has been introduced as a new statistical measure in text analysis to reveal the number and proportion of words belonging to the same group in terms of mobility-related content. Words in this corpus have been classified into 7 specific categories. Results indicate that some categories of general aspects (future, general transport, environment, society) are much more represented than the other three of more forward-looking character (automation, electromobility and sharing). Aggregated CTF of these three categories are the highest in the mobility plans of Luxembourg, Copenhagen, and Helsinki, which are forerunners in these emerging technologies. The findings may help to understand the development strategies in a city and, the text analysis framework developed provides planners and decision-makers with a novel tool to identify the focus areas of mobility-related documents.

ABSTRACT. Understanding the factors that influence intention to use automated shuttles can inform strategies to promote ridership. Limited research has investigated factors that influence intention to use automated shuttles operating in Canada and in mixed traffic. In addition, previous research has measured intention-to-use without considering the frequency of intended use. We surveyed the public in 2021 about a temporary automated shuttle trial (planned for operation in mixed traffic) in Toronto, Canada, before its deployment for public use. Our objectives were to investigate predictors of intention-to-use in a mixed traffic context in Canada and whether factors affecting the likelihood of trying the shuttle differed from those affecting intended frequency of use. Ordinal logistic regression results showed that higher perceived usefulness, positive attitude towards the service, and higher trust in the shuttle capabilities significantly predicted both measures, but age was a significant (negative) predictor only for intended frequency of use. This difference in demographic effects for the two examined measures suggests that future research should assess intention-to-use in more detail. Our results can also inform strategies to promote future automated shuttle trials. For example, informational campaigns to promote trust in the shuttle’s capabilities and highlight benefits of the service may improve intention-to-use.

ABSTRACT. Managing tourism and visitor mobility is the key issue for urban destinations in order to achieve sustainable development. The desired outcome is reducing residents’ dissatisfaction and disruption, and improving tourists’ quality of visit. Thus, based on a analysed case studies (good practices) from various cities in the world, this paper outlines thematic strategies for managing visitor flows in urban destinations by using a combined approach of transportation and tourist-site management. The selection process is according to a set of criteria, using multi-objective analysis

ABSTRACT. The comprehensive utilization planning of rail transit station area space is one of the keys to determine the success or failure of TOD mode. As an important part of rail transit, the functional positioning of station area space is the basis of comprehensive utilization planning. Based on the typological perspective, this paper takes the three functions of station area in urban structure, transportation network and investment development as clues, and establishes a multi-dimensional integrated station area planning function positioning method from three perspectives of center coupling, interchange demand and investment coupling respectively, so as to provide effective reference and guidance for giving full play to the economic value and passenger flow value of station area.

ABSTRACT. Motorized Two Wheelers are one of the most popular forms of transportation in developing countries. They exhibit a variety of distinct maneuvers such as travelling with very short headways, riding abreast, filtering through leader vehicles, etc. Filtering is one of the risky riding maneuvers which increase the probability of collision and serious injuries in MTW riders. This study employs the data from real world urban traffic and initially predicts the following/ filtering prediction model based on the conventional Raff's method. Later, a Decision Tree (DT) model is developed to predict the choice and the results are compared to Raff's method. The model accuracy for the latter was found out to be about 80%. Other performance indicators were also calculated to quantify the accuracy of the model, and it was found out that the model performed satisfactorily well in the predictions. A thorough understanding of factors influencing the probability of filtering is essential for a deeper knowledge of the driving behaviour of MTWs, and will be beneficial for a better representation of MTWs in traffic flow models, and for practical applications such as Intelligent Transportation Systems (ITS).

ABSTRACT. Low- and middle-income countries (LMICs) like India have recorded significantly high Motorized-two wheelers (MTW) fatalities compared to other vehicle types. MTW users are considered vulnerable and are prone to severe injury crashes. Helmet (protective headgear) usage has significantly reduced MTW crash severities globally. Statistics indicate more than 37% of the MTW crashes in India are attributed to non-usage of helmets. Therefore, this study aims to identify the factors for helmet non-compliance behavior among Indian MTW users. For this purpose, face-to-face public opinion surveys were conducted in the Mumbai Metropolitan and Pune regions of Maharashtra, India. A comprehensive questionnaire was designed to capture MTW users’ socio-demographic characteristics, MTW riding characteristics, and general perception and attitude toward helmet usage. Analyzing the MTW users’ opinions revealed that extreme weather conditions, cost of helmets, and inconvenience due to helmets (such as hindrance to hearing and peripheral vision) were key factors affecting helmet non-usage. An ordinal logistic regression model developed based on stated preferences survey questions indicates a significant increase in helmet preference with the availability of dedicated helmet storage and law enforcement presence. The study findings can aid in formulating various national and state-level policies to increase helmet compliance behavior among MTW users.

ABSTRACT. In the context of rapid urbanization, the mechanism of human mobility and urban interaction has gradually changed. Previous studies focused on the strength center of urban structure. However, the mechanism of urban structure in the emergence of human mobility changing from micro to macro was ignored. This paper reveals the mechanism of urban structure formation through network modeling and mobility measurement of human movements based on taxi travel data. Firstly, by constructing a complex network of trips and measuring network centrality, the study identifies mobility "attraction centers", passenger flow "distribution centers" and public transportation "potential centers" in the urban ". Secondly, further community segmentation shows that micro individual trips emerge with specific characteristics at the macro scale, and urban sub-structures establish relatively stable connections through internal "attraction centers" such as jobs and recreation. Finally, this paper reveals the socio-economic mechanisms of urban structure formation in the spatial dimension, and initially explores the underlying relationships between human mobility patterns and urban space. The findings of the study have important implications for sustainable urban planning.

ABSTRACT. Low-and-middle income countries (LMICs) continue to suffer the negative consequences of crashes with speed recognized as the main causative factor. The relationship between speed and crash outcome is complex and has been subject to debate. Over the years, how speed affects the outcome of a crash has been investigated and argued to depend on the type of traffic environment which has led to the re-analysis and development of models for different road environments. However, literature neglects the effects of mixed traffic on speed and crashes, and this has raised questions on the applicability of the conventional power and exponential models. This study reviews literature on speed and crashes in mixed traffic, for LMICs, and verifies the applicability of the power models to the context. Study results indicate that speed studies in LMICs are rudimentary and while studies support the positive relationship between speed, speed variance, and crashes, the strength of the relationship is unknown. Literature provides no conclusive evidence on the applicability of the power and exponential models to LMICs roads, and this remains controversial. More research efforts in LMICs should focus on the effects of speed and impact speed on crashes both at aggregated and individual road user levels.

ABSTRACT. Technological advancements in Automated Vehicles (AVs), particularly the integration of diverse stakeholder groups (communication service providers, road operators, automakers, repairers, AV consumers, and the general public), have resulted in the emergence of new technical, legal, and social challenges. The most pressing challenge is deterring cyber-criminal activity by implementing cybersecurity protocols and regulations. The literature lacks a systematic decision tool to dynamically visualise a "macro" understanding of the AVs Cyber Regulatory Framework (CRF) among ITS stakeholders, although individual stakeholders have a good understanding of cybersecurity regulations. To address this knowledge gap, this study employs the Causal Loop Diagram (CLD) to dynamically assess inter-disciplinary Intelligent Transportation System (ITS) stakeholder cyber-regulatory advancements. The CLD envisions "the tragedy of the commons" system archetype, in which ITS stakeholders act in their self-interest to improve cybersecurity, making decisions based on their needs irrespective of the impact on others; on AVs adaptation and long-term consequences on AVs-CRF. The findings suggest that decision-makers should focus on three major leverage points: establishing a CRF grounded on automakers' innovation; sharing risks in eliminating negative externalities associated with underinvestment and knowledge asymmetries in cybersecurity; and capitalizing on massive AV-generated data in AV operations and urban architects.

ABSTRACT. This paper analyzes the effects of intracity and intercity commuting subsidies of two cities, which competes for the residents. A high-income and a low-income city constitute the system, assuming cities can independently develop subsidy strategies. Five subsidy scenarios are considered: (i) and (ii) intracity commuting subsidies unilaterally implemented in two cities, (iii) intercity commuting subsidy unilaterally implemented in the low-income city, (iv) intracity commuting subsidies simultaneously implemented by two cities, and (v) intercity commuting subsidy implemented by the low-income city while intracity commuting subsidy implemented by the high-income city. At the competitive equilibrium, unilateral intracity commuting subsidies lead to population inflows and outflows in the presence and absence of intercity commuters, respectively. The unilateral intercity commuting subsidy gives residents incentives to reside in the low-income city and intercity commute to the high-income city. Competitions do not always benefit the system, but rather act as a damper. Compared with unilateral subsidies, competitions increase and decrease the total social welfare of the system in the presence and absence of intercity commuters, respectively.

ABSTRACT. Residential relocation behaviour is crucial to forecasting travel demand while designing and implementing new road transport infrastructure. However, little is known about people's residential relocation behaviour changed due to transport infrastructure construction. Therefore, this study examined the sociodemographic and travel-related correlates of residential relocation in Bangladesh. An intercept survey and an online questionnaire were conducted to collect data from the participants. Participants' sociodemographic and travel-related variables were examined in a Bivariate analysis. Using a generalized linear mixed logistic model, the study found that flyover users were less likely to move their residence due to increased travel distance and more inclined to relocate due to travel time savings. Higher middle-income people were more likely to change their residential than their counterparts, and those who were employed were more likely to relocate compared to non-working people. Flyover users who had a car were less likely to relocate compared to flyover users who did not own a car. Future studies should consider sociodemographic and travel-related correlates of individuals' residential relocation behaviour in transport infrastructure investment projects (e.g., construction of flyovers) to keep the residential relocation rate at a minimum and to reduce traffic congestion, particularly in Dhaka, Bangladesh.

ABSTRACT. Transit Oriented Development (TOD) is a key mechanism to integrate transport-land use in an efficient way. However, TOD should be context specific to get the full benefit from it. This study tried to look at the spatial potentiality of Dhaka city for successful TOD Planning. Station areas were analyzed from both Node and Place perspective considering their two different roles. Widely used 5D indicators of Cervero coupled with an additional D variable 'developability' were used to measuring future spatial development potential. Following a mix method approach the study identified that despite the spontaneous development pattern Dhaka has good potential to transfigure into TOD. Spatial analysis reveals the current density within the TOD precinct is the most important indices for TOD planning, and the mean value for the developable plots evident room for (re)development. The spatial configuration of street pattern shows higher walkability potential in terms of intersection density in the unplanned areas despite their spontaneous nature of development. Correlation analysis helps to determine which transport and land use factors are responsible for structuring station areas (re)development. Finally, the application of the node-place model depicts the relative positioning of the station in terms of their balance between transport and land use.

ABSTRACT. Bicycle-sharing systems (BSSs) have emerged as an important climate-smart transportation strategy in many cities, supporting sustainable low-carbon societies. This paper investigates usage trends in a bike-sharing scheme that has been in operation in Chennai since 2019. One of the reasons for looking at a city like Chennai is to see if metropolitan cities in developing countries benefit from bike-sharing schemes and if bike-sharing schemes can play a prominent role in these cities, as these cities face many transportation challenges such as congestion, delay, pollution, accidents, and last mile connectivity issues, among others. The study used app data to conduct an exploratory analysis to examine the impact of factors such as temporal, weather, travel characteristics, and bike type (conventional or E-bike) on bike share usage in the city. The model results from this study related to bike-share ride duration (short, medium, and long) can help other cities in developing countries improve and/or expand their existing bike-share networks, as well as cities planning to launch new bike-share programs.

ABSTRACT. Road markings, one of the important traffic ancillary facilities, play a significant role in traffic safety. The installation of road markings inevitably requires a amount of marking paint. However, the visibility and durability of current road marking paints are unable to meet the requirements of the modern development of the transportation industry. Since road marking construction units only focus on whether the initial performance of the marking paint meets the requirements, without considering the mechanism of the paint's performance changes during use, the visibility and durability of the markings decrease rapidly after a time. In this context, based on the optimal formulation scheme of the marking paint, this study prepares paint samples, designs a marking wear test, and combines SEM analysis to investigate the reasons for the decline in the wear resistance and luminance factor of the marking paint. By observing the microscopic morphology of the surface of the marking paint samples at different wear stages, it is concluded that the quality of glass beads themselves and the adhesion between glass beads and surrounding fillers are the main causes of marking paint failure. The obtained failure mechanism provides corresponding experimental plans and results for further development of high-performance coatings.

ABSTRACT. This paper highlights the pressing need for sustainable alternatives to cars in urban mobility. It explores the potential of platform-based mobility services as a viable strategy to transition from cars, analysing the associated incentives and barriers using the Multilevel Perspective (MLP) framework. This analysis uncovers challenges faced by platform-based mobility solutions, including limited user practices, knowledge, infrastructure, and policy support compared to cars. However, it also identifies opportunities for these alternatives stemming from the problems faced by the car regime. Moreover, the study investigates the development of a regulatory framework for platform-based mobility solutions, aiming to promote sustainability and mitigate negative externalities. The analysis focuses on the regulations governing shared dockless micromobility in Los Angeles, providing an experimental setting. This paper introduces a novel approach by evaluating Los Angeles’ micromobility regulations from the perspective of Strategic Niche Management (SNM), an important strategy developed within the sustainability transitions literature to accelerate transitions towards sustainability. The paper emphasizes the importance of effective regulation to guide emerging technologies towards sustainable urban mobility, highlighting the challenges and uncertainties involved. It proposes an experimental setting as a valuable approach for policymakers to acquire knowledge, develop evidence-based regulations, and facilitate a smoother transition process towards sustainability.

ABSTRACT. The city of Lipa in the Philippines is a medium-sized city that is already starting to experience traffic congestion and needs to confront the issue right away and one sure way of getting results is the improvement of its public transportation system. Lipa City is estimated to generate 147,132 daily trips using the multiple classification analysis (MCA) method. More than one-third of the survey respondents picked motor-tricycles as their primary mode of transport, followed closely by nearly 30 percent of respondents using jeepneys. Logit models predicted that tricycles are the predominant mode of transport with a probability of between 35 to 52 percent, followed by jeepneys with a probability of between 15 and 35 percent. These modes of transport may not be able to keep up with the demand in the long run given their limited capacities and are not environmentally friendly. Now is the time to focus on transport studies in secondary cities, such as Lipa City, to address worsening traffic congestion before they too will become similar to what is being experienced now in Metro Manila and Cebu City.

ABSTRACT. Road accidents have become a worldwide issue and have been the subject of several publications and studies. However, the negative effects of traffic accidents are hardly highlighted. In industrialised nations, the death rate due to road accidents is very low and the system to pay victims is relatively strong, but in developing countries, the fatality rate due to road accidents is rather high and the process to compensate victims is pretty pathetic. In light of this, the purpose of this study is to examine the many characteristics that should be utilised to compensate victims of traffic accidents. In this study, specialists from various fields were chosen. It featured specialists on road safety, medicine, rehabilitation centres, economics, sociology, insurance, and trauma centres. These specialists were consulted in order to evaluate the variables of the road accident compensation equation. The approach use the Analytic Hierarchy Process to examine the data and establish the component ranking (AHP). The most essential component to consider, according to the conclusions of this article, is the cost associated with the victims, whereas the least important factor is the cost associated with property damage.

ABSTRACT. Road fatalities are a severe cause of concern for policymakers and administrators in developing countries like India, especially on rural highways. Some of the major causes of these road crashes are poor road design, the geometry of the intersection and lack of traffic calming measures. Road safety audits are essential for road design in the purview of the overall safety of all road users and minimizing road accidents. Black spot identification and its mitigation measures are essential steps to reduce overall road accidents. Black spots are short stretches where accidents/fatalities take place repeatedly. Long-term safety measures for black spots are time-consuming and cost-intensive. This research study aims to verify the efficacy of short-term and cost-effective treatments and mitigation countermeasures on blackspots in the peri-urban road sections of Indian highways. The results of this research study confirm the positive efficacy of short-term measures, which are cost-effective and can be implemented before the implementation of permanent long-term solutions

ABSTRACT. The aim of this study is to present the possibility of apply the analytical Gauss Plume Model (GPM) to determine the dispersion of air pollutants from freight transport, carbon oxides (CO), nitrogen (NOx) and bicarbonates (CH) on two road sections located in Szczecin. The application of the analytical Gaussian Plume Model (GPM) was made for real-time estimation of air pollution dispersion on road sections in a specific agglomeration area using data obtained from traffic detectors. The proposed Gaussian Plume Model (GPM) enables a quick response to exceeding the permissible standards in areas highly exposed to transport pollution.

ABSTRACT. This paper models and analyzes a collective incentive strategy with passenger departure time equilibrium aiming to maximize the total passenger surplus. In the proposed collective incentive strategy, passengers have dynamic off-peak period discounts where the discount value depends on the total number of passengers enrolled in the incentive program. The proposed model considers passengers’ demand elasticity and responses to the strategy and determines the starting time and duration of the collective incentive strategy during the time of the day. We analyze the properties of the proposed collective incentive model to identify the analytical solutions and performance. Analytical results indicate that there exists a threshold demand elasticity below which the total surplus of peak and off-peak commuters can be improved simultaneously. Properties also show that there could exist multiple local optimal solutions of incentive strategy duration for a given starting time. A case study is conducted with a metro system where results indicated that the proposed collective incentive strategy is capable of improving total passenger surplus, increasing off-peak ridership, reducing crowding and congestion and improving transit revenues simultaneously.

ABSTRACT. Passenger cars are the major contributor to urban air pollution in India. Generally, emission factors are developed in a laboratory setting using a standard driving cycle. However, laboratory-based emission tests do not represent real-world emissions. This research quantified the CO, HC, CO2, and NOx emissions for a diesel passenger car using the portable emission measurement system (PEMS) in Sangareddy town, India. A Simple linear regression (SLR) technique was employed in this study to develop the speed-based emission models. The developed SLR models had higher accuracy, as demonstrated by the coefficient of determination (R^2), root-mean-square error (RMSE), and mean absolute percentage error (MAPE) values. In this investigation, emissions rates (CO, HC, CO2, NOx in g/s) increased as speed increased, and the emission rates were particularly high at high speeds (90-100 kmph). The result revealed that emission rates were found to be minimal at an acceleration range between -0.2 to 0.2 m/s2 at a speed range of 30–60 kmph. The observed emission factors (CO, HC, CO2, NOx in g/km) in this study exceeded the Bharat Stage (BS)-IV emissions limits. Analysis of speed and acceleration on tailpipe emissions will help policymakers understand emissions patterns in heterogeneous traffic and frame policies accordingly.

ABSTRACT. Excess levels of crowdedness in the subways during peak hours lead to unsatisfactory riding experience for subway users and raise questions of inefficiency for the management agencies. To address this problem, an innovative off-peak monthly pass subway fare pricing scheme is designed and tested regarding its benefits in incentivizing behavior shifts and easing the congestion during peak hours in the subway system. Based on the idea of time-based differential pricing, a framework is proposed to guide the development of the monthly pass scheme: the framework consists of three steps, including Stated Preference surveys to detect the behavioral responses, behavior models to understand travelers time sensitivity, and an Agent-Based Model simulation to predict the network-level outcomes of the policy. The proposed framework is tested with a case study of Beijing subway Line 5. A baseline scenario with no off-peak monthly pass and two alternative scenarios with monthly passes are tested and compared regarding the policy outcomes. The results demonstrate that the monthly pass can reduce the crowding both in terms of the platform crowdedness and train occupancy during the morning peak period, while also attracting more travelers to use the subway as well.

ABSTRACT. Decarbonization of road transport requires socio-technological system transitions that combine a systemic change in transport infrastructure, technological interventions, and societal change. Non-state actors play a significant role in mitigation, including sub-national and cities. The Provincial Governments of DKI Jakarta, West Java Province, and the city of Semarang as part of the non-state actors seek to develop local strategies in the transport sector to achieve the emission reduction targets. The ambitions, roadmap, and policies are different while the economic and political situations are challenging for developing long-term planning and programs at the city level. Many policymakers focus on technology interventions that easily be implemented in a short period such as fuel switching to biofuel or biodiesel as it could also be synergized with national programs. It gives the largest immediate impact on GHG emission reductions in those three locations while the modal shift to non-motorized transport gives small emissions reductions. Developing renewable energy for the production of electricity could increase GHG emission reductions from the electrification of vehicles, however, it can be implemented only in a certain region. Capacity building and stakeholder engagement is other key important aspect as enablers for the local transformations

ABSTRACT. Globally, vehicular pollution is one of the greatest concerns in urban areas. Several studies on air pollution have been conducted using deterministic, statistical, and soft computing methods. However, there has been little research on how soft-computing methods like Artificial Neural Networks (ANN) can help us comprehend the non-linear and highly complex dispersion of vehicular pollution. This study compares the predictive abilities of the California-based Line Source Dispersion Model (CALINE) and the Artificial Neural Network in terms of PM2.5 concentration. The model has been designed for one of Delhi's busiest traffic intersections, namely the Income Tax Office (ITO) intersection. In the model, PM2.5 pollutant, background pollution, meteorological, road characteristics, and traffic flow have been taken into account as factors. The results reveal that ANN predicts vehicle pollution far more accurately than the CALINE model. The statistical comparison of CALINE and ANN models revealed R-squared values of 0.62 and 0.74, and normalized root mean square values of 0.44 and 0.35, respectively.

ABSTRACT. This study aims at developing four delay models from six different traffic flow and geometric variables using both statistical as well as artificial intelligence-based methods and to classify the level of service for Indian roundabouts. The main objectives of developing these models are to understand the relation between various variables, to find any special structure if present in data and to predict the future trend. The level of service classification is based on the value of average delay per vehicle of the entire roundabout. It was found that among all four modelling methods, non-linear regression model and artificial neural network are giving better results in terms of goodness of fit which is measured by coefficient of determination (R2) value. Weaving width, circulating flow and entry width are variables included in stepwise regression analysis. While circulating flow and entry width are found to be most important variables to predict delay in case non-linear regression analysis. The LOS is classified using k-means clustering technique and result is compared to classification given by HCM 2010 and Indo-HCM 2017. This will enable in designing the roundabouts with better performance as well as in estimating its current efficiency to manage the traffic.

ABSTRACT. Currently, population declination has become a timely concern matter in Japan. While making plans to restore people after the disaster, rapid population migration has become a crucial uncertainty to implement of reconstruction plans. Those uncertainties in reconstruction plans are dependent on the heterogeneity of resident’s preferences. This paper discusses to formulate an effective reconstruction plan for future disasters with consideration of recovery time and incentives as preference classes. Two level optimization model was considered in the model as upper-level policy optimization model and lower-level estimation model. In the model, EM algorithm was considered to classify data to two classes by defining class attribution probabilities and to find the missing annual income values in data sample. The stated- preference (SP) survey, which was conducted around Iekushi, Misaki and Yawatahama areas were used to develop the model. Pareto frontier analysis was considered to find the optimum patterns for incentives and recovery times. As per incentives and recovery time allocations of cities, results are revealed that there are significant heterogeneities in residential choices as per recovery time and incentives on residents’ location choice decisions.

ABSTRACT. In sub-Saharan Africa (SSA), motorcycles are playing a major role in daily mobility and access to the city, as well as in the local economy, with the explosion of motorcycle taxi services and the development of personal motorcycles. The motorcycle is the main alternative to conventional public transport. The number of households owning a personal motorcycle is increasing, whereas motorcycle taxi services are developing fast. The aim of this paper is twofold i) to present an overview of the spread of motorbikes in SSA and their use, ii) to discuss two major public health issue linked to this boom: the increase in road accidents and the contribution to growing air pollution. Data are scarce on motorcycle equipment and use in SSA. In order to address this lack of statistical data, we selected two datasets: DHS Survey results to provide information on household motorcycle ownership rates across sub-Saharan Africa and microdata from a household mobility survey (Dakar, Senegal) and from a survey of transport users (Lomé, Togo) to characterize the uses of motorcycles. The numerous environmental and public health issues raised by the rapid growth in the usages of motorcycles call for real improvements in the public regulation in SSA cities.

ABSTRACT. This paper examines the impact of total real trade (sum of import and export), real gross domestic product, real effective exchange rate, and foreign direct investment inflows on international air passenger travel demand in Nigeria using annual data from 1982 to 2019. Autoregressive distributed lag approach was employed to analyze short- and long-run relationships between the variables while Granger causality test was conducted to determine the direction of causality. Total real trade and economic growth are major factors positively influencing demand for international air travel to and from Nigeria in the short- and long-run. Contrary to findings in the literature, foreign direct investment inflows impact air travel negatively in the long-run but has a positive effect in the short-run with 1-3year lags. Real exchange rate is found to reduce air travel demand in the short-run. The result indicate a bidirectional Granger causality between international air passenger travel and total real trade, and between air travel and economic growth. Government, policymakers, airlines and airports need to implement strategies and provide infrastructure that will support increase in demand for international air passenger travel due to economic growth.

ABSTRACT. The COVID-19 virus caused a sudden decline in air cargo supply, resulting in a steep increase of air cargo rates worldwide. This phenomenon resulted in rising interest from the industry and academics towards air cargo research. Unlike air cargo demand, air cargo supply has been lesser studied in academic research. This study conducts a narrative literature review on the complexity of determining and calculating air cargo capacity on a global level. First, airlines’ flight scheduling planning, which determines an airline’s network, is reviewed. Second, the complexity of making aircraft payload calculations is discussed. Finally, the networks and aircraft payloads are combined to form the market supply. The study’s objective is to better understand the air cargo supply side and its problems and form a base for future research on the air cargo market, including demand and supply.

ABSTRACT. This study aims to identify potential direct route between Taiwan and the US by analysing the indirect traffic through other transit airports. Two composite indexes referred to as the Passenger Transfer Dependency Index (PTDI) and Passenger Transfer Dependency Degree (PTDD) are developed to analyze passengers’ transfer dependency on other hubs and the routes that they dependent. The research results indicate that transit traffic is mainly concentrated in HKG followed by NRT and ICN Airport. After the cost-benefit analysis, this research suggested that national carriers like China airlines (CI), EVA airways (BR) and STARLUX Airlines (JX) can launch or increase the number of flights to Los Angeles and New York, other destinations like Boston, Newark and Washington should be added to Taoyuan International Airport (TPE) service destinations. This research can help airports and airlines improve their aviation network. The results could help airports to identify their market position and from there encourage airlines to plan the development of new routes.

ABSTRACT. Airlines operate hub-and-spoke networks for passengers and freight transport. The advantage of the hub-and-spoke structure is its efficiency for operating large networks by maximizing the number of destinations, besides achieving regional market dominance as well as economies of scale, scope, and density. Despite the potential, Africa is the most extreme example of the complexities of sparse and underdeveloped airlines. A few powerful nodes dominate sparse markets. Africa's connectivity score, ranking, and aircraft movements are the lowest of all regions.

The research applies a multiple case study approach to identify and analyse the key success factors of top-performing airlines for improving air connectivity to be adopted by African airlines from a passenger and cargo perspective.

The paper concludes that varying resources and activities through partnerships, multi-hub strategy, and intermodality at airports are the key success factors for better air connectivity. African airlines must be aligned with the air industry’s best practices to improve air connectivity and performance..

ABSTRACT. Regional airports are facing various challenges some of which must be tackled to ensure a sustainable future where they can embrace upcoming opportunities. Those challenges, with the financial viability problem in the lead, are analyzed, structured, and discussed based on a literature review of 43 papers and books. The importance and interaction between the concrete challenges are explained in more detail. Generally, we can conclude that regional airports are facing challenges dividable into four categories: the market dynamics, the financials, the politics, and the geographic location of the regional airport. To illustrate the challenges in practice, the case of the airport of Antwerp (EBAW) and the airport of Ostend-Bruges (EBOS) in Flanders, Belgium, is investigated. The case study allows us to verify the difficulty of the situation in Flanders, which challenges cause major and minor effects, and whether any challenges are missing from the current literature.

ABSTRACT. This study computes the air connectivity of 16 airports in the Yangtze River Delta (YRD) region and identifies the possible driving forces over the period of 2008-2018. Based on the regional characteristics of civil aviation in the YRD, three discount factors are added to the connectivity model including the capacity, delay, and velocity discounts. The results show that the macro condition of cities such as population and GDP, own condition of airports such as runway length and the number of gates, and airline competition measured by Herfindahl-Hirschman Index (HHI) have significantly positive effects on airport overall connectivity. The presence of low-cost carriers is conducive to air overall connectivity, while it has a negative effect on the international connectivity of airports. Keeping competitive on common routes among the adjacent airports is likely to promote domestic connectivity while developing new routes significantly affects international air connectivity. In addition, promoting competition among hub airports can increase air connectivity, highways, and HSR within the YRD region can also facilitate the integration and distribution of aviation resources. They play an important role in inter-airport competitions and cooperation. This study can help to provide theoretical basis and data support for differentiated development of YRD region airports.

ABSTRACT. The rise of global maritime trade facilitates the use of ports which serves as an important interface for transferring goods and services across different borders. However, ports are becoming increasingly vulnerable to the effects of climate change, which cannot be ignored. Adverse weather conditions, such as Windstorm, Extreme High Temperature, and Storm Surge, pose a significant risk to these ports, highlighting the urgent need for action to mitigate their impact. The Port of Felixstowe (PoF) has historically been the largest container port in the United Kingdom (UK). This paper presents a simulation model for PoF that integrates the complex nature of port operations and, more importantly, analyses for disruption scenarios developed based on future climate change projections in the UK. Additionally, this paper presents a port risk assessment analysis to quantify the impact between disruption scenarios. This paper serves to offer port stakeholders greater awareness of climate change-related disruption events and the understanding of quantified impacts to operational performance for action.

ABSTRACT. There is a growing need for seaports to find ways to reduce air pollution they generate. A wide range of potential best practices exist, but what lies behind the decision to actually implement them? Our study aims to answer the research question by a literature review. The study examines research articles on reduction measures to determine the incentives why they are implemented by seaports or the barriers that impede the implementation. For this purpose, the authors conduct a literature search and a qualitative content analysis. Understanding barriers as well as driving factors, helps scientists as a basis for further research on the interdependencies of influencing factors, as well as experts and stakeholders in developing suitable emission reduction strategies for citizens living and working in and around seaports.

ABSTRACT. This paper aims to evaluate whether environmental port pricing strategies on vessel operators, through port dues discounts, impact traffic in European ports. Although price discounts at ports have the clear purpose of reducing air emissions, the role of the strategies on port traffic volumes amid fierce competition remains to be determined. Through a panel data analysis, this paper estimates an equation for traffic demand in 56 European ports from 2005 to 2021. This research suggests that environmental port dues rebates, through maritime environmental performance indices, can be associated with higher traffic volumes so that these environmental port initiatives can act as a competitiveness factor among European ports.

ABSTRACT. Hydrogen’s potential is currently attracting a lot of attention. It is a crucial link in the energy transition toward a climate-neutral future. Hydrogen serves as a fuel, a resource for chemical industries, and an energy carrier that must be produced before it can be applied. Hydrogen produced from sun or wind is climate neutral. The advantages of using hydrogen in the transport sector include zero-emissions and, compared to battery technologies, a large range and long operating time and short refueling time. The disadvantages include the fact that the technology has not yet been fully developed, the high costs of the technology and of hydrogen production and use, and its low energy efficiency. Various policy initiatives aim to achieve a transition in which ports might play a crucial role. Because of ports’ location and existing activities around petrochemical clusters, they have not only a sales and user market, but also an extensive import, export, and distribution infrastructure. The successful introduction of hydrogen depends not only on technology (techware) but also on the priority given to organizational aspects (orgware). This is not a simple challenge, as orgware has its own complexities to overcome.