ABSTRACT. The existence of an analytical relationship connecting departure delay and resulting en-route conflicts remains a significant gap in the air transportation literature. This paper proposes a framework to estimate conflict probability and the number of conflicts based on departure delay. To get a conflict probability expression, we propose a binomial logistic regression model with conflict status (Conflict or No Conflict) at a waypoint as the dependent variable. The independent variables are departure delay and the number of waypoints crossed since take-off. Using the conflict probability expression, we then calculate the expected number of conflicts at any waypoint. Data required to estimate the model parameters is collected through Flight Data Processing System at the Advanced Air Traffic Services located at Anna International Airport, Chennai, India. Results indicate that the observed number of conflicts detected matches closely with the expected number of conflicts for a delayed aircraft on its route. The overall framework is also flexible and provides sufficient generalizability to accommodate multi-airport delays. The proposed relationship, if included in the system-level delay management strategies, can augment the performance and safety of the air transportation system.

ABSTRACT. In this paper, we aim to capture the dynamic change in runway capacity over short time intervals (such as 15 minutes). we first propose the idea of adopting stochastic frontier analysis to estimate runway capacity, which provides a statistically stochastic estimation with less cost. We further apply a novel endogenous stochastic frontier analysis (endogenous SFA) to address the endogeneity due to either the correlation between frontier variables (such as wide rate and arrival rate) and omitted factors that also determine runway capacity but are explained in random error (such as air traffic control), the correlation between environmental factors (such as delay) and omitted factors, or both. Simulation results show this endogenous SFA handles endogeneity properly and provides unbiased estimates for the factors determining runway capacity and runway capacity. The results based on real data from three airports indicate that significant endogeneities for wide rate, arrival rate, and delay are detected. When endogeneities are controlled for, the arrival rate has a smaller negative impact on runway capacity, the wide rate shows a larger negative effect on runway capacity, and the positive effect of delay on inefficiency displays a downward trend. We find that the exogenous model substantially overestimates the runway capacity.

ABSTRACT. At a number of European airports, massive flight delays, lost luggage and other irregularities were recorded during the 2022 summer period. Key reasons for these developments are staff cuts during the COVID-19 pandemic followed by a fairly strong recovery in the aviation sector in 2022 and resulting staff shortages. However, stakeholders at some airports (e.g. in Southern Germany) appear to have managed these problems better than elsewhere. Delays and other irregularities in air transport cause economic damage for different stakeholders, including airport operators, airlines, the (federal) police, ground-handling and security service companies, as well as the travelers themselves. This paper evaluates key causes for, and economic effects of the observed developments, followed by recommendations to improve future delay situations. First, existing literature is analyzed and interviews with available stakeholders are conducted in order to assess how the stakeholders cooperate at airports, and why delays and other irregularities have occurred. In a second step, available data is used to illustrate the delay situation in the summer of 2022. After this, value of time impact is estimated for flight passengers based on a sample of routes from three German airports to Palma de Mallorca. The paper closes with recommendations for improvement.

ABSTRACT. Within the new amended proposal for the SES, the EC further stresses its ambition to unbundle terminal from en-route ATC to introduce competition for the market. This research assesses whether ANSPs would lose potential scope economies or not. Previous research estimated cost complementarities from a translog specification. Some of the estimated models resulted in positive complementarities, others in negative, meaning that no clear conclusion could be taken. However, such knowledge will be crucial to motivate an unbundling policy. Insight into the existence of scope economies between both services can help ANSPs decide on their future strategies in a continuously further liberalised ANS market.

In this paper, a multiproduct quadratic cost frontier is estimated from data from the EUROCONTROL ACE Benchmarking reports. As opposed to the commonly used translog, the quadratic functional form allows interferences on economies of scope. Preliminary results suggest that European ANSPs might not be benefitting from scope economies in exploiting both en-route and terminal ANS.

ABSTRACT. Airports influence the way we plan our cities. This is mainly due to their physical size, their functions, and the different impacts they have. Despite this evidence, there are few studies that address this issue, with much of the research focusing on the study of environmental and economic impacts, without considering the impact of airports on urban planning. In this paper, we propose to analyze this influence, through the relationship between planning instruments with Amsterdam Schiphol Airport and its main corridors. To this end, we seek to understand the influence of the airport on spatial planning in the Amsterdam Metropolitan Area and the Randstad Region. To conduct this work, we conduct a literature review and analyze Dutch planning instruments as well as Dutch legislation. The cartography serves to illustrate the distribution of the main road and rail corridors. The results show that the airport is integrated into the planning instruments, assuming an important centrality in the Dutch transport system. This relationship of the airport with the territory has also contributed to transform it and to implement policies to safeguard the airport and the territory itself, with land use policies articulated between operators and policymakers.

ABSTRACT. The fully integrated multimodal door-to-door trip, with the air transportation as the main leg, requires many aspects to be considered both from passengers and transportation authorities’ perspective. Therefore, we conducted an online survey in Europe by collecting more than 2000 questionnaires, from which we acquired inputs related to the passengers’ attitude and motives for selecting airport access travel mode choice. Based on the mobility profile of participants, we performed Fuzzy C-means (FCM) clustering for determining the clusters of the respondents with similar characteristics related to the travel attributes and mode choice preferences. We validated the results by comparing the clusters obtained by FCM and k-means clustering algorithm. The results of the cluster analysis showed the preference of travel mode choice, i.e., car being the most preferred mode choice among different age groups. Also, the highest number of participants in the clusters rated the factors waiting time, travel costs, and travel time as important, while the factor reliability was rated as most important when making the mode choice. Consequently, obtained results and the importance of reliability could be considered as a useful indication for transportation authorities for improving the multimodal service and fostering the shifting from private to public transportation modes.

ABSTRACT. In 2020, Indian Railways took up a de novo timetabling exercise for the Golden Quadrilateral and Diagonals (GQD) connecting Mumbai-Delhi-Kolkata-Chennai, involving about 1700 trains on a weekly basis over a network of 9,099 km. Based on significant participation in this activity, this paper elaborates on the challenges faced in a network-wide simulation and scheduling of trains across a large network. The methods to address these challenges and the software implementation aspects are also described. A network-wide mixed-rail traffic simulator was used successfully to construct a daily timetable for the GQD. The two primary goals of the Zero Based Timetabling (ZBTT) project were to generate train schedules that were: (a) feasible (in terms of kinematic constraints on both trains running and block-section, running lines) and (b) conflict-free (due to multiple trains having to share resources and the need to ensure time-durations of resource usage are different, subject to safety constraints), for a proposed set of departure timings and halt patterns of all the services that were planned on the GQD.

ABSTRACT. Many freight trains are still diesel-powered, and their emission cannot be ignored. This research proposed a framework to evaluate the path inefficiency due to stops in the middle of their journeys and the associated emission from idling and reacceleration. The framework includes Number of stops, Stopping time, Stopping percentage, and was applied to integrated datasets from January to June 2022 in Great Britain. Each diesel freight train made on average 1.34 stops, with an average summed stopping times of 17.2 minutes and a stopping percentage of 6.89%. It was estimated that in that 6-month period, 53.1 ktonnes of CO2 were emitted. Domestic intermodal accounted for 60% of total emissions. Early or late departure at the origin from the scheduled time may have affected journey time but have not increased emission greatly. This framework could be used in the evaluation of railway timetables and operation management at the national level.

ABSTRACT. This study investigates a rolling stock scheduling problem on a metro line with multiple depots. An arc-based network-flow model is formulated with the aim of improving the service level and reducing the operation cost simultaneously, in which the flexible train composition mode is also taken into consideration to well match the transport capacity and time-varying passenger demand. To solve the proposed models, an exact branch-and-price (B&P) approach is designed to find the optimal operation schemes, in which column generation is used to solve the relaxed master problem at each node of the searching tree, where a dynamic programming approach is embedded to solve the pricing subproblem to generate promising paths (columns) for each rolling stock, and then the branch and bound (B&B) procedure is incorporated to find integral solutions. To test the performance of the proposed approaches, a series of numerical experiments are conducted on illustrative cases with different passenger demand distribution patterns. The computational results verify the improved operational efficiency and better service level of the optimal solutions found by our proposed approaches.

ABSTRACT. A typical rail-network has a combination of daily trains and non-daily trains that have a weekly-pattern. Being non-daily, such trains run sporadically across the week and thus create the problem of inefficient timetabling. Further, for large rail-networks, the timetabling is often done decentrally zone-wise without explicitly ensuring that groups of non-daily trains have similar running times on the bottleneck sections. In this paper, we use a notion of ‘dailyzing’ (making a daily path of non-daily trains) by performing a modulo 24 hours operation and then using Hierarchical Agglomerative Clustering (amongst other techniques) to group the trains. These clusters of trains share the same railway resources almost simultaneously but on different days of the week. Thus the scheduling of one representative train of the cluster as a ‘daily train’ would automatically schedule non-daily ones in that group. Hence, the daily path for non-daily trains provides a systematic and more efficient way of timetabling. The clustering/grouping of trains can also help find an empty slot for a new train scheduling/addition or help in pointing towards resource under-utilization.

ABSTRACT. Data envelopment analysis (DEA) has been widely used for analyzing the safety of different modes of transportation. Its recent applications for level crossings have been successful to compare countries according to the safety of their level crossings or comparing relative safety of level crossings. This paper provides the most comprehensive DEA model which can assess the relative safety of level crossings by considering daily train traffic, daily vehicle traffic, number of railway tracks, number of road lanes, maximum speed of trains and road vehicles, the number of accidents, injuries and fatalities in the past. The model is used for the case study of all level crossings in Canada and is followed up by two Tobit regression models to investigate the impact of region and protection type. The proposed method can help railway policymakers and practitioners worldwide in ranking the safety of level crossings, prioritizing improvements, comparing different regions and achieving an overall decrease of accidents and fatalities at critical points.

ABSTRACT. Human factors play a huge role in road traffic safety. Research has found that a huge proportion of traffic crashes occur due to some form of human error. Improving road user behavior has been the major strategy that has been emphasized for improving road traffic safety. Meanwhile, despite the training efforts, and testing for drivers, the global status of road traffic safety is alarming. In the aim to turn the tide around in improving road traffic safety, there is a need to pay adequate attention to factors that can help minimize the impact of human error, or at least ensure that implications of human error do not result in undesirable consequences on the road. This study evaluates how factors such as driver distraction, fatigue, driving under the influence of drugs and alcohol, and outside objects affect the driver. The need for a reasonable degree of automation to help reduce the impacts of human factors on road safety and recommendations aimed at providing widespread support for a reasonable degree of automation systems in driving tasks is presented.

ABSTRACT. The objectives of the study are twofold: (a) to analyze geometric design consistency (GDC) for heterogeneous traffic conditions, especially on two-lane rural highways, and (b) to modify GDC criteria and correlate them to field-reported crash severity. Considering the study objectives, two study sites one is National Highway 953 (S-1, hilly terrain) and second is National Highway 56 (S-2, rolling terrain), have variable roadway conditions were selected. Forty-six performance box (P-Box) runs were collected for cars and heavy commercial vehicles (HCV) on selected 57 curves for speed data collection. After that, the GDC was analyzed using the available design consistency criteria as the difference between operating and design speed. The GDC results indicate that the percentages of good, fair, and poor for the S-1 study site are 45%, 35%, and 20%, and for the S-2 study site, they are 80%, 20%, and 0%, respectively. In addition, the S-1 study site (64% cars and 40% HCV) and the S-2 study site (65% cars and 0% HCV) moved higher than the design speed. Afterward, the modified GDC results were correlated with the crash severity. Later, some modification is made to establish an accurate relationship between GDC results and their correlation with crash severity.

ABSTRACT. The use of Advanced Driver Assistance Systems (ADAS) to enhance the safety of vehicle occupants and other road users has increased recently. However, most vehicle users are not very familiar with the system. Therefore, the identification of factors affecting the user acceptance of ADAS technologies is important from a road safety point of view as well as the vehicle manufacturers. The present systematic review focuses on the user acceptance factors identified by several studies along with the methods used. The PRISMA flow strategy is used for the present review. Thirteen studies are selected after filtering the existing studies through a Systematic Classification Scheme (SCS) and thirteen user acceptance factors for ADAS technology are identified. Conventional technology acceptance models and/or behavioral models are commonly used to identify user acceptance of ADAS technologies. Some of the significant factors were included in existing models. Hence the importance of developing a specific user acceptance model for ADAS technology is highlighted in the study. The factors identified will be helpful for future researchers to focus on the influence of each factor on various available ADAS features. Vehicle manufacturers can also consider these factors for their future vehicle designs to enhance user awareness and acceptance.

ABSTRACT. Powered Two-Wheelers (PTWs) have significantly gained momentum in developing countries, specifically Latin American cities, due to their ease of use and inexpensive nature. Motorcyclists are vulnerable road users who heighten their risk when practicing illegal actions such as red-light violations, maneuvering, and driving in undesignated lanes. This research provides a video-based surrogate safety methodology into the behavioral aspects of PTW users within Mexico City, Mexico, and São Paulo, Brazil. Two signalized and two unsignalized intersections in each of the cities were selected, and hundreds of hours of video data were collected from on-site installed cameras and processed in automated software. Statistical models and comparative analyses between the cities were generated to measure motorcyclist behaviors according to a set of identified factors. Preliminary results show that helmet use is high, with 97.8% and 98.7% percentages incurred in Mexico and Brazil, respectively. Mexico City motorcyclists are 2.2 times more likely than those in São Paulo to perform risker activities. Regardless, riders in São Paulo pose a significant proportion in committing road safety violations (maneuvering) as 37.25% of motorcyclists consistently change lanes. These behavioral attributes allow for further research to address experimental mitigating actions that lessen the consequences of risky motorcycle travel.

ABSTRACT. The study utilizes the theory of planned behavior (TPB) to explore how drivers intention to violate traffic norms are associated with their actual driving behavior. Further, the study extends the existing theory of planned behavior by including the addition factors of opportunity (lack of enforcement) and motivation (time pressure (schedule adherence, personal time), sensation seeking). In addition, drivers were categorised into two categories based on their intention to commit violation using K-means clustering i.e. low and high intention drivers. The findings indicates that for both sub-groups, driver’s intentions has significant positive relationship with their actual speeding and red-light violations. Further, it was observed that driver’s intentions to commit traffic violation depends on their behavioral belief toward the behavior (attitude), driver’s belief about how often other road users are committing these behaviors (descriptive norms) and drivers perception about their capability to perform these behavior (perceived behavioral control). Moreover, it was observed that the existing relationship between intention and actual behavior is strengthened when there exist higher opportunity and motivation to carry out these behaviors. Based on the findings, the study suggests various interventions aimed towards reducing the speeding and red-light violations among drivers.

ABSTRACT. The research in this paper seeks to quantify the potential of a novel initiative to mitigate “panic buying” through appeals from “trusted change agents” (TCAs) that ask individuals to limit their purchases of basic supplies. TCAs are agents involved in disaster response efforts, such as local leaders and representatives of relief groups, that are deemed to be trustworthy by the various segments of the population. To assess the effectiveness of these appeals, the authors surveyed residents in the United States (U.S.) to characterize the respondents’ purchases of basic supplies during the pandemic. The results of the survey were used to: (i) assess the level of trust the respondents have in the various agents considered; (ii) estimate the expected impacts of TCAs’ requests in terms of changes in respondents’ purchasing behaviors; and (iii) estimate a Multiple Indicators Multiple Causes (MIMIC) model that expresses the respondents’ willingness to limit purchases as a function of the socioeconomic attributes of the respondents. Among the results, it was found that Firefighters and Responders were the most trusted agents during the COVID-19 pandemic; and individuals with more life experiences, such as those widowed, were more willing to limit purchases.

ABSTRACT. The supply chain plays an essential role in the competition between companies. Supplier selection is of great importance considering the influence on the quality of the final product, the return rate, the price of the product, and the sustainability of the whole supply chain. Moreover, the real world is facing much uncertainty. In this uncertain environment, applying fuzzy decision support systems is promising. The main objective of this study is to develop an optimization model to choose suppliers and determine the number of orders for perishable protein products in uncertain conditions in a retail store. A fully fuzzy multi-objective model for a retailer company's closed-loop supply chain is developed to minimize costs and waste and maximize profit, customer satisfaction, quality, and margin under uncertainty. The proposed model is applied in a real case study of Iranian retail stores for protein products. The results proved the potential of the proposed model to improve the closed-loop supply chain’s sustainability performance.

ABSTRACT. Trade credit is extended by suppliers to buyers who often have easier access to external financing, while buyers may delay paying their suppliers beyond the agreed due date. Using a game-theoretic model, we analyze the total financing cost of the supply chain under endogenous supply contract and working capital policies. The embedded stretching option of trade credit allows supply chain partners to pool their liquidity buffers. Due to this pooling effect, even if the supplier's financing rates are strictly higher than the buyer's, the buyer may still demand trade credit from the supplier in order to lower the total financing cost and improve the supply chain efficiency. The model reveals that trade credit is more efficient than cash on delivery when the supplier's cost for collecting trade credit is low or when the supplier does not have access to a low-cost financing channel. This pooling effect also dictates that variabilities of firms' liquidity shocks have asymmetric impact on the efficiency of trade credit: while trade credit can only be more efficient than cash on delivery when the supplier's liquidity shock has a sufficiently large variability, it could benefit the supply chain even when the buyer's liquidity shock is deterministic.

ABSTRACT. The objective of this paper is to identify, describe, and discuss the literature surrounding the interconnectedness of risk and any existing literature surrounding the way that multiple risks can compound to create larger disruptive events within supply chains. Numerous research studies on singular risk events have been conducted, which aim to explain those individual risks’ effects on the supply chain. Existing research is mostly siloed in scope, overlooking a gap in research surrounding the compounding effects that multiple risks can have on an event, and the systemic and compounding propagation of multiple risks across the multi-tiered structure of modern supply chains. The findings of this paper demonstrate an incommensurate focus of existing literature on singular risk events, and a lack of research focus on the interconnectedness of risk and the compounding effects that multiple risks can have on a disruptive event.

ABSTRACT. Digital transformation is a foundational change in how firms operate and deliver value to customers by using digital technologies in creating new business opportunities. The purpose of this study is to offer a conceptual framework by reorganizing the elements of digital transformation, including resources, technology, capabilities, and performance, into a workable process and investigate how firms integrate these resources, build new capabilities, and transform them into the enhanced performance. This framework is aimed to understand the process of digital transformation and its antecedents of firms’ performance in the business environments. It builds three blocks: resource integration, organizational capabilities, and outcomes, exploring the impact of resources integration on outcomes through organizational capabilities. For the resource integration, this study adopts resource-based view (RBV) and service-dominant logic (SDL) to integrate the organizational resources including IT-based resources which plays a role in moderating the effect of resource integration. Moreover, we argue that firms’ capabilities have two levels: higher-order capabilities and lower-order capabilities which will convert these resources through the capabilities into the organizational performance.

ABSTRACT. In this paper, a conceptional two-stage approach for decentralized coordination of platoons using deep reinforcement learning is developed. For this purpose, the relevant existing approaches for the decentralized and centralized coordination of platoons are identified first with the help of a systematic literature review. Then the advantages and disadvantages of the different approaches are analyzed, and the most important results are described. Derived from the findings, a conceptional two-stage approach is developed, which consists of a dispositive and operational level. At the dispositive level, the individual vehicle routing of a trucking company is performed. All feasible routes between the origin and destination nodes under consideration of time window restrictions have to be identified first. The truck then decides at the operational level, based on changing environmental parameters, which tour to choose and whether or not to form a platoon. With the help of decentralized coordination of platoons, it will thus be possible to achieve a cost optimum for platoon-capable trucks.

ABSTRACT. Based on supply chain theory and to compose, as well as expand knowledge about conflict of interest on logistics, the study is aimed to create policy recommendations on logistics distribution to support regional connectivity and economy. The study applies Location Quotient Analysis (LQ), Spatial Analysis (GIS) and Sensitivity Analysis analytical tools. The variables are related to the logistics support facilities and infrastructure availability in each region. The analysis focuses on logistics distribution for commodities that are not time-sensitive. The correlation between distribution patterns and spatial policies has implications for the logistics costs charged to users. Spatial design in Indonesia, which mostly brings logistics facilities closer to the road network, causes high use of road-based freight transportation modes and results in the risk of double handling and high logistics costs (around 24% of national GDP). This research proves the hub and spoke concept will provide a shift in the modal share in logistics distribution activities. The shifting mode is more concentrated on the allocation of hub-to-hub trips to minimize the dominant existing conditions using road-based freight transportation. This must be supported by the application of incentives and disincentives to ensure the achievement of shifting targets and the reduction of logistic cost.

ABSTRACT. The emergence of ICT and ITS in recent times has created interest among practitioners to improve transport operations by the use of information created by such systems. But the implementation and efficient application of ITS in practice to improve transport operations often require contributions from inter-organizational actors in a collaborative setting. Stakeholders in these kind of collaboration settings come together to create business value (improved transport operations) and co-evolve in a dynamic environment leading to the formation of a transport ITS ecosystem. For successful value creation and capture, it is not only critical for stakeholders to have a clear understanding of the roles, activities involved in value chains but also consider the changes in their business models and the dynamic inter-dependencies among partners. This article contributes to literature by developing a conceptual framework to depict the value creation through application of ITS in improving freight operations. For this purpose, we apply the concepts of case research and theory building research to use the existing data-to-value chains in the literature to apply and adapt to the context of freight logistics. The three research pilots of the FTMaaS project from freight logistics sector are used for creation and validation of the framework.

ABSTRACT. Addressing the increase in long distance freight transport demand in a sustainable manner requires a shift to intermodal freight transport (IFT). Efficiency of IFTs plays an important role in this modal shift, which depends on seamless connection, coordination and interoperability of all modes and components of the system, amongst others.An important enabler of this interoperability is the ability of sub-systems to share real-time information with each other seamlessly.This paper presents a multi-layer modelling framework where the interdependancy between various systems is modeled using Discrete Events Simulation. The data-sharing aspects have been addressed using the common data platform developed in the Sift2Rail European Program. The framework is applied to real-time integration of node and network operations at railway yards. As a result of this integration, node operations can be re-planned considering the updated network state, resulting in efficient utilization of existing resources at nodes. This modular framework enables implementation of current internet-based common management platforms and e-freight solutions targeting interoperability and intermodality through corridor-based multimodal transport management systems.

ABSTRACT. The purpose of this study is to design, implement, install and examine how a Bluetooth low energy (BLE) beacon system can be applied in a seaport terminal to evaluate effective access management. The examination and evaluation are conducted through a developed evaluation framework dealing with internal and external effects. The internal effects focus on how well the BLE beacon system can measure total truck turnaround times (TTTTs), and the external on how the system can perform detail before-and-after analysis of the TTTTs to evaluate effective access management. 298 TTTTs are measured together with observations, six interviews and three focus groups meetings. The BLE beacon system measures 44% of the TTTTs in more detail, is faster and more cost effective to implement as well as more flexible with equal accuracy compared to the existing terminal system. However, to increase the productivity the BLE beacon system needs to address identified problems such as inactivation of the system, speed limit for Bluetooth pairing and interfering problems between beacons. Such BLE beacon system to evaluate effective access management has not (to the best knowledge of the authors) been conducted before in seaport terminals.

ABSTRACT. Parking in dense urban cities is a major challenge for last mile logistics. Inadequate parking supply and policies that do not distinguish freight vehicles’ needs often lead freight vehicles to park illegally. This paper conducts a scoping review of relevant literature to identify the parking behaviours of commercial freight and service vehicles, methods used to model these behaviours, and factors that determine their outcomes. The review is undertaken per PRISMA-ScR guidelines. A total of 5,951 unique records were identified, of which 105 passed the title and abstract screening, and 26 were eligible to be included in this review. Commercial vehicles’ parking behaviours mainly comprise parking location and type choices, parking duration, illegal parking, as well as parking cruising and search time. Methods to study these behaviours include discrete-choice modelling, regression analysis, survival analysis and simulation. Parking policies can be categorized into space and time management, pricing, and enforcement. We present literature gaps and provide insights on future research opportunities in the areas of modelling complex decision-making structures, investigating parking cruising of commercial vehicles, and evaluating the implications of freight demand management.

ABSTRACT. This paper investigates the effect of spatial and locational characteristics of establishments on freight (trip) attraction (FA/FTA) models. The authors estimated econometric models of FA and FTA as a function of the establishment attributes as well as the spatial and locational determinant variables, using establishment-level data collected from Addis Ababa City, Ethiopia. The interconnected issues of spatial dependency and spatial heterogeneity together with nonlinear functional specifications were incorporated with the application of spatial techniques, including spatial error models (SEM), spatial autoregressive model (SAR), geographically weighted regression (GWR), multiscale-GWR (MGWR), and the combination GWR-SAR/MGWR-SAR. Regarding the explanatory variables, the empirical results revealed that firms in the manufacturing, wholesale and retail industry sectors that are located on the wider streets tend to receive more FA and FTA. The closeness to the primary road network and the city entry gate influences the FTA of manufacturing and construction firms. Moreover, retail establishments located near the major market receive more tonnage. The models also confirm that FA and FTA are the results of two different processes. Generally, the use of spatial regression techniques improves the accuracy of both FA and FTA models. Especially, MGWR-SAR exhibits superior performance by jointly addressing spatial dependency and spatial heterogeneity.

ABSTRACT. The knowledge of the characteristics of a commercial area allows a better understanding of its urban freight trips. In developing countries, many commercial areas have informal trade. Informal trade has not been considered either for freight trip attraction estimation or for initiatives implementation, despite it could attract freight trips and block streets and sidewalks. This paper aims to estimate and compare freight trip attraction with and without considering informal establishments, to get an initial impact of informal trade in commercial areas of developing countries. The comparison is made considering two supply situations, the first one considers that formal and informal trade share suppliers and the second considers that formal and informal trade have different suppliers. The results indicate that informal trade must be considered in freight trip attraction in an area estimate depending on the amount of informal trade presence in a commercial area, since it impacts freight trip attraction in an area estimates according to it. Also, the supply form of informal trade in the commercial areas must be considered such as sharing or not of suppliers with formal trade, which impacts directly the trips attracted due to the additional trips made exclusively for informal trade.

ABSTRACT. This paper explores the relationship between accessibility and agricultural production through a strategic freight transport model based on product analysis. Three accessibility indicators entering the freight generation model are tested. The temporal accessibility index is the best-performing accessibility measure for the case study conducted in Colombia. The models exhibit that accessibility positively affects freight generation, proving a solid link between temporal accessibility and agricultural production. When using the models to predict the impact of new transport infrastructure projects, changes in agricultural production were not highly significant.

ABSTRACT. Rapid urbanisation and accelerating population have increased the demand and the level of consumption of goods in the urban area. However, providing the required goods and services to the people imposes negative externalities in urban areas, such as air pollution, congestion on the streets and traffic accidents. The focus should be paid to lowering the negative externalities and making this process more efficient and sustainable in the context of urban freight transportation. This study aims to understand the occurrence of the movement of goods. We carried out Establishment Based Freight Survey using in-person interviews of owner/managers/employees of establishments. EBFS has been performed to know the establishment-related characteristics and identify the factors that affect the amount of incoming and outgoing freight associated with the establishments. For this study, we have selected Fast-Moving Consumer Goods segment to carry out the work. Freight Generation and Freight Trip Generation of establishments have been modelled using various establishment characteristics such as number of employees, gross floor area, years in business, operational hours of the establishment and number of LCV trips. Freight vehicle utilisation for establishments in terms of kg-km travelled, and kg-hour travelled has also been modelled for attraction and production activities of establishments.

ABSTRACT. In this study, we formulate the total cost of a feeder line considering different types of fleet (fixed-size and modular) and optimize the service frequency and the number of vehicle modules (units) in case of using modular buses. Using the proposed model, we investigate the differences between the optimal total costs and optimal dispatching policies obtained for fixed-size and modular fleet. The sensitivity of the total costs, the optimal headway, and the number of vehicle units is analyzed with respect to changes in different critical parameters. The results show that at a demand rate of 250 passengers per hour, the modular fleet can operate with up to 94% lower unused seats while still offering an increased quality of service to passengers. We found that the modular fleet always has a lower total cost even if it is up to 10% more expensive than the conventional fixed-size buses in terms of the dispatch cost per seat in a demand range of 15 to 1000 passengers per hour. The results indicate that with an increase in dispatch cost ratio the demand threshold, up to which the modular fleet has less total cost, increases exponentially.

ABSTRACT. The waiting time of passengers at transfer stations is one of the most important criteria to measure the service quality of public transportation. Because of the stochastic nature of traffic, scheduled transfers cannot always occur. This research proposes an online control framework for a bus line using holding, skip-stop and speed change tactics. We build an arc-flow optimization model enumerating all possible tactics within a time horizon. The model minimizes total passenger travel times by improving, among others, transfer times and reducing deviations from the bus schedule. Decisions are based on real-time passenger flow data and travel times. The methodology was tested on a case study of the bus system of the city of Laval, Canada. A simulation framework has been developed, integrating data on smart card transactions and bus locations, to verify the performance and results of the optimization model. Data generation in the simulation framework is improved using a training set. Different levels of uncertainty are introduced on instances of a testing set and the resulting optimal parameters are applied to a validation set.

ABSTRACT. Although the past research results have provided many effective tools for evaluating public bus service quality, they still lack the concept of risk. This research attempts to integrate Kano’s model, IPA, and FMEA which provides quality attribute classification information with importance-performance analysis that provides attribute improvement ranking information and combines failure mode and effect analysis and quality risk management development. It can provide the public bus with better service quality risk management and improvement strategies. In this study, the researchers took Bangkok, Thailand, to evaluate public bus service quality risks. According to the result of this study, safety for boarding on and off the bus, cleanliness of vehicles, and punctuality of buses according to the schedule are the top three attributes that have a high service quality risk and consider a prior improvement. These attributes belong to interaction with passengers, tangible service equipment, and operating management support dimensions. Therefore, the government should take action and improve service quality to make Bangkok commuters consider switching from driving cars to using a bus.

ABSTRACT. Urban Metro Networks (UMN) as an inseparable part of transit systems, have a significant contribution to the efficiency of this system, and disruptions in their operations can severely disturb daily trips. Hence, numerous research has been conducted on the vulnerability assessment of UMNs. However, most papers have not considered the infrastructural features of the UMNs. This study aims to demonstrate the importance of accounting for infrastructural features of the UMNs -specifically the Stations with Direction-Change-Facilities (SDCF)- to improve the validity of research results. We, accordingly, introduce the Block-Based Failure Strategy (BBFS), a new failure strategy that can take SDCFs into account. The Montreal UMN is selected as the case study. Its vulnerability to targeted disruptions based on both BBFS and a conventional strategy called Node-Based Failure Strategy (NBFS) is assessed. The results show that there is a significant difference between the simulations based on BBFS and NBFS. Once the role of SDCFs is considered and BBFS is implemented, the network is considered completely degraded after 9 targeted disruptions; while the simulation conducted based on NBFS indicates that the network can tolerate 35 targeted disruptions before being totally degraded, which is significantly higher than what would plausibly occur on the network.

ABSTRACT. The present study aims to identify vulnerable locations along a bus route in Kolkata City, India using GPS trajectory data. For this purpose, the study analyzed spatial and temporal variations to capture the variability associated with bus journey time. Statistical K-S two sample test was performed to understand this spatio-temporal variability, and subsequently k-means ++ clustering was used to identify vulnerable locations (high average, and/or high variability in journey time) along the given bus route. Contrary to the previous literatures, this study separately analyzed bus stops, and segments in the context of emerging countries. The outcomes indicates that the bus stops which are frequently served are more vulnerable in nature compared to the ones served sporadically. It is also observed that vulnerable segments and bus stops are mostly present at the beginning and end of the route suggesting the immediate need to relook at these locations. Furthermore, bus stops served by multiple routes are also found to be vulnerable in nature indicating the need to reassess the operational planning of buses serving such stops. Such insights provides a rational basis to policymakers and transit operators for developing suitable case specific remedies to improve the attractiveness of the bus system.

ABSTRACT. This paper studies the operational safety of urban rail transit (URT) systems through Artificial Neural Networks. While recent safety literature adopting systematic models consider the complexity of URT operations, they focus on single systems or single components of the operational process. Our study contributes to the URT safety literature by having a macro perspective, while considering that such complex socio-technical systems involve multiple non-linear interactions among their components. To our knowledge, we present the first cross-country analysis of URT safety through machine learning models, using a unique international dataset from 27 URT systems which comprises annual system-level data. Two models are estimated to predict the annual URT injuries. The first model includes safety-related incidents as inputs, while the second includes operational characteristics of the system. Additionally, a closed-form formula is presented to predict the annual number of injuries based on operational features of the URT system along with an illustrative example to demonstrate benchmarking applications. The results are promising and indicate good generalizability. The models proposed in this study could be useful for operators and policy makers as they aid in prioritizing improvements, predicting future safety performance based on changes in operational features, and as a benchmarking tool.

ABSTRACT. Data from vehicles tracked using Global Navigation Satellite Systems (GNSS) can be used to monitor driving behaviour and road safety. In usage-based insurance programs, driver insurance premiums are tailored according to individual driving behaviour, often using data collected from user-owned smartphones. Due to positional noise caused, map matching algorithms must be used to spatially link GNSS observations to the road network. The purpose of this study is to evaluate the performance of several algorithms to process smartphone GNSS data for vehicular trips in urban road networks. This study evaluated five implementations, namely one topological (TMM), two probabilistic (PMM) using Hidden Markov Models (HMM), one fuzzy (FMM), and one hybrid map matching algorithm (HyMM) in terms of match accuracy and run time. Data was collected using ten smartphone devices and three applications across 12 trip scenarios in Montreal, Canada targeting the downtown, old city, highways, bridges, and tunnels. Results were compared with a series of ANOVA tests. Accuracy was not significantly different for the best performing algorithms (the Fast HMM and TMM) followed by the HyMM, with the Standard HMM and FMM algorithms performing significantly worse. Only the FMM algorithm was significantly slower than the others in terms of run time.

ABSTRACT. Since the C-ITS (Cooperative Intelligent Transportation Systems) are supported by TIC (Technology of Information and Communication), the telecommunication protocols and their effective coverage of the road network are strongly affecting the performance when providing high-level services to road users. Usually, the telecommunication network is supported by two approaches based on: (i) IEEE 802.11p standards (e.g. ITS G5) or (ii) cellular network (e.g. 5G). When the telecommunication network is designed as an Ad Hoc network with short-range communication, it requires RoadSide Units (RSU) along the road to broadcast messages within its communication range to the end-user. One major issue regarding Ad-Hoc networks lies in the sensitivity of traffic control performance to RSUs’ location and to the effective road network coverage to ensure adequate services. This paper develops a sensitivity analysis to evaluate the tightness impact of the network mesh according to the C-ITS service under consideration. Especially, the focus is made on the Variable Speed Limit (VSL) service and the impact is evaluated with respect to traffic efficiency and pollutant emissions.

ABSTRACT. Deep reinforcement learning (DRL) offers new perspectives for the implementation of autonomous driving. In this paper, we adopt the DRL algorithm “twin delayed deep deterministic policy gradient” to train the longitudinal control model using a reward function that can prioritize safety sub-reward. However, allowing an uninterpretable DRL-based model to dominate in taking over the longitudinal control of vehicles would raise unexpected risks. Thus, we further propose a hybrid model by combining the DRL-based model and intelligent driver model (IDM). The proposed hybrid model leverages the benefits of these two models using an indicator called velocity response time. The numerical simulation experiments demonstrate that the hybrid model performs better in terms of disturbance mitigation, safety and efficiency improvement than the DRL-based and IDM models.

ABSTRACT. This paper explores fundamental principles and combination of algorithms to accurately detect, classify and track surrounding vehicles on expressways using a vehicle mounted cost-effective LiDAR sensor in dynamic conditions, i.e., when vehicle is in moving state. Density-Based Spatial Clustering of Applications with Noise, Random Sample Consensus, and Kalman filter algorithms were employed on 3D LiDAR data collected from field to execute the following tasks: segmentation of ground and non-ground points, object clustering, road boundary identification, vehicle classification, and tracking. Tracked vehicles’ trajectory data used for estimation of their relative positions and speeds. Finally, LiDAR data was synced with Global Positioning System sensor data to get the absolute positions and speed data in continuous frames. The suggested systematic approach can be used to extract real-time micro-level trajectory data for surrounding vehicles on expressways, which can be valuable for researchers as well as practitioners for various Intelligent Transportation System (ITS) applications.

ABSTRACT. Due to the absence of an autism-tailored driving training program in Qatar, instructors may lack the expertise and skills to apply a personalized approach to those learners' demands. The current study investigated the improvement of the learning-to-drive process for autistic learners in Qatar. The study consisted of three progressive steps: (1) Assess driving instructors' prior knowledge and practices regarding autism and driving. (2) Explore driving instructors' knowledge on autism and driving before and after an evidence-based training workshop. (3) Compare the learning to drive process for autistic learners following lessons from driving instructors that followed workshop, compared to those with driving instructors that did not. Eighty-seven male driving instructors and 6 male autistic learners were included in the study. Results from the assessment phase indicated that most instructors lacked knowledge about autism and driving. During the training phase, the workshop improved the driving instructors' knowledge on autism and driving. After the practice phase, trained driving instructors reported that they were better able to match their lesson to their autistic learners than non-trained driving instructors. Moreover, the three autistic learners who received driving training from the trained instructors showed better training experience than the three who received training from non-trained instructors.

ABSTRACT. Effective enforcement of traffic laws is essential to the safety of transport systems. Multiple factors may adversely impact the ability or willingness of law enforcement (i.e., police officers) to engage in traffic safety enforcement. Through a narrative review of existing literature, this report summarizes factors that influence traffic safety enforcement by police and provides policy recommendations to improve traffic safety. Several factors that affect officers’ engagement in traffic law enforcement were identified, including: (i) individual-level factors (e.g., officers’ attitudes towards traffic law enforcement), (ii) situational factors (e.g., traffic offenders’ demeanor at the time of infraction), (iii) organization-level factors (e.g., supervisory influence), and (iv) community-level factors (e.g., community’s support for traffic safety enforcement). Barriers to effective traffic safety enforcement may depend on a country’s economic condition. In high-income countries, police officers’ lack time for traffic law enforcement; in low-income countries, there is lack of funding to support policing activities. Recruitment of non-sworn personnel to conduct traffic safety enforcement could help to overcome these barriers through reduced costs for training and employment. Results and recommendations arising from this review may benefit transport and law enforcement agencies through increased understanding and encouragement of officers’ engagement in traffic law enforcement.

ABSTRACT. This paper aims to provide a cognitive perspective on the hazard perception process in the traffic situation based on the two complementary theories of brain information processing, namely, Signal Detection Theory and Predictive Coding Theory. The theories are empirically validated in an augmented virtuality scenario, where participants are faced with hazard cues characterised by a different degree of predictability. Throughout the experiment, the acceleration and braking behaviour of an e-scooter rider together with the electroencephalography data is collected. The developed experiment allows for testing the applicability of brain theories in explaining behaviour and cognitive processing of hazard perception. Current findings support a priori expectations showing that participants create predictions concerning future potential hazards. Produced predictions and the subsequent behaviour are modulated by the degree of ambiguity of hazard cues in line with Signal Detection Theory. Complementary to behavioural results the alpha wave is identified as a neural marker of hazard predictability. The results provide implications for road safety researchers and practitioners, where the inclusion of a cognitive perspective can guide the more-informed design of road infrastructure as well as in-vehicle human support systems to be more aligned with the processing mechanisms of human cognition and exploit the synergies between them.

ABSTRACT. Despite improvements in roadway engineering and safety enforcement, traffic collisions and injuries remain one of the leading causes of death worldwide. Traffic violations and risk-taking behaviors are closely related to drivers' perceived threat of risky driving behavior and their support for laws and regulations. This paper examines the drivers’ perception components and their impact on support for safety laws by using structural equation modeling accompanied by a set of factor analysis to group the correlated responses into factors. The results indicate that drivers’ perspective of social non-acceptance of risky driving behaviors and their awareness of safety problems significantly influence drivers' personal non-acceptance of dangerous driving behaviors. Also, it has been shown that drivers' non-acceptance of risky driving behaviors influences their support for laws prohibiting those behaviors. To improve the traffic safety culture in Canada, suggestions have been made on how to improve drivers' attitudes and support for safety laws as per finding of this paper.

ABSTRACT. The highway safety manual provides guidance on predicting crash frequency (CF) based on safety performance functions (SPFs), and crash modification factors (CMFs). This study attempts to develop (i) truck SPFs (regression models predicting truck-involved CFs), and (ii) hazard-specific CMFs (multiplicative factors reflecting the change in CFs due to transportation hazards), for rural two-lane two-way highways (R-TL-TW) and rural multilane highways. Police-reported truck-involved crash data on rural highway segments of Alberta, Canada, from 2015 to 2017 were used to develop truck SPFs for four crash severity levels: total, fatal, personal injury (PI), and property damage only (PDO). According to the study results, the negative binomial distribution was deemed as the most appropriate distribution to model truck-involved crashes for all crash severity levels. Of the statistically significant CMFs, the CMF for poor visibility (CMF=1.5) suggests that poor visibility increases PI type truck-involved crashes on R-TL-TW segments by 50% as compared to the number of such crashes attributed to crash causes other than transportation hazards. Road safety researchers and practitioners may adapt the study methodology to effectively rank hazard risks to a highway freight transportation system, thus prioritizing safety countermeasures designed to mitigate truck crashes attributed to transportation hazards that intensify truck vulnerability.

ABSTRACT. This paper studies and presents data-driven methods for finding rankings of traffic links in a network for optimal traffic data reconstruction based on measurements taken from a subset of links. The link ranking represents the importance of respective links in terms of reconstructing traffic information from sparsely placed sensors, connected vehicles, or other state-of-the-art methods. We first present a baseline method based matrix factorization of the eigen-vector basis matrix, followed by column pivoting. Moreover, we propose a reinforcement learning framework to improve the ranking method when the traffic data is used for the purpose of routing. This study utilizes dynamic traffic data that is observed and estimated from simulation.

ABSTRACT. Fundamental diagram(FD) is considered as the foundation of traffic flow theory and is critical for traffic modelling and management. In this paper, we propose a FD reconstruction approach which aims to derive well-fitted FDs with empirical data. The proposed approach includes an iterative nonlinear pattern extraction method and nonlinear-pattern-based FD reconstruction method. A linearization transformation procedure(LTP) is proposed to convert the initial-FD(IFD) into a linear function. The LTP is also performed on the data. In case there exist nonlinear patterns in the transformed data, the nonlinear pattern extraction method is used to derive these patterns iteratively. Based on the IFD and extracted nonlinear patterns, the new FD can be reconstructed. We use the freeway loop-detector dataset to verify the performance of the reconstructed-FD(RFD) by the proposed method. The results show that the RFD fits better with the empirical data compared with the IFD. We further analyze the performance of the IFD and RFD in different density intervals with sample bias. The results show that the proposed FD reconstruction approach could reduce the fitting errors significantly in the density intervals with few samples, and on average provide better fitting performance in the entire density range compared with that of the IFD.

ABSTRACT. As an important part of intelligent transportation systems, machine vision and deep learning techniques are becoming more popular in vehicle speed detection. This study proposed a vehicle speed extraction method based on machine vision and deep learning with the help of lane assistance lines (six-nine line). First, built a multi-objective detection and tracking framework based on YOLOv5 and Deep SORT. The YOLOv5 is used to identify vehicles and obtain vehicle information such as center position, width, and length. The Deep SORT is responsible for analyzing the relationship of trajectories between vehicles. Based on vehicle trajectory data, a lane assistance line was used as a reference to extract the vehicle speed. Second, the LIDAR was used to verify the accuracy of the proposed method. The LIDAR data processing includes four steps: detection area extraction, background segmentation, vehicle detection and tracking, and vehicle speed calculation. Finally, the vehicle operation data of Beijing's Third Ring Expressway were obtained. The experimental results show that the vehicle recognition accuracy could reach 99%, and the speed detection accuracy of each lane was around 95%. The proposed method could provide some support for the implementation of traffic control measures.

ABSTRACT. Prior to the acquisition an electric vehicle, pre-evaluation of vehicle energy use is essential for assessing whether the intrinsic electrical storage capability is satisfactory. However, inconsistency in vehicle modelling may provide unreliable predictions concerning energy usage. In order to increase the prediction reliability, one potential solution may lie in use of city-specific driving cycle data and other geographical information.

This paper presents a novel method of extracting driving data from archived dashcam videos without the need to deploy a fleet of test vehicles to log conventional telemetry. Utilising dashcam videos as input, employing last-generation image processing and recognition technology, textual in-route driving data embedded in the video can be extracted. The results from preliminary testing using real-life dashcam videos demonstrate negligible errors with regards to energy requirements and pollutants emitted from an EV operating on the modelled routes. Consequentially, the proposed solution opens up the possibility to employ a significant amount of new data in order to better assess the transport sector’s energy requirements. This is especially important for situations where conventional telemetry is difficult to obtain.

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The study investigated driver behavior in a developing country, based on Nigerian data, on the assumption that angry and aggressive behaviors are revealed when drivers respond to various traffic situations. The drivers studied include shared-taxi, bus, truck and impulsive drivers. Drivers’ angry and aggressive behaviors were captured from the replies reported when drivers were faced with a list of hypothetical traffic states prevalent on inter-city roads in Nigeria. The questionnaire used to elicit driver responses was adapted from the Manchester’s Drivers Behavior Questionnaire (DBQ). Exploratory factor analysis was used to establish the principal components of the data collected. The driver response menu was then rescaled to generate binary data suitable for binomial distribution due to Bernoulli trials. The maximum likelihood logistic regression was used to estimate the odds ratios reflecting the scales of anger and aggression of drivers. The results suggest that the probability of driver aggression was high while the probability of driver anger was even higher. Impulsive drivers revealed higher aggression scales than others. The approach is novel in quantifying the behavior of drivers of different transport modes. The findings are also useful for policy making towards influencing driver behaviors on inter-city roads in developing countries.

ABSTRACT. In the past, far-reaching measures have been tested regarding how to encourage people to switch from cars to the more emission-friendly public transport. Previous projects have only been able to convince people to switch temporarily through subsidised public transport. Detached from the ecological aspects, the turmoil in the global economy at the end of February 2022 resulted in a price shock in mineral oil prices, which shifted the primary focus of mobility behaviour from ecological to economic concerns. The logistic regression analysis of a quantitative survey in Germany confirms that a large number of journeys taken via car were saved due to the increased price. However, despite high mineral oil prices, travelling by car remains the primary means of transport for many people. Contrary to results of prior studies, the present analysis shows that participants from large cities have saved fewer trips by car compared to people living in rural areas, even though large cities generally have a denser infrastructure with a more comprehensive range of mobility options. Travel time and reliability are the main factors in our respondents' choice of transport mode and are more compatible in large cities with denser public transport than in rural areas.

ABSTRACT. Due to the differences between men and women, they are expected to exhibit different travel behaviors. In developing countries, there are limited studies on citizen travel behavior. The main aim of this study is to clarify the transportation behavior distinctions between men and women by modeling the effect of lifestyles and attitudes on the commuters’ mode choice. For this purpose, an interview questionnaire was designed, and 979 participants were interviewed in Tehran. Questions were posed about attitudes toward transportation, attitudes toward residential location, and lifestyle of individuals. The results of factor analysis indicate a significant difference between men’s and women’s lifestyles and attitudes. The results of the structural equation model showed that the effect of lifestyle and individual attitude on travel behavior is different between men and women. These differences verify the importance of making transportation policies addressing gender distinctions. The findings could be helpful for future research in this area.

ABSTRACT. A solid understanding of the impact of urban mobility environments on well-being is crucial for cities and their planning activities. Despite its importance, there are very few empirical studies investigating mobility environments and its antecedents in transport research literature. This study contributes to bridging this gap by conceptualizing a two-level model. Drawing on a nested dataset of 3,487 citizens from the Top 35 German cities, the results of a two-level hierarchical regression model show that competence, autonomy and relatedness as antecedents of motivation and well-being are influenced by cities and their transport environment. Based on the empirical results, the paper discusses the implications for theory, city planners and transport providers.

ABSTRACT. When we talk about sustainable travel we often think about some distant future that we are trying to reach. We exchange ideas, set milestones and try to execute them. All this in the adults’ world, most likely representing perspectives of generation X, Y and Millennials. But what about youngsters and their perception of sustainability? Do generation Z and Alpha actually know what sustainable mobility means and if so, do they care at all? This study analyses results of a kids’ city mobility survey conducted in a primary school in Poland and highlights key points related to sustainable travel from kids’ perspective. It shows that, on one hand so far we as adults have failed to communicate the sustainability message to the children, but on the other hand gives some hope in the way kids think and perceive their daily commuting, especially in the context of key characteristics of these new generations. There is hope for sustainable (travel in the) future, but for it to succeed it is crucial to understand today's kids' generations better and put conclusions of our conversations and findings into concrete actions tailored to Gen Z and Gen Alpha's needs and expectations.

ABSTRACT. The present study demonstrates the use of the nested-logit (NL) approach in modal-split modeling with input related to the total cost of travel determined based on the cost of travel per km, and the cost of travel time per minute incurred by trip-makers. The calibrated best value of the scaling parameter that simulated the actual travel pattern as in Amritsar city in India was identified based on a trial-and-error approach, followed by cost-based sensitivity analyses. The study revealed that an increase in the combined costs of travel by private modes including intermediate public transport (IPT) modes resulted in a higher estimated ridership by public modes of travel such as mini-buses. Similar analyses were performed to estimate the ridership for private modes Vs IPT modes. One of the key findings of the cost-sensitivity analysis is that even when the total cost of travel by private modes including IPT was increased by up to 35%, the ridership by these modes remained more dominant than that of public modes. In Amritsar, trip-makers rely on independently operated minibuses and IPT alternatives that provide shared rides in place of buses. The insights provided can help formulate policies for promoting public transport modes.

ABSTRACT. The present work aims to investigate commuter’s preference towards motorized feeder service for the last mile connectivity from metro stations in the context of Sector-V commercial hub, in India. Firstly, the influence of socio economic and trip characteristics of commuters in deciding motorized feeder service over the active modes is investigated. Secondly, the commuters’ willingness to pay for the motorized feeder service is determined. This work also investigates the effect of socio-economic and trip characteristics of the commuters, if any, on the WTP values. For this purpose, binomial probit model is developed to identify the factors influencing commuter’s preference to use motorized feeder service. In order to determine the commuters’ willingness-to-pay, discrete choice modelling is performed. In this regard, a suitable questionnaire is developed to collect stated preference data of the commuters. Random parameter logit models were developed for determining the WTP values, as well as to determine the effect of socio-economic and trip characteristics of the commuters on the WTP values. The study brings out several interesting findings which will help in formulating suitable policies for improvement of motorized feeder service as last-mile connectivity.

ABSTRACT. The significantly higher level of detail of agent-based travel demand models (ABM) compared to aggregate models stands in contrast to their high simulation times. Once fast model responses are necessary, the application of ABMs may pose run time challenges. For such purposes, a condensation of ABMs' sensitivities and saturation effects regarding travel mode choice is required, which - as shown in this paper - is achieved by a multiple discrete continuous extreme value model (MDCEV). The application case of this method is a serious game which enables decision-makers and citizens low-threshold access to a better understanding of interrelations within the urban mobility system. The mode choice model for the serious game is estimated on the basis of the simulated travel demand patterns of an ABM. The comparison of the model application with the ABM reference results attests a good ability to reproduce the current travel demand, even for different types of traffic. Also modal shift reactions on policy interventions reveal a high level of consistency. The presented approach might allow for improved and more flexible communication of forecast results in different use cases while strengthening the comprehensibility and credibility of planning tools in the transport sector to other interest groups.

ABSTRACT. The service quality of a public transport system is mostly measured by employing indicators from the traffic engineering perspective. But often, the actual perception of the passengers may not conform to these results of the technical service level indicators. Therefore, this study aims to evaluate the Customer Satisfaction Index (CSI) of the public bus services and identify the most important factors that affect the passenger satisfaction and mode preference in the city of Kolkata. Multinomial Logit (MNL) model is developed to comprehend the effect of the various factors on mode preference. The CSI suggests that the Regular AC bus riders and the choice riders are most satisfied with the AC bus service. Waiting Time is found to be the most important parameter influencing the perception of the AC bus service. The MNL model suggests that age, time of the day, income, trip frequency, ridership and waiting time are significantly affecting the mode preference of the commuters. Para-transit is considered as a potential alternative by the AC bus users.

ABSTRACT. Studies in residential self-selection literature which use attitudinal factors to model the jointness of residential and travel-related choices assume a unidirectional impact from attitudes to behavior; however, such an assumption may be violated under several circumstances. In this current study, we allow the error terms of the attitudinal factors to be correlated with the main outcomes as we jointly model residential choice, auto-ownership level, and ranked-based modal preferences. In our joint model, we use Green Lifestyle Propensity (GLP) and Luxury Lifestyle Propensity (LLP) as the two stochastic latent constructs. The empirical data for this study is drawn from the 2019 multi-city Transformative Technologies in Transportation (T4) Survey for the city of Austin that elicited information regarding individuals’ residential location, auto-ownership, and modal preferences through a stated preference experiment in a futuristic AV environment. Results indicate significant unobserved correlations between the latent constructs and the main outcomes; ignoring such endogeneity leads to substantial underestimations of the “true” causal effect of high-density neighborhood (HDN) living on travel-related choices, which can have serious consequences for policy-making.

ABSTRACT. Discussions on the nexus between transport infrastructure and economic growth have had decades of modifications, analysis and contributions at varying intensities and capacities in academia. The current study is to analyze the trends in the literature concerning the extent, direction and variations of transport-infrastructure-led-economic growth causality. Unlike previous reviews, it is a comprehensive review carrying more papers published in more years. As a result, a roadmap to shorten the overarching gap between academia and public policy is figured out. Using the PRISMA methodology of Systematic Literature Review, only those published in ABDC ranked A or A* journals have been taken within 2000-2021. The literature search was conducted in 2021, and the systematic selection process identified 47 articles for a detailed study. The existing literature is categorized, but the opportunities and possibilities for future research have been streamlined. There is excellent potential for theory extension and development in the concerned field as it covers the subjects of transportation, economic growth, environment and spillovers. We have limited our research to top journals, excluding articles from low-ranked journals, along with writings other than English. The findings are to have a stakeholder-level impact on decision-making, including policymakers, technocrats, academicians, researchers, and so on.

ABSTRACT. This paper begins with a brief historical presentation of the evolution in France of evaluation practices and the laws and regulations that impose them. The French example is an illustration of a general development of evaluation methods and of the objects that these methods seek to grasp. The usefulness and implementation of ex post evaluations will then be discussed, whether by simple experience feedback or by methodological necessity, in particular for the analyze of wider economic benefits (WEB) which were often mentioned in the presentation of the projects and which were sometimes decisive in the decision to invest. This methodological dimension will naturally lead to discussing the use of permanent observatories, such as those set up in France after the construction of major motorway projects or new high-speed rail lines. Particular attention will be paid to the case of the socio-economic observatory set up to assess the effects of the “Sud Europe Atlantique” high-speed line, which is a first case of railway concession and which is a very singular project regarding its cost (€8 billion).

ABSTRACT. Most communities have two transportation systems: an automobile-oriented system that includes higher-speed roads and parking facilities, plus a non-auto system that includes sidewalks, paths, lower-speed roads, and public transit services. Planning decisions often involve trade-offs between them. This study examines how determine the optimal balance of investments in these two systems. It estimates non-auto travel demands and describes how planning should serve them. In a typical North American community 20% to 40% of travelers cannot, should not or prefer not to drive and will use non-auto modes if they are convenient, comfortable and affordable. This is higher than commonly-cited statistics indicate and much higher than the portion of transportation investments currently devoted to non-auto modes. This study identifies economic principles that can guide multimodal planning. It concludes that to be efficient and equitable, planning should invest in non-auto modes at least as much as their potential mode shares, and more to achieve strategic goals and correct for a century of underinvestment. This is more comprehensive than previous studies.

ABSTRACT. The advanced developments in information technology have enabled resource exchanges among different transportation service providers (TSPs). One can offer its mobility resources to the other to gain rewards. We study the optimal strategies of resource exchange and pricing for two TSPs using a sequential-move game. In the first stage, we develop a Nash bargaining game to characterize the interactive resource-money-exchange process. The mobility resource price is modeled as a two-part tariff in terms of the exchange quantities. In the second stage, we develop a duopoly competition game to characterize the pricing strategy of the two TSPs. The utility of end users is affected by TSP's prices and supply-demand congestion effects. By doing so, we can derive the conditions under which TSPs will adopt the above three strategies. Analytical results show that a ``win-win" outcome can be achieved when the unit price decreases in the number of exchange mobility resources. We also find that regardless of how the service prices are set, as the units of exchange resources increase, the demand for resource sellers will decrease and the demand for resource buyers will increase.

ABSTRACT. Many people depend on inland waterways transport (IWT) to access remote zones in the global south. In those areas, most of its users are low-income people. It is the case of the Magdalena River, the most important in Colombia, where fares are defined without considering social benefit criteria. This research aims to develop a social optimum fare model for IWT passenger services and apply it to a case study in Colombia. For this purpose, we developed the production and cost functions for IWT services using an optimization model and econometric techniques with available data. Then, we calibrated demand functions with diverse functional forms and estimated fares considering several social benefits distribution scenarios between users and transporters. Our work is the first attempt to deduce optimal fares for IWT using actual data for demand and costs considering economic principles of social welfare in the Latin American context. The model's application investigates if current fares are optimal in the Magdalena River, illustrating the practical application of the model and its policy implications. The results suggest that optimal fares require subsidies.

ABSTRACT. E-scooter and e-bike sharing mobility systems are now available in many cities worldwide as a low-threshold mobility offering for a broad mass. In Germany, e-scooter sharing mobility systems have been established for the first time in 2019 in large cities, primarily in inner-city areas. In the meantime, various shared mobility service providers have expanded to small towns and the outskirts of large cities with different supply strategies. Therefore, this paper aims to investigate the different aspects, such as pricing models and parking regulations that affect the usage of such services in the outskirts. For this purpose, the provided data of an e-scooter and e-bike shared mobility service provider has been analyzed. The results show that shared mobility service provider can profit from extending their supply strategies to outskirts due to similar user behaviour compared to inner-city areas. Compared to other outskirts with a lower price, a higher price does not necessarily result in lower demand. Thus, the demand on the outskirts is not necessarily price-driven but rather depends on local factors. In addition, there was a strong tendency to use e-scooters compared to e-bikes. In all case studies, an almost identical relationship between residents and users could be determined.

ABSTRACT. The transport sector is responsible for more than a quarter of the global emissions, and road transport alone contributes with over 70% of that share. Following the concerns about the current Emissions Trading Systems (ETS) being unable to achieve the 2030 emission goals, the European Commission presented a proposal to implement a parallel ETS to cover road transport emissions. The outcomes expected from such a policy proposal can be summarized as higher fuel prices, leading to less fuel consumption and reduced road transport emissions. This article explores fuel consumers’ perceptual differences if the fuel price increases because of an increase in fuel duties or because of the introduction of a parallel ETS for road transport. This research employed a Serious Game (SG) to elicit perceptions during a set of semi-structured interviews. The game was named the Commuter Dilemma Game because it was designed to simulate possible decisions that daily commuters would face after fuel price increments. The main finding is that emissions trading seems to be seen more positively than an increase in fuel duties because the study participants associated emissions trading to a reduction in CO2 emissions, and fuel duty increases to an increase in pump prices.

ABSTRACT. Since January 2021, a national CO2 price, which is passed on to consumers and companies via an additional price on fuel due to an upstream principle, has been in use in Germany. In addition to increasing energy costs and the effects of inflation, the CO2 price will further burden the freight forwarding industry. Carriers must therefore recalculate their transport costs. However, the question of how these additional compensation costs should be included in their calculation approaches. This paper demonstrates the CO2 price’s first effects on road transport prices based on a description model resulting in a new index. The newly developed model clarifies the connection between transport prices and fuel costs, including CO2 prices, based on empirical data.

ABSTRACT. In the Paris Agreement of 2015, many nations agreed to mitigate carbon emissions to avoid drastic climate changes. To achieve this, emission reductions in transportation are essential. In this paper, I investigate effects of fuel taxation in Finland, Norway, and Sweden. I estimate emission reductions, using a synthetic control unit chosen from the OECD. Carbon emissions declined by 10.5 percent for Finland and 17.3 percent for Sweden between 1990 and 2005 after major increases in fuel taxation compared to its counterfactual. Norway reduced carbon intensity by keeping emissions constant under massive economic growth. However, observed effects show that emission reductions in road transportation are achievable. Moreover, I conduct a regression analysis to inspect for stronger tax than price effects on fuel consumption, referred to as tax salience in literature. Previous literature provides evidence for North America. If salience is present policy evaluations using price elasticities may underestimate emission reductions. Evidence for tax salience in Europe is ambiguous. This work indicates that tax salience is present, but overestimated by previous literature as complexity of fuel taxation and effects from diesel substitution in the European Market are neglected. This is critical as undertaxation may lead to miss emission reduction targets.

ABSTRACT. Transit-oriented Development (TOD) is widely used to promote the integration of land use and transit services. Existing studies have indicated a strong association between the TOD pattern and accessibility at the metro-served area (M-SA) level. However, largely due to constraints of available/empirical data, few studies have quantified an association beyond M-SA, e.g., at the corridor or city levels across years. By using big/new data, we examine to what degree the accessibility of an M-SA cluster (M-SAC), a set of M-SAs within t minutes’ metro ride from a metro station is correlated to that M-SAC’s TOD-ness in Shenzhen, China. We measure the accessibility by the daytime/nighttime population in the same M-SAC. We define TOD-ness as the average extent to which all the M-SAs in an M-SAC meet agreed-upon characteristics concerning the three Ds: Density, Diversity, and Design. Coefficient of geography association, Gini index, pairwise correlation, and linear regression are carried out. We find that the accessibility in one period can significantly predict TOD-ness in the ensuing periods. However, the accessibility’s impacts on TOD-ness decrease or even disappear over time. Besides, station (area) characteristics can significantly predict TOD-ness and the three Ds after controlling the accessibility.

ABSTRACT. Urban areas are required to integrate transportation and land use with changes in social conditions. In this context, it is effective to consider land use that maintains users at railway stations, which are the foundation of transportation, while utilizing the existing stock of transportation networks. We conducted multiple regression analysis to identify the relationship between the number of railway passengers and land use around stations on four private railway lines in the Tokyo metropolitan area and seven lines in the Sendai metropolitan area, prior to the ultimate goal of creating sustainable cities and railway services. These results provide the first steps toward developing sustainable rail services in metropolitan and regional cities, along with integrated transportation and land use planning.

ABSTRACT. With the continuous development of rail transit system in various cities, the public transit-oriented development concept has become an important research field of urban design. This paper takes the Urban Design of Lujia Rail Station area in Kunshan City as an example, and summarizes the characteristics of TOD construction mode in Kunshan based on the evolution of TOD theory and practical development. Then it discusses the integration of multi-scale planning and design strategies for station cluster, station areas and stations, the ways to solve problems such as land fragmentation, cultural discontinuities and landscape dislocation at Lujia Rail Station area, and the specific practices to improve the coupling degree of land development and transportation development. The study can provide an empirical reference for the renewal and transformation of the rail transit station area in China.

ABSTRACT. Station-city synergy refers to the process of integration and joint development of the rail transportation movement system and urban life. As a pioneer in rail construction, European rail stations have been practicing efficient and sustainable station-city synergy modes such as slow-moving priority and public transport priority under the trend of green mobility. Therefore, through field research on the organization of mobility modes in European Railway station areas, this paper summarizes their walking systems, public transport and bicycle systems, private cars and cab systems and strategies under the green mobility trend, hoping to contribute to the design of station-city synergy in China in the future.

ABSTRACT. In recent years, the number of cities aiming at compact cities that centers on public transportation and concentrate residence and urban functions around them has increased. However, there are very few cities that are actively promoting policies to improve the convenience of railways, which should play a central role in such cities. It is possible that there are some relationships between the convenience of railways and change in urban structure. Therefore, this study examines the influence of local railways on urban structure by analyzing changes in the user density overtime, the number of train services and population around rail stations, and their mutual relationship, focusing on railway and tramway in local cities. In addition, local railways and tramways have been classified by two business operators, and the relationships between the user density, the number of train services, and the population around rail stations have been analyzed and examined by business operators.

ABSTRACT. Adopting battery-electric buses (BEBs) is useful for tackling climate change and promoting environmentally-friendly mobility solutions. However, designing a BEB system configuration requires sophisticated planning efforts due to contradictory objectives/decisions. Furthermore, the optimal design of a BEB system can be approached from three perspectives: economical, operational, and environmental; each produces a different system configuration and a distinct impact on the utility grid. Towards that end, this study develops three BEB system configuration optimization models from three different perspectives, including minimizing: capital costs, electricity costs, and greenhouse gas (GHG) emissions. These models provide the optimal charging infrastructure configuration for a general hub-and-spoke transit network and quantify the fleet configuration (battery capacity) and the charging schedule. A real-world bus transit network in Belleville City, Ontario, Canada, is used as a case study. Comparing the results of these models demonstrates that the BEB system configuration and GHG savings vary significantly according to the optimization perspective. These findings emphasize the importance of using multi-objective optimization to guide the configuration of a BEB system design and stress the need for trade-offs to achieve optimal resource allocation.

ABSTRACT. The transportation sector has been aiming to reduce the carbon emissions by promoting the use of low emission vehicles. Although the Indian electric vehicle market is dominated by electric two-wheelers and three wheelers, various governmental schemes have boosted the inclusion of electric buses within the urban bus fleet. However, it is essential for the transport authorities to understand the acceptability of the electric buses among the commuters who are not using public transport currently. This paper aims at understanding the preferences of non-public transport users, to assess the probability of them shifting their modal choice towards public transport, and electric buses in particular, within the Indian context. The data has been collected through a Stated Choice experiment from 414 individuals in Ahmedabad. It has been observed that the low-income individuals are found to prefer public transit if the buses are electric with an affordable fare. The results indicate that electrification of urban bus fleet can improve the image of the existing bus services thereby facilitating modal shift towards public transit among the low-income individuals who have shifted to other modes of transport due to the deterioration of the service quality of the existing transit system.

ABSTRACT. Water consumption for public transport is an uninvestigated issue, yet water is central in environmental policies as it is for energy and pollution. No standards, regular data or policies are available in this field and washing operations are managed at garages according to local practice, with very few cases of water post-treatment. This paper moves from here and presents a scenario assessment where three innovative technologies for saving water are applied at three washing plants, within the European Commission’s LIFEH2OBUS project. The technologies are: water reclamation; water reclamation and harvesting; waxing without water. Simulations highlight an 84% reduction in average of water consumption after one year of implementation, i.e. 37 million fresh water saved, for a fleet of 680 buses. By reaching 50% of the European transit fleet in 5 years (342,143 buses), 18 billion liters/year can be saved, corresponding to -42% of the total water used by the transport sector, along with a 1,159 GWh reduction of energy consumption, and 504 ktCO2eq greenhouse gas emissions less, equating to 151 million Euros saved. The research goal is to give rise to a new study field on water management in the transport sector and contribute to advance scientific knowledge further afield.

ABSTRACT. Evaluation of data-driven engineering solutions depends on efficient analysis and IT knowledge at expert level. Recent technologies and their pilot applications in transportation engineering generate big data such as vehicle data. To handle and analyze vehicle data, solutions and new methodologies are necessary for field engineers to interpret the results reliably. ELISA, the eHighway pilot project in Germany, is an engineering solution to achieve zero emission goal by road freight transport. Five overhead contact line trucks (O-trucks) are operating along five kilometers of the eHighway test track in each direction. In this study, we present a difference-based run detection methodology to analyze vehicle data obtained through five O-trucks. Dataloggers on the O-trucks transmit more than 100 parameters for each 100 ms. We propose that difference between following records for a parameter is an efficient way of analyzing and detecting runs on a highway section. The proposed difference-based approach and run detection algorithm performed well to investigate 650 GB data from O-trucks in the ELISA project. Operational and energy consumption analyses by using this data process provide reliable and reasonable results. We shared numerical and visual analysis samples to give insight for further evaluation and monitoring of the large-scale eHighway implementations.

ABSTRACT. There is no globally accepted definition of a sustainable bus transit system. In addition, the literature does not include a method for evaluating the sustainability of such systems. This paper begins with a literature review of evaluation criteria considered in previous studies. Then, we categorize these criteria into three major groups according to the three principles of sustainability. In the next step, the final list of criteria in each sustainability dimension is presented. We also identify various beneficiaries related to public bus transit systems. Finally, we suggest a mathematical approach that ranks and weights the identified criteria from the perspective of each beneficiary as well as all beneficiaries. This method can be used to select the final list of criteria for evaluating the network design and operations planning of a sustainable public bus system. This proposed approach is based on the Group Best Worst Method (GBWM). To test the applicability of the proposed model, the GBWM is applied to a small sample in the cities of Calgary, Canada, and Beijing, China, and the results for both cities are discussed. The results show that the definition of sustainability in public bus transit services is a local rather than a global concept.

ABSTRACT. The present study investigates the direct effect of traffic volume, speed and observer distance from the noise source on the equivalent noise level. Partial least square-structural equation modelling was used to analyse the effect of these factors on the equivalent noise level at the intersection based on the 342-hours data collected for mixed traffic in Kanpur, India. The entrance and exit arm analysis is carried out separately to evaluate the effect of these factors on the measured equivalent noise level. It was found that one-unit growth in entrance traffic volume increases entrance and exit arm equivalent noise levels by 0.306 dBA, 0.210 dBA, respectively. Also, one-unit exit arm volume changes are expected to increase entrance and exit arm equivalent noise levels by 0.458 dBA, 0.488 dBA, respectively. The changes in speeds were found to decrease the entrance and exit arm equivalent noise levels by 0.735 dBA and 0.995 dBA, respectively, in a regime of 5 km/h increase in the exit arm stream speed. An increase in the distance of the sound level meter by 1 m from the source was found to reduce the entrance and exit arm equivalent noise levels by 0.423 dBA and 0.439 dBA, respectively.

ABSTRACT. Throughout the process of urban transformation, governments should seek to enhance public happiness and security. Public service facilities are vital for achieving this goal. However, research on the spatial optimization of public resources with social equity in mind remains sparse. The marginal middle class is a special part of a megacity’s population, and it should be of great concern for governments around the world. This study defines the scope of the marginal middle class and analyzes four communities located between the inner and suburban rings in Shanghai. We evaluate the subjective well-being of the residents of these communities, along with the accessibility, availability, affordability, and acceptability of public service facilities. Multiple linear regression models were used to identify the factors affecting subjective well-being. The results show that age, occupation, per capita green area, per capita living space, and the accessibility of several public services have significant effects on the subjective well-being of the marginal middle class in megacities. This study proposes that for future planning in megacities, policymakers should not only focus on the quantity and accessibility of public service facilities, but also on the subjective feelings of residents.

ABSTRACT. Existing studies developed social dynamic models to address urban challenges; and social dynamics networks may illustrate a large complex urban structure better compared to social static networks, especially using a multi-layer network due to considering the complex interactions within different entities of urban structures which generate multiple types of relationships, temporal changes, and other various complications. However, these models have not been evaluated from a sensitivity analysis point of view. The sensitivity and stability analysis can show the characteristic results of simulation models and are essential for confirming model validity with various parameter settings. Therefore, this study is aimed to examine the characteristic results of social dynamics simulation models and to confirm their applicability in the evaluation of different urban policies in real and virtual cities. Furthermore, the study examines the behavior of the simulation models associated with the city`s demography, land use, and transportation system. Additionally, the study investigates the correlation between the birth rate, land prices, and transportation costs with the future situation of the city by analyzing the simulation results. The result of this study shows if the social dynamic models can evaluate different urban policies such as changes in the population, land prices, and transportation accessibility.

ABSTRACT. Changes in walkability and greenspace impact travel related activity patterns, health outcomes, and vehicle emissions. Resulting levels of physical activity or sedentary travel time impact obesity, diabetes, and heart disease. It is becoming increasingly possible to track changes in local land use indicators known to impact health. This information can provide decision-makers with feedback required to spatially prioritize transportation infrastructure and inform land use actions needed to promote health while addressing social justice concerns. Linking local government achievement of established benchmarks for key health and climate change indicators with access to resources establishes a performance-based approach to transportation funding. This study tracks physical and social evolution of neighborhoods between 2013 and 2020 at the census tract level. Largest and smallest increases in walkability were observed in Western Pacific and West North states, respectively. Characterized by nonlinearity with overdose/ceiling effects, racial and social justice related disparities were found in access to more walkable infrastructure by marginalized populations (such as less-educated, older, unemployed, and black individuals). Empirical findings support the creation of a surveillance system to underpin a “performance-based” approach to transportation funding based on local land use actions as a mechanism to achieve social justice, health, and climate change mandates.

ABSTRACT. New transport innovations, including smartphone-enabled transport apps for Mobility-as-a-Service, and micro-mobility modes of travel including e-scooters and e-bikes, have the potential to promote greater sustainable travel and modal shift away from the car, as well as improve physical activity through greater active travel, and provide additional data to help inform evidence-based transport policy. This study looks at the multi-scheme implementation of a large transport innovations programme in the Solent region on the south coast of the UK, and provides some early lessons based on an interim review of some of the ongoing trials, to help assess whether particular innovative schemes can help to solve some of the ongoing environmental and sustainability challenges faced by a multi-city region. This includes presenting the initial results from the process evaluation of the programme over the first 18 months, as well as the findings from the operators of the e-scooter trials, which were one of the first schemes to get started. The findings suggest there is high displacement of car trips when using e-scooters, although this is largely based on self-reporting or secondary surveys, and the usage is most popular among younger males, which are consistent with most other studies to date.

ABSTRACT. Objective data on pedestrian travel has long been lacking, especially pertaining to quantitative information about flows and route choices. The recent ICT development has opened up opportunities to automatically/passively collect position-determined data, but has rarely been used to study walking behavior. This study analyses the use of two such data sources for pedestrian study. Data was collected in autumn 2019 in Umeå, Sweden, where residents (N = 88) in the study area were asked to use the travel survey app (TravelVu) for 5 days. A total of 3856 trips were recorded of which 51% was walking. A measurement of travel patterns was also carried out with Wi-Fi (Bumbee) for 8 days at 14 points, which recorded 279,791 entries. The results show that what Bumbee loses in precision it makes up for in the number of registrations, while TravelVu provides a detailed picture of individual’s travels. This pilot study addresses how well the combination of these types of data describes the pedestrian traffic in an area in terms of flow, route choice and distribution in time and space. Furthermore, the study provides knowledge on how new data sources can be used to provide municipalities with a picture of their pedestrian traffic.

ABSTRACT. E-bikes increase cycling mode shares and are expected to contribute to sustainable mobility. This paper analyzes data from the German national travel survey from 2017, as there is a lack of research on their effect on travel behavior, differentiating between socio-demographic groups. We present two logit models, one analyzing the ownership of different bicycle types and the other analyzing the influence of bicycle types on mode choice. During the data collection in 2016/2017, e-bikes were rare compared to conventional bicycles and were primarily owned by older age groups. While an above-average household economic status increases e-bike ownership, urban residents have lower e-bike ownership and usage rates. Daily cycled distances are higher for people with e-bikes; they extend cycling ranges, as their owner’s cycling mode shares are less sensitive to distance. Contrastingly, e-bikes do not seem to substitute car ownership. Compared to conventional bicycles, their use is more dependent on the season. Our results confirm findings from other countries and partially indicate cross-national transferability. Several diverging findings, such as that e-bikes increase cycling among young owners less and that age does not reduce e-bike use, suggest a closer look at how national framework conditions shape the uptake and use of e-bikes.

ABSTRACT. Evidence on public acceptability can support policy makers in their decision making around which urban interventions to implement. We compare the degree of acceptability for five built environment interventions targeted at active travel and quantify individual- and neighbourhood-level factors associated with greater acceptability of these interventions. We draw on cross-sectional data from the Targeting Healthy Eating and Active Living Environment survey of 27,162 participants living in 17 Census Metropolitan Areas in Canada. Our study focuses on the extent to which participants agreed with: increasing crossing time at intersections; building protected bicycle lanes; redistributing road space to pedestrians and cyclists; implementing traffic calming measures; and closing street segments to motor vehicles. Agreement with interventions ranged from a low of 44.3% for closing streets to a high of 73.5% for increasing crossing time. Across all interventions, people who were younger, women, born outside of Canada, had lower incomes, and used alternative modes to driving were more likely to express agreement with implementation of the interventions. There were few associations with neighbourhood-level variables. Our results provide evidence on levels of acceptability of selected transportation interventions in urban Canada as well as insight into determinants of greater acceptability.

ABSTRACT. Cycling network is an essential non-motorized infrastructure, whose air quality significantly impacts the cyclists’ respiratory health. With the revival of bicycle in recent years, respiratory exposure has gained wider attention. Taking the Siping neighborhood in Shanghai as an example, this study explores the distribution pattern of cycling-related NO2 exposure and the respiratory exposure on different cycling route choices. 1) The study takes mobile monitoring equipment to measure the concentration of NO2 in each street section before combining it with cycling trajectories data of shared bicycles to determine the distribution of NO2 exposure in the neighborhood. 2) It employs the Logit model to investigate the mechanism for route selection under the two scenarios of "perceived exposure" and "informed exposure," discovering a trade-off relationship between NO2 exposure quantity and time consumption: cyclists significantly prefer low exposure quantity and less duration under perceived exposure, while under informed exposure they prefer detouring for lower exposure risk. 3) It suggests measures to optimize the cycling networks for respiratory health. This finding demonstrated the spatial variation in NO2 exposure in the localized cycling network's. and indicates how pollution exposure affects the route choice, which might offer technical advice for creating a safe and practical cycling network.

ABSTRACT. This study investigates and models the bikeability at unsignalized intersections operating under non-lane-based mixed traffic conditions. For an extensive analysis, required data sets are collected from seventy well-diversified sites selected from different parts of India. Subsequently, the significant predictors of the user perceived bikeability are identified, which include the peak hour traffic volume, effective width of the approaching leg and conflicting traffic volume, etc. Incorporating all these variables, service prediction models are developed using step-wise regression and genetic programming (GP) techniques. The GP-based model has observably shown better prediction efficiency and higher reliability in the present context. The outcomes of these models denote the perceived satisfaction level of bicyclists at a given site on a letter-graded scale of A–F (excellent–worst). Besides, the model applications have exposed that more than 86% of the study sites are offering service levels of ‘C’ or inferior. Thus, the identified variables should largely be prioritized in the transport planning and development process to avail better bikeability effortlessly.

ABSTRACT. There are several existing evaluation methods for cycling networks, each with its set of indicators, none of which provides a complete picture of the cycling network performance. For example, most studies have relied only on the coverage as an indicator for network performance, while others focused on accessibility. Reviewing existing evaluation methods, it further appears that connectivity or discontinuity indicators have not been systematically identified and are missing from many evaluation methods. Discontinuities can be either intrinsic to the cycling facilities and the cycling network, such as changes in the type of facility or end of facilities, or related to changes in the cycling network environment, in particular the usually adjacent road network and motorized traffic. This paper formalizes the concept of discontinuities in the cycling network and the various causes of discontinuities, proposes a set of indicators to measure cycling network connectivity and the methodology to calculate them, including automated methods for geospatial data with the code available under an open-source licence. The automated method is applied to the comparison of the cycling network connectivity of four North American cities: Montreal and Vancouver in Canada, Portland, and Washington D.C. in the United States.

ABSTRACT. Park-and-Ride (P&R) systems are a consolidated traffic management strategy in the light of pressing demand for transportation solutions to improve traffic flows and promote sustainability to combat the climate crisis. The objective is to incorporate a population density function that, associated with a catchment area of a P&R facility, allows for the estimation of the potential demand of a P&R site. The potential demand is a valuable information in any P&R planning framework as it allows for the analysis of economic feasibility of a P&R site, as well as deciding on key design variables such as location of the facility, or level of service of the public transport serving the facility, among others. This research considers a continuous metropolitan area with population density in function of the distance to the city center. The catchment area of a P&R site is defined analytically by generalized costs of traveling to the city center using P&R or driving directly. Results show the variations of the catchment area and the population within it for different locations of the P&R site and different speeds and frequencies of the public transport servicing the facility, highlighting the importance of incorporating a density function to estimate potential demand

ABSTRACT. A current topic that has surfaced among Public Transport Companies (PTCs) is the selection of alternative fuels for their bus fleets. Both European and Italian regulations are pushing toward abandoning diesel fuel and the consolidation of alternative traction power sources, such as battery-electric vehicles, fuel-cell electric vehicles, and hydrogen-electric vehicles. The literature has provided some approaches toward assessing this selection such as multicriteria-decision-methods in some countries in the world. However, not enough specific attention has been paid to cost criteria, experts involved, and the type of service required. This study intends to address these gaps by applying an integrated method, which includes: (i) the Analytical Hierarchy Process (AHP) to calculate the weights of criteria; (ii) the ELimination Et Choix Traduisant la REalitè I (ELECTRE I) to find a good compromise solution among the fuel alternatives and (iii) a simple Weighted Sum Model (WSM) to refine ranking. This integrated method was applied in Italy involving a panel of experts from whom the data was collected. Different fuel alternatives for both urban and interurban services are discussed. The results could provide a useful tool supporting PTCs that wish to rationalise and prioritise bus fuel alternatives when deciding on fleet renewal.

ABSTRACT. Over the past two decades, environmental justice has been seen as an important tool for ensuring transportation infrastructure does not perpetuate a legacy of disproportionately impacting low income and/or minority communities in the United States. However, state-centered environmental justice research often focuses on quantitative methods for carrying out environmental justice analysis, focusing less on qualitative assessments of agency practitioners responsible for performing environmental justice work. We present a qualitative case study grounded in semi-structured interviews with twenty environmental justice and community impact assessment practitioners at state departments of transportation (DOTs) across the United States. Four major themes arose surrounding practitioner roles, agency context, tools/data availability, and assessment of impacts. Challenges and opportunities identified in the study provide state DOTs with operational lenses to evaluate how to further justice and equity in their project delivery processes.

ABSTRACT. We apply the concept of justice to transport project budgetary allocation. Using four major policy documents of a mobility advocacy organization, a 12-year open government budget data (2010-2021) and a 5-year transport program investments data (2021-2025), we mobilize the principles of equity and justice to assess the fairness of the funding allocated for road-based public transportation by the Philippine government. Our evaluation is based on the tripartite framework of unit-scope-shape of equity analysis. Our findings suggest a historical dominance of car-centric budgeting in the form of funding for road construction which tends to benefit only private vehicles. Furthermore, there is an over-reliance on rail projects, which hardly rectify the unmet mobility since they fail to address the massive supply shortfall despite the huge amounts of funding allocated. Given that the national budget is the clearest expression of the government’s priorities, activist engagement in the budget process is a promising venue for advocating equity in the domain of transportation.

ABSTRACT. Mobility as a Service, also known as (MaaS) represents a shift from traditional ownership-based modes of transportation towards access-based services. The success of MaaS, like any other service, depends on being user-centric. Still, due involvement of many stakeholders with different objectives necessitates establishing efficient governance to achieve the ultimate strategic goals for a sustainable transportation system. This study aims to demonstrate stakeholder’s views on the success factors for implementing MaaS and how governance affects the development of MaaS in countries with high share of expats where Qatar was chosen as a case study.

A workshop with different transportation stakeholders was held to brainstorm and discuss MaaS governance for the possible implementation of a MaaS system in Qatar, followed by a post-meeting questionnaire to evaluate MaaS stakeholder perception about their role in MaaS implementation and development. Although most of the stakeholders involved in the workshop thought MaaS could enhance the environment, sustainability, accessibility, efficiency, safety, and financial stability, many did not view data sharing positively. Improvement of physical infrastructure was considered an essential requirement for the success of MaaS. Subsequently, 50% of attendees agreed that Qatar's transport regulator(s) must run the MaaS system.

ABSTRACT. The principles of networked public transport are that systems should be designed to facilitate transfer between routes, thus providing for a minimal duplication of the system, and ensuring a net of public transport allows anywhere to anywhere access across the system. Theoretically networked public transport holds the best hope for developing a public transport system that can compete with the private car. Despite there being many policies that support networked transport systems, and demand the development of adequate alternatives to the private car, implementation of such systems has been limited. This paper reports on a review of 100 cities in China for implementation of networked public transport. The findings provide an opportunity to review how understandings of the principles of networked public transport are being interpreted and what implementation that is leading to in China. The paper demonstrates that the principles of networking can under some conditions be turned back to a logic of origin-destination public transport systems. The conclusion being that instrumental actions alone will not necessarily lead to a networked public transport system that can stand the test of time.

ABSTRACT. The development of the Makassar-Parepare railway line is an integral part of national development in encouraging regional economic growth, which the development progress has reached 90% and the planned operation will begin in 2023. Moreover, the strategic policies demand in providing an integrated network of infrastructure and services. The GIS mapping method to identify the connectivity between modes of transportation and the potential for the development of TOD and COD areas.

The results of the study found that there needs to be a harmonization of the programs among of the central provincial, city/district governments, as well as the role of the private sectors. Central and provincial government programs such as the bus buddy program/buy the service and BRT Maminasata, as well as urban/rural transport feeders. The bus buddy program/buy the service program is a pioneering transportation service that is subsidized by the central government at Mandai Station and Airport. Meanwhile, BRT Maminasata can connect the community to the metropolitan city of Maminasata. Arrangement of urban/rural transport routes by regency governments in realizing sustainable rail services to the activity centers. In addition, the potential stations with the policy of developing TOD and COD areas which has an impact on economic growth.

ABSTRACT. The value of travel time savings (VTTS) is one of the key issues in transportation studies, but there is little previous research on VTTS for children. In this paper, we report on a survey conducted with residents along the Hitachinaka Seaside Railway, which opened a station for children commuting to a newly built school, focussing on a comparison of VTTS between children and adults. As a result, many respondents answered that VTTS for children is more than that for adults. Half of respondents answered as the reason for their valuation that children's commuting time is as valuable as their parents' in terms of the opportunity cost. However, more than two thirds responded that saving children's commuting time is more valuable because concerns about children’s safety represent additional costs for parents. Also, there are quite a few respondents who evaluated children’s potential and their future income. If VTTS for children is higher than for adults, social benefits calculated on the assumption that there is no difference between children and adults are underestimated, distorting public investment decisions in transportation planning.

ABSTRACT. To promote electric vehicles, it is vital to know what impacts the preferences for electric vehicles over conventional fuel-based cars. To address this, a discrete choice experiment is developed and integrated into a survey. An online survey was conducted in Canada with 2062 valid responses. Different labels are designed for the survey to determine the most effective GHG information framing to increase the influence of such information on decisions. In this study, the influence of lifecycle emissions is considered. Three ensemble learning techniques are applied and they are compared based on prediction accuracy, and the most accurate technique is applied to determine the relative influence of variables on the intention to buy electric vehicles. Further, the interaction of variables is investigated using xgbfir. Subsequently, Accumulated Local Effect (ALE) is employed to examine the influence direction of top variables on the electric vehicle purchase likelihood. The results suggest that environmental attitudes and purchase price are the most influential parameters on the intention to buy electric vehicles. Moreover, those who are extremely worried about climate change, do not own a car, and self-identified as being at the top of the climate change stage of change are more likely to buy electric vehicles.

ABSTRACT. Under the background of requirements for China's new-type urbanization and the rapid development of railway construction, the comprehensive development of integrated Station-City development based on TOD has become the inevitable trend of the railway transport hub. China's railway passenger transport hub of the third-generation transportation complex has poor economic benefits and serious problems of separated Station-City. How to make up for the separation between stations and cities and strengthen the integrated development of station and urban functions has also become a prospective study. Based on the attributes of traffic nodes and urban places of railway passenger transport hub and the "3-Ring" theory, this paper strengthens the attribute of urban place of railway passenger transport hub, studies the spatial walking accessibility and functional value within the actual walking range of the first circle of large railway passenger transport hub, and analyzes the reasons for the poor walking accessibility of the third-generation railway passenger transport hub in China with the reference of the successful case of Station-City integration, put forward strategies for the problem.

ABSTRACT. Developing an extensive transit network is acknowledged as an effective way of alleviating urban traffic congestion, reducing the adverse impacts of the private car and improving urban liveability. In cities where there are a variety of modes available, individuals have the opportunity to choose between using the transit system and wider modes. In this research, we employ a discrete choice model to explore the transport mode choice of residents living in neighbourhoods near Underground stations in Beijing and London. Our findings show that only 35 per cent of local residents used the Underground as their main travel mode in Beijing compared to 45 per cent in London, whereas 28 per cent of people still drive private vehicles in Beijing compared to only 3 per cent in London. This is despite all having similar levels of accessibility with easy walking access to their local Underground stations. Travel mode choices can be attributed to various socio-economic characteristics, attitudes, built environment and travel factors – and there are significant differences in mode choice across population cohorts. Our research can help transport planners and policymakers to understand the complexity of travel mode choice and the myriad of factors involved in using public transit.

ABSTRACT. Dwell time is an important part of the total travel time in urban rail transit which directly impacts the system’s reliability and the line capacity. Advancements in microsimulation software packages allow us to develop a detailed model of rail transit stations and test various strategies and their efficiency to improve the dwelling process in urban rail operations. In this study, we developed dwell time models in PTV-Vissim and then, proposed a method to improve simulation results by including passengers’ walking behaviour and their interaction within the transit system. The Vissim’s user-friendly graphical interface (GUI) was used to develop the dwell time models and afterwards, the Vissim models were improved by accessing Vissim objects through the COM interface in Python to enhance the simulation performance. The results show that the basic dwell time model in Vissim can be improved and capture more realistic situations after considering passenger walking behaviours.

ABSTRACT. The purpose of this research is to provide a methodology for dynamically evaluating the significance of stations in a transportation network. This is accomplished through two distinct phases of activity. Firstly we propose a dynamic analysis of the underground transportation system of the city of Milan, Italy. Two data sets about passenger flows (both entering and leaving stations) are used to calculate the flows on links with a resolution of 1 minute. Data are processed through an ad hoc written assignment procedure. Secondly, a centrality index is calculated by using passenger flows (entering, exiting, and on-segments) as weights of the underground graph. After maps reporting the outcomes of those calculations are drawn, an image comparison is carried out by using image processing tools and different aggregation intervals, in order to investigate how the importance or exposure of each station changes over time. The findings demonstrate that over time, indices vary by station, with junction stations naturally having the highest values. By increasing the observation interval from 1 minute up to 30 minutes, index changes become progressively smoother suggesting that for certain applications (e.g., those concerning security), aggregating data could lead to misleading conclusions.

ABSTRACT. In a society undergoing “Work-style Reform” and where many workers can choose remote work, such as in Japan, it is important to understand the changes in commuting behavior of passengers and to forecast future railway demand based on the results in order to create appropriate railway policy. In addition, the number of remote workers has been rapidly increasing due to the impact COVID-19 pandemic. However, there are few studies which quantitatively analyze the changes using real passenger behavior data. This study focuses on the changes in commuting behavior of passengers related to remote work due to the impact of COVID-19. Using automatic ticket gate IC card data, the study identifies changes in the number of passengers, frequency of individual railway usage, origin-destination (OD) patterns, and departure time, by comparing data from before and after the COVID-19 pandemic.

ABSTRACT. This paper explores the obstacles wheelchair users in Montevideo face to travel by public transport and how improved universal design affects them. We compare two points in time: the year 2013, when 5% of the buses had universal accessibility (high floor with elevator or low floor with ramp) and the year 2021 when 51% of the buses employed universal design. To do so, in 2013 we designed a set of trips to actual destinations for different types of activities to compare time costs between wheelchair users and people without mobility restrictions. We estimated time costs again for the same set of trips using the 2021 transport network. For both 2013 and 2021, we found that, relative to people without mobility restrictions, wheelchair users had to travel longer times. Nonetheless, these differences diminished in 2021 compared with 2013. On-bus time remained almost the same for both years; the most important source of travel time reductions is the coupling time component. From a policymaking perspective, our findings indicate the importance of expanding universal design in public transport. They also highlight the need for a comprehensive approach to identifying different types of obstacles and how universally accessible infrastructure may help to overcome them.

ABSTRACT. A survey of older adults aged over 65 (n=247) was conducted in the city of Genoa “the oldest city in the oldest country” in Europe. We examined the influence of socio-demographics, travel behaviour, satisfaction with the neighbourhood and opinions of local public transport (LPT) services and the relevance of cost, time and comfort towards WTP for an annual subscription of LPT, with two scenarios of status quo and improved level of services. A segmentation analysis was conducted based on the mean values of the two WTP scenarios, followed by a linear regression model. Our findings suggest current pricing of the annual pass (345€) exceeds the value suggested by the respondents. The mean WTP for the status quo level of services (221.36€) was also much lower than the WTP if the level of services were to improve (304.07€). Having existing Women was found to be more likely to use LPT but also tended to be living alone with lower incomes. Off-peak hours, in the particular the afternoon, were also associated with higher WTP. Our findings suggest PTAs should devise more tailor-made approaches to improve user experience, user uptake and satisfaction of older adults in using LPT.

ABSTRACT. Around the globe, many cities suffer from car-based mobility patterns. Improving the sustainability of urban mobility is usually high on the agenda. In many cases, this includes approaches such as modal shift or city of short-distances, which need a change in mobility patterns of the inhabitants to become realised. Urban mobili-ty planning and policies usually have a strong focus on the urban scale. However, it is obvious that the mobili-ty patterns of urban residents are not at all restricted to the city they live in. In this paper, we are particularly interested in how far non-urban activities and relations contribute to car-use and car-ownership of urban resi-dents. This is linked with the questions for what reasons, on basis of which motivational triggers, citizen’s travel out of the city. We draw on research on personal social networks, to understand the specific meaning that activities or relations outside the city have for the life of urban residents. Based on empirical data from an interview study from Karlsruhe, Germany, we illustrate that activities or relations outside the city quite often are of particular importance for the individuals. For the governance of a mobility transition, an urban focus is necessary but not sufficient.

ABSTRACT. Automated vehicles (AV) have the potential to cause profound changes in future mobility systems. However, it remains open whether AVs will trigger more or less sustainable development trajectories in the mobility sector. In this paper, we argue that social acceptance of AVs is a crucial factors influencing the direction AV developments. We propose a conceptualization that distinguishes different dimensions of social acceptance. We apply this approach to an interview study with citizens in Karlsruhe (Germany), which focuses on aspects of social acceptance of automated mobility services.

ABSTRACT. Japan’s motivations for implementing Mobility-as-a-Service (MaaS) are diverse, and its vision and objectives are very clear and target oriented. The government has focused on deploying MaaS to address the mobility issues of its declining and rapidly aging population. However, whether these projects can achieve equity goals and assure accessibility to all is under question. Therefore, this paper first aims to define equity objectives and their indicators to achieve such mobility solutions with MaaS. Next, it seeks to explore equity impact in two different MaaS cases developed and implemented by the government and the private sector. Accessibility, affordability, and inclusivity have been chosen as equity objectives in this study, along with six different equity indicators to measure the equity evidence of two MaaS projects. Questionnaires were prepared separately for each case, and the heads of these projects were interviewed about equity concerns. The findings indicate that equity is not highly or may not even be prioritized in both MaaS cases. Nevertheless, MaaS projects in Japan have distinct characteristics to achieve specific goals. Therefore, this study suggests conceptual and practical ways or implications for incorporating transportation equity goals into these newly implemented MaaS services in Japan.

ABSTRACT. This paper aims to quantify the effects of different traffic calming devices on the noise generated by the traffic flow. The noise levels of a particular vehicle passing at and after the traffic calming devices were measured simultaneously while maintaining most of the site characteristics and traffic data similar. This research will ascertain statistical analysis of the noise levels emitted by vehicles at the traffic calming devices. The 24 traffic calming devices selected included 12-speed humps and 12-speed tables for 2-lane and 4-lane at 3 different zones (residential, school, and industrial) in multiple areas in Doha City, Qatar. The data collection conducted for 8 hours per site showed that the observed mean noise levels for all the sites exceeded the WHO standards [53 dB(A)] and Qatar standards [55 dB(A)] permissible noise levels because of the vehicle fleet mix. The analysis indicated that traffic calming devices generated comparatively higher noise than the control point, meanwhile, speed humps emitted more noise levels than speed tables. Further, it was statistically proven that traffic calming devices in 4-lane emitted higher noise levels than those in 2-lane. In addition, the industrial zone was observed to generate higher noise levels than the residential and school zone.

ABSTRACT. In 2017, the Traffic Act was revised, and older adult drivers who were involved in accidents had to undergo a simple test to analyze their cognitive function. Therefore, in this study, I conducted a driving experiment with the help of drivers of more than 65 years of age who were normal, who had mild cognitive impairment, and who had dementia to compare their driving skills. Further, we observed the driving characteristics using a closed training course in a driving school. The cognitive functions of the drivers were evaluated using two kinds of screening tests. Further, we analyzed the relation among the scores of screening tests, the driving customs (obtained by interview) and driving behaviors of the drivers. The driving behaviors at intersections or while parking were not observed to differ significantly; further, almost all the older adult drivers behaved without safety confirmation. Majority of the older adult drivers did not stop and verify the surroundings at intersections. On the other hand, the behavior in lane change and obstacle avoidance on midblocks was different between MCI/dementia drivers and normal drivers significantly. All the MCI drivers were observed to change the lane without switching on the blinkers.

ABSTRACT. This research examines the perspective of teenagers on cycling and urban spaces by evaluating four different participatory research formats. It aims to discuss the intersection of the salutogenic approach with urban planning. Therefore, a living lab experiment called the bike buddy (BB) program was created. First results indicate that program participants feel a lack of connection to their surrounding streets but have a natural tendency to design public space following the salutogenic idea when given the space to express their ideas.

ABSTRACT. In-vehicle research is scarce. Therefore, this research aims to determine and compare the CO2 levels as an indicator of air quality in subway wagons and transit buses in the city of Montreal, with field observations from 2021-2022. Data were collected in units of the Société de Transport de Montréal with a NDIR monitor, in trajectories covering three subway and four bus routes. Data consists of hundreds of readings on CO2 levels in one-minute intervals throughout the trip. Additionally, we record the unit’s occupancy level, natural ventilation, and air-recirculating status. Using multilevel mixed-effects models, we identified the salient factors affecting CO2 levels and compared the results between modes.

Results suggest that levels in buses are approximately 26% higher than in subways. Furthermore, the levels show a direct correlation with the occupancy rate, as semi-crowded and crowded units have levels 5% and 15% higher than not-crowded units. In buses, air-recirculating systems are positively correlated with CO2 levels; units with the air conditioning system on show levels 18% higher, and those with heating have levels 19% higher than buses with both systems turned off. Preliminary data analysis shows CO2 levels 8% higher during the colder months (November through February), confirming a seasonality effect.

ABSTRACT. As a vital aspect of individual’s quality of life, mental health has been included as an important component of the U.N. Sustainable Development Goals. This study focuses on a specific aspect of mental health: depression, and examines its relationship with commute patterns. Using survey data from 1,528 residents in Beijing, China, we find that every 10 additional minutes of commute time is associated with 1.1% higher likelihood of depression. We test for the mechanisms of the commute-depression link and find that commute is associated with depression as a direct stressor rather than triggering higher work stress. When decomposing commute time into mode-specific time, we found that time on mopeds/motorcycles has the strongest association with depression. Moreover, the commute-depression associations are stronger for older workers and blue-collar workers. Hence, policies that could reduce commute time, encourage work from home, improve job-housing balance or increase motorcyclists’ safety would help promote mental health.

ABSTRACT. The expansion of mass rapid transit systems such as the metro in urban metropolitan areas is expected to moderate the problems of congestion and public transport overcrowding. It is crucial to devise measures to attract private vehicle users towards these modes to make them economically and financially viable. Positive perception of travel wellbeing and high trip frequency can lead to long term habitual inertia and prevent commuters from shifting towards new sustainable alternatives. To support transport policy making in promoting sustainable modes, this study mainly investigated the association of existing travel wellbeing and trip frequency of private vehicle commuters with their mode shift behavior towards an upcoming metro system in Mumbai Metropolitan Region (MMR), while some external changes occur in the transport system attributes. A well designed stated preference survey was conducted and 2400 responses were collected from 217 private vehicle commuters (two-wheeler and car). Results indicate that the commuters value metro onboard comfort the most, followed by transfers, travel time, and waiting time. Existing travel wellbeing is found to be insignificant in determining the mode shift behavior, although the association was negative. Furthermore, regular private vehicle commuters showed a significant shifting propensity towards the upcoming metro.

ABSTRACT. Developing countries have made major investments in urban public transport infrastructure aiming at improving accessibility and the quality of life of citizens. However, besides its evident benefits (improved accessibility and increasing land value), these interventions can affect the socioeconomic dynamics in the zones of influence, generating externalities such as the displacement of the original residents. This study aims to evaluate relocation decisions after the implementation of a new cable car, which might be associated to gentrification. The study zone is located at the urban fringe of Bogotá, and is characterized by low-income, poor accessibility, and originally self-built-in settlements. The analysis is based on the estimation of discrete choice models with stated preferences data collected after the cable started operations. The framework allows to evaluate the willingness to relocate for adults living in the cable’s catchment area, accounting for heterogeneity in the preferences by sociodemographic attributes and household ownership, considering the hypothetical availability of housing alternatives with varying prices and accessibility to transport and police stations. Results suggest that willingness to relocate is low, while preferences between house owners and renters differ. The research contributes to the literature addressing the impacts of alternative public transport infrastructure in developing countries.

ABSTRACT. Mobility as a Service (MaaS) – bundled mobility services accessible on-demand and on a single platform – has been a popular research topic in recent years. Most MaaS studies, however, are embedded in the context of developed cities, where most of the existing MaaS schemes are operational. The purpose of this paper is to give an overview of first findings in the Global South. We aim to answer the following questions: Is MaaS likely to gain traction in the Global South? How does MaaS in the Global South differ? Can MaaS mitigate transport problems in the Global South? Following a systematic literature search, we identified 23 relevant papers that were included for full-text analysis. A qualitative synthesis of these papers suggests that: (i) there is a considerable demand for integrated, app-based mobility services; (ii) however, different regulatory frameworks, available infrastructures, and user preferences require adjustments; and (iii) MaaS can indeed promote more sustainable mobility behavior. The results are of interest to policymakers and transport professionals in order to plan MaaS schemes in developing cities. We also identify knowledge gaps and outline research opportunities to guide future studies in this incipient field of research.

ABSTRACT. The current study suggests a user satisfaction-based approach to prioritise attributes influencing walk accessibility to metro stations in Delhi, India. The target user group of the present study includes metro users who access the metro stations by walking. Responses from 466 such users are collected using smart tablets through face-to-face interviews. User satisfaction ratings towards twelve walk accessibility influencing attributes identified in the study are recorded on a six-point Likert-type rating scale. The study engages a comparative Multi-Attribute Decision Making (MADM) approach comprising of three prominent methods, namely, Relative to an Identified Distribution Integral Transformation, Grey Relational Analysis and Technique for Order Preference by Similarity to the Ideal Solution to analyse the collected perception database and prioritise the attributes based on user satisfaction. The study outcomes identify ‘Extreme Weather Conditions’, ‘Illumination’, ‘Universal Design Considerations’ and ‘Safety and Security’ as the poorly performing attributes based on user perception and require immediate interventions. Spearman’s rank-order correlation analysis is performed to compare the attribute priority ranks derived from the three methods. The research findings can be useful to transportation planners, policymakers and enforcement officials in formulating and implementing strategies to allocate funds based on user-identified priorities for improving walk accessibility to metro stations.

ABSTRACT. Increasing use of private cars has caused several issues ranging from traffic congestion to air pollution. Although various studies confirmed the significant impact of urban form on public transportation (PT) demand, these studies are mainly limited to Global North or China. This study aims to address this gap and capture the nonlinear contributions of various urban form elements in choosing PT mode in one of the developing countries considering spatial heterogeneity. For this purpose, by reading the previous studies, potentially effective elements of urban form were identified. Using data from a city in Iran, random forest regression was developed as a powerful machine-learning method. The proposed model achieved proper goodness of fit but, more importantly, allowed us to explore the impact of urban form on PT demand based on a game theoretic interpretability technique. We found that the directions of associations for most variables aligned with other studies in other parts of the world. However, there were several variables whose directions of association differed at origin and destination; moreover, some variables’ direction of association was opposite that of others. Therefore, the effect of each variable on PT demand must be assessed on a case-by-case basis and based on origin-destination.

ABSTRACT. In many cities in developing countries, motorcycles play a critical role in the urban transport system. Besides, private cars are becoming preferable modes to those who afford them. The use of individual transport modes contributes to urban sprawl and challenges the development of new public transport systems. In recent years, there has been much interest among urban and transport planners in integrating urban transport and land development planning. This study aims to understand the relations between urban and transport development, formulate a concept for integrated transport and urban development and propose strategies for integrating urban and transport development in so-called motorcycle-dependent cities. A literature review is conducted to identify the interactions between transport system and urban form elements and the problems of uncoordinated transport and urban development in Asian developing cities. The case study approach is employed to argue and pre-select candidate measures, which could potentially form strategies for integrated transport and urban development. Experts in the field of transport and urban planning and management are consulted to confirm and prioritize the measures, using multi-criteria assessment. Then, strategies for integrated transport and urban development are formed by bundling measures.

ABSTRACT. Despite growing research on transport and life satisfaction, studies from and about urban Global South contexts are still scarce. Using a peripheral low-income community in Bogotá (Colombia) as a case study, this paper examined how life satisfaction relates to mobility measures, neighborhood perceptions, and social capital. We interrogate how transport-driven urban transformations such as a recent cable car system (TransMiCable) influence perceived and measurable mobility effects on life satisfaction. We propose six hypotheses to understand such relationships before and after TransMiCable implementation, considering control and treatment groups. Thus, we defined seven latent variables (i.e., life satisfaction, neighborhood and transport satisfaction, security, infrastructure, interpersonal trust, and institutional trust) and three objective measures (leisure activity participation, travel time, and transport affordability). We tested the hypotheses using a multiple-cause multiple-indicator modeling approach, which allowed us to identify how an intervention impacts perceptions and mobility indicators. Results showed the principal determinant of life satisfaction was leisure activity participation. Transport and neighborhood satisfaction were also important determinants of life satisfaction. The effects of security, infrastructure, and institutional and interpersonal trust had indirect, positive, and statistically significant effects on life satisfaction, while travel time and transport affordability had negative and significant effects on life satisfaction.

ABSTRACT. Though transport has been stressed in many sustainable development strategies, the understanding of social sustainability in the transport sector remains inadequate. Transport social impact assessment (SIA) at local level lacks a systematic guidance. This research take China as a sample of large developing country to explore transport SIA practices in different-sized cities. Through a review of transport documents, this paper identified that Chinese cities can be divided into 5 groups according to the characteristics of transport SIA practices, including social impacts covered, level of details, indicators and methods, etc. The quality of transport SIA is largely related to local economic condition, but is also affected by factors such as preference polices. Interviews with Chinese transport practitioners were then introduced to further identify the gap in transport SIA in smaller-sized cities and potential improvements. Based on the interview analysis, key aspects for improving transport SIA practices in China can be summarised as (1) highlighting local priorities of transport SIA; (2) establishing systematic frameworks which allow local authorities to address local priorities and specific concerns in transport SIA, and establishing specific databases for collecting local evidence; (3) setting up criteria according to the development local conditions for selecting SIA indicators.

ABSTRACT. A high percentage of rail ridership in India is facilitated by the superfast express (SE) trains that operate across and within the 17 zones of the Indian Railways. While large cities with SE train stations in zones have some form of first/last-mile transport connectivity and are considered safe to access during nighttime or early wee hours, several other stations do not have this privilege. Therefore, considering the 9 pm – 7 am period as not-so-friendly hours of travel, and the 7 am – 9 pm period as the desired hours of travel, analysis shows that the inequalities in centrality and accessibility exist between the zones more than between the stations within a zone for these two periods. If evaluated for accessibility, there were five zones of the South Western Railway, Southern Railway, East Coast Railway, South Eastern Railway, and Northern Railway that would experience deterioration in accessibility for the same desired hours of travel. It was also found that the investment made by the Indian Railways across the 17 zones between 2016 - 2020 resulted in positively impacting the total employment growth in the zones, and it was significant.

ABSTRACT. This paper analyses the 15-minute city approach in a context where it is a reality due to mobility restrictions. We problematise the approach by considering urban functions and amenities of four informal settlements in the Barranquilla-Soledad conurbation in the Colombian Caribbean region. To do so, we propose a mixed-method approach to understand the limitations and potentialities of the 15-minute city idea. We used spatial and quantitative methods to evaluate proximity, diversity, density and digitalisation in these settlements. Also, we applied a mobility survey to 300 participants to characterise their sociodemographics and travel patterns. Then, we estimated logit models to understand the characteristics of those performing activities within and outside the 15-minute threshold. The results of the analysis suggest that, unlike proximity, diversity and density, digitalisation is the only dimension that is barely present in the current practices and conditions in the study areas. The mobility analysis about activities accounting for socioeconomic characteristics shows that a planning guideline addressing hyper proximity requires attending to differential access needs. Although most of the participants already experience the hyper-proximity precepts of the 15-minute city and perform their activities in their home vicinity, these activities are not performed there by choice but by necessity.

ABSTRACT. This paper investigates the market dynamics triggered by the 2010 bankruptcy protection of Japan Airlines (JAL). Our analysis suggests that JAL downsized its overall operations, leaving relatively thin routes even though there were fewer competitors and slightly higher yields in those thin markets. The airline nevertheless increased the yields and flight frequencies in the consolidated network more significantly than its rival airlines did. Following JAL’s bankruptcy, Japanese carriers focused on improving yield and frequency, and the competition between the duopoly airlines (JAL and All Nippon Airways (ANA)) became less effective. In comparison, low-cost carriers (LCCs) and smaller airlines continued to exert significant competitive pressure on the market despite their small market shares. These patterns are different from those observed in the US, where a huge domestic market is served by a large number of competitive airlines. Overall, our analysis suggests that the Japanese government’s support of JAL’s restructuring efforts was appropriate. However, there is evidence that the JAL-ANA duopoly became less effective in maintaining market competition. The Japanese government should more actively explore ways to provide a level playground to LCCs and smaller airlines so that enhanced competition can promote airline efficiency and services in the long term.

ABSTRACT. We investigate airport competitiveness for air cargo hub airports to find how COVID-19 impacted the perception of the air cargo business environment. We collected data for the competitiveness measurement using structural equation modeling and the difference-in-difference analysis before and after COVID-19 for freighter forwarders and air cargo experts’ perceptions, especially at Incheon International Airport. Previous studies have considered the perspective of competitiveness of airports based on the assessment of either airlines or passengers. This current study used 27 variables to evaluate the air cargo business environment on airport competitiveness based on respondents’ perspectives. We found that three attributes—efficiency and infrastructure investment, flight service, and location and accessibility—make for a vital air cargo hub airport’s competitiveness. The freight forwarders’ and experts’ perceptions of air cargo movement, airport competitiveness, and strategies have not changed significantly between pre- and post-COVID-19.

ABSTRACT. Many airports have evolved into “airport cities” by exploring those non-aviation activities that lie outside the traditional boundary of airport concessions, such as hotel, convention, shopping center. Airport city, or referred as airport mall, thus directly competes with the downtown stores, given their increasing service substitutability. Both air passengers and local residents can consume at either the airport mall or downtown stores. We model the government’s optimal airport city regulation, when it has incomplete information on the operating cost and service quality of the airport city. The analytical results suggest that, the airport can earn an “information rent” when the government has incomplete information on the airport mall’s operating cost. Such incomplete information leads to opposite distortions on the airport aeronautical charge and airport mall shopping price. It proves more socially efficient for the government to offer airport an “information rent” through a higher aeronautical profit, such that the direction of airport price distortion depends on the price elasticity of air travel demand. Under incomplete information, the regulation from either the central or local government could lead to worse entire/local welfare than doing nothing.

ABSTRACT. This paper studies theoretically the competition between an airline and a high-speed rail (HSR) operator by extending to consider that, similar to HSR, the objective function of the airline is also a weighted sum of profit and social welfare. This specification captures well the air-HSR competition in China. Since China has the largest HSR market and the second largest air transport market around the world, a simplified model characterizing better the air-HSR competition in China is worthy of investigation. We find that, first, a larger weight of the airline on welfare increases the equilibrium air traffic and flight frequency, while it decreases the equilibrium traffic volumes and service frequencies of HSR in all markets. Second, a paradox is found between the airline’s objective and social welfare. Specifically, when the weight of the airline on welfare is sufficiently large, due to the demand- and supply-side network effects, a larger weight of the airline on welfare may undesirably reduce social welfare. Third, the welfare distribution between different markets is uneven. A larger weight of the airline raises the surplus of consumers in the long-haul major market, while it reduces the consumer surplus in the short-haul regional market. Finally, policy implications are discussed.

ABSTRACT. In this paper, we use an original and rich dataset (containing yearly data on 186 airlines worldwide, for the period 2007-2019) to empirically test the impact of airlines’ government holdings on performance using a 2SLS approach to control for potential endogeneity of government holdings. We show that the impact of government holdings on airlines performance is non monotonic and quadratic. However, the shape of the relationship for African and Middle East airlines is different from the one for airlines from other regions of the world. We finally estimate an optimal level of government holdings for our sample.

ABSTRACT. This paper reviews the methods applied to regulate airports and their impact on efficiency. Our review reveals that different market structures and regulatory environments have varying impacts on efficiency. The majority of studies find that airport regulation has proven to encourage technical, financial and cost efficiency, however a few find negligible to negative impact on efficiency levels. We find that dual-till incentive regulation is more effective in promoting airport efficiency in comparison to rate-of-return regulation. We also find that light-handed regulation leads to efficient airports but does not necessarily result in the cheapest airports in terms of aeronautical charges. Finally, we find that many aspects of airport regulation and efficiency have not been assessed and require further research.

ABSTRACT. We study a pilot scheduling and assignment problem (PSAP) to vessel transiting the St. Lawrence River considering different measures to rank the pilots to be assigned over four different pilot stations along the maritime corridor while it typically happens once in the port at previous works. To do this end, two different strategies are explored; the current approach and a new one. The current strategy applies the number of pilotage and waiting time as a pilot satisfaction level factor while the proposed strategy combines nine different measures including working time, waiting time, and skill difference as pilot satisfaction level factor. A case study based on the context of the St. Lawrence River from Les-Escoumins to Montréal is used. The results show the standard deviation value obtained by the proposed strategies is reduced in all measure, as a result, the new proposed approach makes a more balanced schedule for pilots.

ABSTRACT. This study proposes analytical tools to predict marine casualties in order to contribute to improving maritime safety and preserving maritime and coastal heritages. Maritime casualties can have devastating consequences, even more when they involve dangerous goods, causing loss of life, damage to the environment, and economic losses. Using a global dataset of maritime casualties from 2010 to 2019, this study applies both a machine learning technique and a statistical approach based on rare events Fourier’s distribution to predict the risk of an accident. Using the Tyrrhenian area as a case study, the results show that the proposed tools are able to predict the probability of a casualty occurring with a good level of compliance and can represent a valuable help for decision-makers and stakeholders, who can use the results to identify regions at risk of maritime casualties and take steps to prevent them from occurring.

ABSTRACT. Shipowners need to prepare for low emission fuel alternatives to meet the IMO 2050 goals. This is a complex problem due to conflicting objectives and a high degree of uncertainty. To help navigate this problem, this paper investigates how methods that take uncertainty into account, like robust optimization and stochastic optimization, could be used to address uncertainty while taking into account multiple objectives. Robust optimization incorporates uncertainty using a scalable measure of conservativeness, while stochastic programming adds an expected value to the objective function that represents uncertain scenarios. The methods are compared by applying them to the same dataset for a Supramax bulk carrier and taking fuel prices and market-based measures as uncertain factors. It is found that both offer important insights into the impact of uncertainty, which is an improvement when compared to deterministic optimization, that does not take uncertainty into account. From a practical standpoint both methods show that methanol and LNG ships allow a cheap but large reduction in emissions through the use of biofuels. More importantly, even though there are limitations due to the parameter range assumptions, ignoring uncertainty with respect to future fuels is worse as a starting point for discussions.

ABSTRACT. Shipping of freight by sea is the pillar of international trade. Maritime transport has its crucial nodes in the port systems. The main characteristic of ports in the context of maritime transport, is given by the port time of container ships from arrival to departure in/from the port, after having completed the loading/unloading operations. It is therefore necessary to know how the different attributes of the ports influence the port times of the ships. The most important attributes are then discussed and a multiple linear regression model is estimated. The results obtained are interesting because they highlight the role of attributes that affect the entire port system such as the depth of the docks and not the processing of the single ship. The results are important because they make it possible to identify overall investments relating to the single port system in addition to the usual actions to optimize the processing of individual ships.

ABSTRACT. This paper introduces a vessel voyage schedule planning problem for maritime ore transportation arising from a real-world project in Boffa, Guinea. Due to variable weather conditions at sea and changing loading/discharging time, delay of vessel arrivals at the loading port often occurs which interrupts the ore loading operation and further impacts the yearly throughput of ore transportation. Uncertainty of vessel voyage has to be considered in order to ensure continuous vessel arrivals and uninterrupted loading operation at the origin port while minimizing the operational cost. In this study, we develop a bi-objective mixed integer linear programming model that minimizes, for the entire vessel fleet, the total voyage cost and maximizes the total transfer volume of ore simultaneously. To determine the schedule of every single voyage, a chance-constrained formulation is developed to obtain a robust voyage schedule that ensures an on-time voyage with a required probability. We introduce a series of valid cuts for the model formulation and employ an NSGA-II method to provide multiple excellent solutions for the project managers. The computational experiments confirm the effectiveness of the valid cuts, and demonstrate that the obtained vessel voyage schedule is more robust and outperforms manual decisions.

ABSTRACT. The anchorage of dry bulk ships in Vancouver's trades raises issues that garner national attention. The characteristics of the grain, coal and fertiliser industries that account for the majority of the ship waiting time are identified. The contracting and logistics conditions contributing to the level of anchorage are described. Simulation is used to identify the critical sensitivity of anchorage levels to the variability of ship loading times. The incidence of the environmental and economic costs is examined under voyage charter party terms used in the trades. Significant costs of ship waiting time, beyond demurrage paid, are recognised for ships in the grain trade, in which SSHEX terms are used. These costs are not reflected in the logistics decisions of the trade.

ABSTRACT. The weather route can be used in determining the optimum route for vessels, it can allow for optimization of the duration, the distance, or the fuel consumption. In recent years, while most of the technologies have improved significantly, weather routing is still not maintaining the pace. The objective of the present document is to understand if a specific concept (e-navigation) can affect this optimization approach in the near future. To perform weather routing, seafarers today are called upon to merge non-homogeneous types of data (hydrographic, weather and oceanographic, etc.) that are delivered on board over different devices and in different formats. Once e-navigation will be operative, the relevant marine-related data will be available on a common device in a standardized format (this format will be based on a standard developed by the International Hydrographic Organization (IHO) whose name is S-100). The goal of the present document is to investigate how navigation can take advantage of S-100 in terms of weather routing and route optimization. Various S-100-based products will be analyzed as a function of various optimization algorithms to forecast if e-navigation has the potential to be beneficial when dealing with the weather routing problem.

ABSTRACT. The paper presents a multi-objective model to solve an integrated vessel transit planning and pilots scheduling in the St. Laurent River. The objectives of the problem are minimization of the fuel cost, the wait time and the pilotages cost while considering flexible departure time, weather (tide and current), and legal and safety restrictions. As a case study, the proposed model is applied for finding the optimal transit in the St. Lawrence River, Quebec, Canada. Results show that transits with flexible departure time and flexible speeds could have lower cost. Weather conditions, especially tide and current have an important impact on transit cost. Results proved that total cost could be significantly reduced.

ABSTRACT. Since January 2020, the International Maritime Organization has imposed new regulations to reduce greenhouse gas emissions from ships. Meeting these regulations requires the optimization of ship performance during voyages, including the fuel consumption. The objective of this study is to approximate the fuel consumption for a set of sister bulk carriers taking into consideration their historical routes and the weather data in order to insert it in a ship routing tool. We have developed a predictive model of fuel consumption for these bulk carriers using a multiple linear regression model considering the speed of the engine and the weather conditions. The results show that the estimated fuel consumption of the studied bulk carriers is strongly affected by the speed of the engine and the meteorological conditions. The developed model can predict fuel consumption accurately for more than 80% of the voyages of the dataset with a MAE error lower than 1.5 metric tons per day and a RMSE error lower than 2 metric tons per day making it useful for ship routing purposes.

ABSTRACT. It is important that railway networks are monitored and maintained to ensure good function and safety. A tool, known as Interferometric Synthetic Aperture Radar (InSAR), is used by researchers, geo-technicians, and engineers for monitoring and measuring ground deformation over a large area remotely with high frequency and accuracy. The purpose of this study has been to evaluate the use and feasibility of the InSAR technique for track condition monitoring and compare it to conventional track condition monitoring techniques. Malmbanan, in Sweden is used as a case study for this project. Coordinate matching of measurements from the provided Persistent Scatterer Interferometry (PSI) InSAR data and Optram data from survey trains were performed. Then measured changes over different time spans within the two systems were overlapped and classified with different thresholds to see if there is a correlation between the two systems. An extensive literature review was also conducted in order to gain an understanding of InSAR technologies and uses. Results indicate that InSAR has a great potential in monitoring ground deformation of railways, and compliments traditional track condition monitoring techniques.

ABSTRACT. Current logistics and transportation activities are unsustainable in the long run, prompting several authors to focus their efforts on developing solutions. However, the majority of the proposed solutions are aimed toward a more urban setting, disregarding rural or sparsely populated areas since they present numerous and difficult challenges.

In this context, the EU adopted a strategy based on the Physical Internet paradigm to achieve a sustainable logistics and transportation system by 2050. One solution focuses on the reuse of railway lines that are currently underutilized or unaffected by the introduction of autonomous shuttles that transport passengers and small packages. However, no analysis of the capacities provided by the Physical Internet for the application of these shuttles has been conducted to date. As a result, the purpose of this article is to conduct an analysis of the challenges and opportunities of the rural context, as well as the potential solutions offered by the Physical Internet to address them.

ABSTRACT. In the early decades of the 21st century, railways had an established, small (relative to road transport) but significant share of the overall transport market, providing a combination of high-speed, high-capacity passenger services and high-volume, long-distance freight transport, with the balance between passenger and freight traffic varying by location. The passenger railway market was severely disrupted from early 2020 by the Covid-19 pandemic; traffic volumes have since recovered, but work-related travel volumes (and, importantly, revenue) have not returned to their pre-Covid levels, putting pressure on railways and their funders to restore revenue and/or cut their costs. As an energy-efficient and low-Carbon (assuming high levels of usage) mode of transport with a potentially vital role to play in addressing the climate crisis, increasing passenger and/or freight volumes (preferably via modal shift) and total revenue is clearly the preferred option, ideally in parallel with increased efficiency and reduced unit costs. To meet these objectives, the railway industry needs to provide high-quality, comprehensive and integrated (including other, complementary modes) transport options that are easy to plan and use, and which provide users (and funders) with good value for money.

ABSTRACT. Hazardous materials (hazmat) transportation is critical to the growth of modern societies, and railroad is one of its important modes, particularly in North America. Although railroads handled one-third of all U.S. exports and roughly 40% of its long-distance freight volume in 2022, academics have yet to devote significant effort to propose risk mitigation policies for them. Thus, an incentive-based strategy, adding subsidy to railroad links, will be addressed in this study to control the risks of hazmat transportation networks. For doing so, a bi-level multi-commodity optimization model is developed and solved by a heuristic solution approach. The methodology is tested on two small-sized instances and the results are reported.

ABSTRACT. One of the key advantages of separating a railroad-highway at-grade crossing are emissions reductions resulting from elimination of idling/waiting of vehicles at a crossing while trains pass. Monetized benefit of emissions reductions is often seen as motivation for separation, but its complete evaluation is often very laborious and time consuming. The California Public Utilities Commission (CPUC) policy that uses a formula for selecting a crossing in California for separation lacks considerations for benefits-cost aspects of the resulting emissions reductions. This paper presents a benefits-cost-based indicator, in conjunction with emissions reductions potential indicator, to quickly identify crossings with high benefits-cost indicator for emissions reductions when separated. The indicator represents the magnitude of benefits-to-cost ratio that can be realized with the separation. Analysis with ten key at-grade crossings in California showed that the crossing recommended for separation by the benefits-cost-based approach adopted in this research differed from the one with the existing CPUC policy. Therefore, if benefits-cost considerations of emissions reductions is important, this paper can serve as a very useful supplement over the existing CPUC methodology for quickly determining which crossing to separate from several thousands of railroad-highway at-grade crossings in California and elsewhere in the United States.

ABSTRACT. This study aims to describe the risky driving behaviours observed around elementary schools during morning drop-off times, as well as the physical environment and active transportation proportions at schools with the most and fewest observed risky driving behaviours.

Research assistants in seven Canadian municipalities observed risky driving behaviours and active school transportation at 552 elementary schools during morning school drop-off times in Spring 2018 and 2019 . Proportions of driving behaviours, overall and by type, were analyzed for each municipality. In addition, schools in the highest decile and lowest decile of risky driving behaviours were contrasted in terms of proportion of active school transportation, physical environment and presence of school crossing guards.

Risky driving behaviours were observed at 98% of the 552 schools, ranging from 92% of schools in Laval to 100% in Calgary. The most frequently observed risky driving behaviour across all sites was dropping child off on the opposite side of the street with the child crossing midblock with no traffic controls (80%). Schools with the fewest risky driving behaviours had more favourable Active Living Environment scores, more curb extensions present, more restricted parking signage, more access to school entrances, and had child crossing guards present less often.

ABSTRACT. The influx of motorcycle as unconventional mode of public transportation in cities and rural areas in Nigeria is alarming and exacerbated, hence the paper examined the influence of motorcycles crashes, on the total vehicle crashes, within the context of enforceability of safety rules and regulation of this paratransit mode of travel. Methodology adopted include data on variables on road transport for the period of Ten (10) years that are ; total crashes ;total motorcycles and total vehicles involved in crashes, therein both descriptive (percentages) and inferential statistics (Regression model) were employed. Results showed that motorcycles have a considerable influence in the total number of vehicles that involved in crashes in the studied years with 17.6 percent, which was significant at 95% confidence interval. It was recommended that holistic policy framework approach, that is, dynamic, socially acceptable, logically implementable, legally bidding, economically feasible and effect measurable, should be adopted that will collaborate both National and state governments, as well as the Unions of the motorcycle owners and operators, with each stakeholders performing their respective responsibilities, such that the inbuilt mechanism for the enforcement and monitoring activities will be achieved and in turn promote sustainability of the road map.

ABSTRACT. The present study investigates the impact of different acceleration styles collected from a sample of human drivers on the vehicle’s energy performance in real-world trips. The variations in CO2 emissions according to different acceleration patterns are benchmarked to real-world trips from a driving campaign that involved 20 drivers on the same reference vehicle. The paper builds on a previous work that benchmarked the correlation between CO2 emissions and acceleration behaviour to the standard homologation Worldwide Harmonized Light Vehicles Test Cycle (WLTC). The current work extends the application to real-world conditions, modifying the acceleration events of real-world trips according to the driver’s acceleration attitude and subsequently simulating the energy performance, specifically the CO2 emissions. The heterogeneity of the driver’s acceleration style is characterised by the vehicle-Independent Driving Style metric (IDS), which represents the driver’s acceleration aggressiveness. The results confirm a significant impact in CO2 emissions of the acceleration behaviour, leading to differences above 10% when a consistent acceleration style is followed for the whole trip. The impact is substantially reduced (± 1 CO2 g/km) when considering the broader stochasticity spectrum of the human acceleration style.

ABSTRACT. Regions with a subarctic climate are characterized by long winters, heavy snowfall and extremely cold temperatures. Weather conditions can change rapidly and are subject to a high level of seasonal variation. These factors influence drivers’ decisions regarding the trips they have to take. Existing literature has confirmed that adverse weather decreases traffic volumes, but no study has yet employed comprehensive and historical data from a subarctic climate. This article examines the effect of weather conditions on traffic intensity in the Northwest Territories using traffic counter data from four locations along the territory’s highway network between 1993 and 2019. We use a linear regression model with specifications that control for time-fixed effects and location-fixed effects to isolate the influence of temperature, rain, snow and wind on traffic volumes. To date, few studies have examined the effect of temperature, rain, snow and wind in an extreme cold weather climate. Our study also validates the conclusions of international literature in the Northern Canadian context. It is both a contribution to transportation and circumpolar scholarship.

ABSTRACT. Traffic signal management is an important concern in transportation. Traffic prediction is attained more interest in the last few years. With the rapid infrastructure revolution and the automobile industry, all countries face traffic congestion. The development of AI and the high dimensional dataset availability has attracted many scholars to develop various techniques to maximize the green time duration. Generally, traffic signal control (TSC) is utilized in real-time due to the lower establishment price. Nevertheless, these methods do not offer good function parameters, particularly during unbalanced traffic. So artificial intelligence is utilized in traffic signal control to degrade the delay period. Some drawbacks include failure to adopt traffic demand and high training costs. So, the novel Golden Eagle-based fuzzy signal controller (GEbFSC) is presented in this article to reduce the traveling time, delay time, and queue length. The presented strategy monitors and detects the traffic from the standard traffic flow dataset. The effectiveness of the presented model is validated by comparing it with other techniques, and the improvement value is evaluated. Finally, the comparative assessment validates that the developed technique performed better than other techniques.

ABSTRACT. Although service network design models are often used at strategic or tactical levels, we shown in this work it can be used to solve operation level bi-directional commodity forwarding problems on a daily basis. We consider a service network design for parcels urban logistics with node capacity. The node capacity is the space/quantity limit for resources (say, drivers and vehicles) at terminals. The node capacity, for instance, the parking limit at terminals, varies by the time of a day or the day of a week. We introduce a general formulation and design a Branch-and-Price method to provide good quality solution of the formulation. On the basis of significant numerical results, a comprehensive analysis of the formulation and algorithm is presented. The results have shown that the proposed method is computationally efficient in terms of computation time and solution quality. We also show that the node capacity indeed affect the delivery efficiency.

ABSTRACT. The effect of COVID-19 on the for-profit sector in Canada has been remarkable as evidenced by the increasing number of businesses filing cases for bankruptcy and high unemployment rates. Indeed, the province of Manitoba has the highest rate of COVID-19 confirmed cases across Canada. Nevertheless, a relevant COVID-19 study in Manitoba is under-researched. As such, this study aims to investigate the key aspects of Manitoba including Canada and Manitoba COVID-19 pandemic-related laws, panic buying, and border closure with the United States and Provinces. In addition, a possible strategies and opportunities are provided for the province of Manitoba to revitalize the economy during the post pandemic era.

ABSTRACT. Agri-food supply chains are likely to be disrupted during mega events. In order to prevent food waste and financial losses, it is crucial to respond and recover quickly from these disruptions. In fact, hosting such events has emphasized the importance of disruption management in supply chains, especially for small countries. The purpose of this study is to give an overview of the possible long-term and short-term impacts of hosting major events. It presents a case study of the 2022 FIFA WORLD CUP using a simulation-based method. Additionally, it takes into account a wide variety of challenges, such as perishability, traffic problems, and increasing customer demand for agri-food products. Realistic data from an agri-food supplier will be used to simulate future scenarios and illustrate their impacts on Qatar’s food supply chain. From simulation results, it appears that the rise in food demand has a great impact on the supply chain operations and performance, whereas transportation disruptions did not have significant impacts. Despite this, we note that higher demand has generated higher revenues. We conclude with several practical recommendations to improve the robustness and sustainability of the AFSC.

ABSTRACT. Although driverless driving promises optimization potentials for the logistics industry, these effects were hardly considered in literature or research about logistics systems. The aim of this paper is to understand the interactions of driverless vehicles with the logistics system to identify undesirable effects of a related market penetration. Based on a systematic literature review and a comprehensive evaluation of 31 publications, a conceptual system model with four subsystems based on Sjöstedt (1996) is designed. On this basis, an expert workshop using Vester’s (1990) sensitivity model, 53 non-technical aspects of driverless vehicles in logistics are identified which have been condensed to 18 variables. Using Vester’s impact matrix, the effects of the variables in the system were formulated. A system dynamics-future model quantifies these variables for three different times in a time span of 30 years, starting in 2019. A total of 19 positive and 17 negative feedback loops in the system are identified. The results of the simulation model show that the market penetration of driverless vehicles can lead to undesirable effects in the logistics system. Based on the ecological, economic, and social dimensions of sustainable development and related policy challenges these effects are discussed from an involved player perspective.

ABSTRACT. We develop a three-echelon supply chain model including engine manufacturer, aircraft manufacturer, and airline to analyze the engine options in airline new aircraft purchases. We show that given an airline's existing fleet composition, a larger fleet size and higher aircraft production efficiency would make it more likely to choose multiple engine options, while higher production cost and engine substitutability would lead to a shift to a single engine or even out of the market. In the model, we highlight the impact of MRO (Maintenance, Repair, Overhaul) costs with economies of scale on airline engine option decisions. In particular, the airline would therefore buy more of the advantageous types in their existing fleets and crowd out the disadvantageous ones. Furthermore, we introduce competition at the airline tier, analyze the property of equilibrium in the duopoly case, and compare it with the benchmark case through numerical simulations. It shows that competition does not always increase the supply of services in the market, but higher MRO economies of scale moderate this shrinkage.

ABSTRACT. Freight transport is one of the most polluting sectors worldwide. While many solutions have been developed for urban logistics, long-distance transport, via trucks, is a major issue for decarbonization. In this study we propose to analyze – operationally and economically – the possibility for a major player in the parcel industry in France to transfer part of its long-distance flows to rail. To this end, we identified the whole combined transport service in France and compared it to the transport plan and constraints of the studied company. The originality of this study lies in the fact that it is based on a real case on a national scale. The results show that the supply of combined transport (in terms of itinerary) is extremely limited compared to the diversity of itineraries performed by trucks. Secondly, on the compatible routes, there is an operational incompatibility from the point of view of the time constraints of the parcel services. The paper illustrates how, for a large road freight carrier, a significant shift to railway is impossible in the current constraints.

ABSTRACT. KTL terminal has hybrid structure of rail freight terminal between private development and public one and this structure can be regarded as new method of useful terminal development. Under no conflict of time slot in terminal, KTL terminal can give benefits for the terminal owner, users, and government each. However, once the conflict arises, those benefits would be disappeared, and the terminal would not be used efficiently. Therefore, appropriate conflict adjustment is needed for KTL terminal to use the terminal efficiently. However, current situation of the adjustment would not seem to be appropriate so well. It would be required for the continuous and efficient access of the terminal to make new agreement of conflict under a certain heavy congestion in the terminal and to try to establish good relationship among the terminal users.

ABSTRACT. To maximise the importance of cargo operations at airports, there is a need to successfully manage cargo distribution efficiently to reduce delivery time and costs. However, achieving efficient air cargo logistics operations is often challenging due to several factors limiting cargo processing. This paper examines the factors affecting cargo logistics management at airports in Nigeria. A survey of various stakeholders was conducted by random sampling at the Lagos International Airport, where 337 valid responses were received. Data collected were analysed using exploratory and confirmatory factor analysis. EFA identified bureaucracy, equipment and facilities, traffic flow, and malpractices as the significant factors affecting the logistics of cargo distribution at the airport. CFA validated the statistical significance of bureaucracy, equipment and facilities, traffic flow, and malpractices as critical factors affecting the logistics of cargo distribution at the airport. It was found that bureaucracy negatively affects equipment and facilities, while malpractices negatively affect traffic flow and equipment and facilities. The findings highlight the need to incorporate real-time automation of cargo processing with equipment provision to enhance airports’ capacity for efficient air freight logistics at airports in Nigeria.

ABSTRACT. The role of inland container depots (ICD) in facilitating a modal shift from road to rail for the reduction of road carnage and damage in Nigeria. Three research questions were formulated to facilitate the findings of the study. The study adopted the survey research design. 211 stakeholders in the port industry in Nigeria were sampled for the study out of a population of 1500 stakeholders through the purposive sampling technique. A questionnaire was used for data collection. The reliability of the instrument was ascertained using Cronbach Alpha and the reliability coefficient was 0.89. The data collected in the study was analysed using a mean score and standard deviation. The findings of the study revealed that ICDs have the capacity to reduce the rate of road damage by substituting roads with rails as the major means of transporting goods from the port, thus making the roads less busy. Also, ICDs can promote synchro-modal transport, which will aid in decongesting the roads in Nigeria and reduce the number of tankers and trucks on the road, thereby reducing the rate of road accidents. The findings suggested that the Nigerian government should introduce ICDs to facilitate the modal shift from road to rail.

ABSTRACT. The use of the Internet of Things (IoT) brings radical advancements in the domain of waste collection as it enables the organization of demand-responsive schedules, which allows a step change in the efficiency of operations. One major drawback of demand-responsive schedules, nevertheless, is that they bring uncertainty in the planning of resources and strong variability in their deployment, as they follow the daily waste demand. This is undesirable in real-life operations as it makes it difficult to reserve resources, secure commitment from suppliers, and ensure the stability of operational processes. The challenge, therefore, is to create scheduling approaches for waste collection that are not only efficiency-driven but also both demand-responsive and supply-friendly. In this paper, we present a solution approach for the waste collection vehicle routing problem in an IoT context (IoT-WCVRP) that focuses on these requirements and demonstrate its applicability through a case study of Rotterdam in The Netherlands. In this case, our approach achieves the stated demand and supply trade-off, and additionally increases the vehicle utilization rates by 5%, and reduces emissions and travelled kilometres by 6% and 8% respectively.

ABSTRACT. The objective of the article is to propose and evaluate the impacts of bio-waste management solutions. We will focus on transport. Each year in France, the transport of the 355 million tons of waste produced represents 30% of the greenhouse gas emissions generated by waste, i.e. 2.4 million tons of CO2 equivalent (Ademe, 2016). Most of these emissions are produced during the waste collection stage. We will propose several scenarios. There is no single solution for the treatment of bio-waste. On the contrary, the majority of systems are moving towards hybrid management, using systems based on management by the traditional technical network and recovery by decentralised systems. By quantifying the environmental impacts of the proposed scenarios, we will be able to compare the inherent advantages and disadvantages and thus identify the one that seems most relevant.

ABSTRACT. Implementing circular supply chains is a major economic transformation that can only work if significant coordination problems between the actors involved are solved.

This requires, on the one hand, the implementation of efficient urban collection technologies, where process industries collaborate hand-in-hand with manufacturers and urban waste treatment specialists and are supported by digital solutions.

On the other hand, it also requires implementing regional ecosystems connected by innovative CO2-neutral circular city logistics systems smoothly and sustainably managing the regional flow of resources and data, often at large-scale and with interfaces between industrial processes and private and public actors.

Our research project aims to develop a blueprint for circular urban regions, including the demonstration of a territorial cross-sectorial, large-scale and sustainable systemic solution for the circularity of high-performance plastics from diverse applications of rigid polyurethane (PU) foams used as insulation material in refrigerators and construction elements.

In the Greater Amsterdam Region (one of the three regions in this study), a sustainable and resilient collaborative network of public and private partners will be established concerning the circular supply chain for rigid foam coming from appliances and construction waste, especially focussed on the urban collection, logistics, dismantling, and building of a control tower

ABSTRACT. The transformations in urban freight transportation resulting from the increase in e-commerce require novel approaches for integrating these flows with traditional passenger flows in the urban environment. Integration of freight and passenger movements is an idea that has recently been investigated in academia, aiming to utilize the spare capacity of public transportation to move cargo, thereby reducing the number of trucks in densely populated areas. This paper proposes a conceptual framework for integrating freight deliveries and passenger transportation using the same vehicle and schedules, using scheduled lines (passenger transportation services), ridesharing alternatives (share-a-ride), and crowd shipping. Examples from real-world operations and quantitative analysis of systems are reviewed to construct a framework to assess the fundamental issues with the integration. Different planning levels are presented and integration issues are described, considering aspects of real-world examples in cities around the globe. This study contributes towards understanding how freight transportation can be integrated in city planning to reduce the externalities attributed to these operations while promoting a more economically and sustainable option for same-day deliveries.

ABSTRACT. The passenger and freight First-Last Mile (FLM) is a relevant transport issue, representing a significant share of total transport costs, pollution, and energy expenditure. According to recent literature and inputs of the European authorities, the combination of passengers and cargo flows could be an effective approach to promote a sustainable and energy-efficient FLM transport. This paper quantitatively evaluates the energy and environmental performances of an integrated passenger and freight transport bus system in Zrenjanin (Serbia). An appropriate setting is designed thanks to the proactive dialogue with relevant stakeholders and analysis of local planning and development documents. Subsequently, the system performances are evaluated and compared to the operations of current public transport and freight deliveries, then focuses on the energy performances, by considering vehicle fuel and technology, total mileage, idle time, and other relevant endogenous and exogenous factors. Results of our analysis call for some operational benefits and energy savings, mainly due to the reduced overall mileage and to the systems’ predisposition for a shift towards zero-impact transport means (i.e. active modes) for the final leg of both passengers and freight trips. However, technological development of vehicles and modal shift encouraged by policy strategies may induce further energy savings.

ABSTRACT. The paper is devoted to the micromobility solutions used for urban freight transport by people in Poland. Various approaches have been adopted to identify new mobility behaviors with a particular focus on micromobility solutions. The research was based on the CAWI survey data with a random sample of over 500 Polish residents, carried out during the late autumn of 2021 (the second wave of the epidemic). To address the article's main scope, qualitative and quantitative methods have been implemented to compare the mobility choices of respondents. During the data analysis, the author looked at differences between age groups, city and countryside residents and similar but also investigated if the mobility gender gap can be identified for the surveyed group. Moreover, the priorities of respondents regarding different business models (station-based and free-floating systems, owned, shared, and mixed micromobility, infrastructure needs, IT applications, etc.) were analyzed. The main finding of the article led the authors to the statement that active means of transport, including micromobility, have great development potential in freight transportation in cities.

ABSTRACT. E-commerce established the consumer as a freight actor. Yet, while in B2B settings shipper and receiver agree upon logistics standards and organization, in a B2C context, the consumer (receiver) depends solely upon the logistics choices of the shipper. The lack of a relationship between the logistics service provider and the consumer limits the potential for consolidation and prevents consumers from paying for tailored logistics services. In this paper, we look at passenger transport, specifically at Mobility-as-a-Service (MaaS), as a way to integrate the consumer into the distribution system. We propose different options for how a Logistics-as-a-Service (LaaS) could look and discuss the role of various stakeholders and the potential levels of integration. We conclude by identifying a suite of research questions that deserve attention to implement a LaaS system.

ABSTRACT. Urban freight is the last mile of a supply chain where commercial vehicles deliver shipments to final recipients. Tour modeling of the last mile can aid in strategic policy planning as commercial vehicles often make a substantial proportion of traffic. Existing tour modeling methods suffer from computational complexities, are sometimes insensitive to behavioral aspects of decision makers (e.g., shippers and distributors), and require extensive calibration data, which may not always be available. This paper presents a tour-based model formulation based on the principle of continuous approximation. The model distributes shipments to nearby regions and assigns vehicles to make the deliveries in each region. We apply the model on a hypothetical example under multiple scenarios. The results show that the model is sensitive to characteristics of regions and tends to replicate firm’s behavior in terms of economies of scale. For instance, the cost per shipment delivery is lower when more shipments are delivered to a region and becomes stable when trucks are utilized at their full capacity.

ABSTRACT. With the expansion of urbanization, freight transport leads to increasingly serious traffic and environmental problems. Transport planners need appropriate urban freight modeling tools to assess the impact of policy decisions on the freight transport system. This paper is designed to model the urban freight transport microscopically through three steps: freight generation, freight distribution, and vehicle routing. A heuristic optimization method that combines priority labeling and simulated annealing algorithm has been developed. The model has been applied to a real-life case study of last-mile deliveries in food retail in Berlin, which is based on existing nationwide survey data and other open source data. The final tour planning results showed that the modeled share of various types of vehicles are consistent with the real world and reflect the current state of urban freight.

ABSTRACT. The container flows constitute to nearly twelve percent of the total truck traffic in Sweden. Container movements differ from other truck freight as the former primarily comprises of import or export cargo, and either origins or destines at the port. Also, the containerized cargo would have different payloads and empty trip patterns. Hence, it is required to include container movements separately in the freight planning process. This paper analyzes the container truck flows in Sweden using the trucking data from Trafikanalys for four years (2016-19), emphasizing empty container movements. Two sets of demand models are presented. The first model estimates the payload (weight of the cargo in a container) of container trucks in tons, which helps convert the weight of container cargo into the number of loaded truck trips between an origin and a destination within the country. The second model is the empty trip model estimating the probability of a container transported empty by a truck. The share of empty containers in the truck traffic was nearly 44-46% by number of vehicles and 32-33% by vehicle kilometers traveled. The results show that the payload and empty trips are highly dependent on the origin, destination counties, and the industry sector.

ABSTRACT. The choice of shipment size is a vital decision in logistics and has a strong indirect influence on freight transport demand, via the choice of mode and truck type choice. Through time, shipment sizes can change as a result of new decisions in the logistics process or due to conditions external to the supply chain. This study investigates the temporal stability of shipment size choices, relating these to the choice of truck types. It uses repeated cross-sectional data for the years 2015, 2017, and 2019 collected from cordon and business establishment surveys in Addis Ababa city, Ethiopia. The integrated choice and latent variables (ICLV) and latent growth (LG) models were used to assess the time-dependent patterns of choosing shipment sizes, both at the level of the entire freight system as well as the specific truck types. The model results reveal that shipment size decisions are temporally unstable where, in our case, shipment sizes exhibited a declining trend. Changes in shipment size considerations are further discussed with the link to fluctuations in economic conditions and their implications on freight transportation planning.

ABSTRACT. This paper reports the research conducted on developing and implementing a national freight demand model for Bangladesh based on Integrated Data Collection and Modeling with Freight Origin-Destination Synthesis (IDCM-FODS). The approach seeks to minimize the cost and time spent on model development by exploiting the power of clever data collection and modeling without sacrificing the quality of the work. The approach has two major components: (1) IDCM, intended to estimate the freight generation (both production and attraction) and freight trips, using a targeted survey sample of commercial establishments to estimate econometric models that are then applied to national statistics to estimate freight generation and freight trip generation; and (2) FODS models, both generic commodity and multi-commodities, to infer freight flows and calibrate a freight distribution model, and a vehicle-trip (both loaded and empty trips) that minimize the errors between the modeled and observed traffic in the network. The paper discusses background information about Bangladesh, the data used in the research effort, the process to conduct the survey and estimation of the econometric freight generation models, the use of these models to obtain freight generation estimates countrywide, the FODS models obtained, and the chief conclusions of the overall effort.

ABSTRACT. Monitoring road traffic state/speed is essential in many applications, such as travel time prediction, traffic control, and traffic safety. However, the traffic state is often unavailable in many locations and times due to the lack of sensors. This paper proposes a novel method to impute traffic state using Gaussian processes (GP). We develop a rotation method to transform traditional GP kernels into anisotropic kernels to model the traffic wave propagation in traffic speed data. Our method can impute traffic state data from fixed sensors or probe vehicles. The GP-based method also has the advantage of providing statistical uncertainty quantification for the imputed traffic state. We evaluate our method using real-world traffic speed data from the Next Generation simulation (NGSIM) program. Results show our method outperforms the state-of-the-art methods in terms of imputation accuracy and efficiency.

ABSTRACT. The present paper compares motorized two-wheeler (MTW) and passenger car’s interactions with the rest of traffic in urban roads while performing overtaking and filtering maneuvers. To better understand filtering maneuvers of motorcyclists and car drivers, an attempt was made to propose a new measure i.e., pore size ratio. Additionally, the factors affecting lateral width acceptance for motorcyclists and car drivers while overtaking and filtering were studied using advanced trajectory data. A regression model was developed to predict the significant factors affecting motorcyclist and car driver's decision of accepting lateral width with the adjacent vehicle while performing overtaking and filtering maneuvers. Finally, a comparative analysis between machine learning and probit model revealed that, in the present case, machine learning models perform better than the probit model in terms of the model’s discernment power. The findings of this study will help ameliorate the power of existing microsimulation tools.

ABSTRACT. Video imagery obtained from cameras mounted on transit buses for nontraffic purposes while the buses are in regular service is used to estimate roadway traffic volumes and vehicle miles travelled (VMT) on a small urban network on a representative day in each of 2018, 2019, 2020, and 2021. VMT for the same network and days is also estimated using traffic volumes obtained from a popular Location Based Services (LBS) data supplier. Traffic volumes from road-tubes, serving as ground-truth, are available on different subnetworks in three of the years. On the road-tube subnetworks, the video-based VMT estimates are found to be much closer than LBS-based estimates to road-tube-based estimates. Similarly, the time-of-day patterns determined from video-based VMT estimates are much closer to road-tube-based patterns. On the expanded network, where road-tube data are not available on most segments, year-to-year changes in video-based VMT are consistent with expectations related to the covid-19 pandemic and with changes implied by statewide traffic monitoring factors, whereas LBS-based VMT changes are not. Quantified comparisons among time-of-day patterns on the expanded network in the different years are also much more reasonable when determined from video-based VMT than from LBS-based VMT estimates.

ABSTRACT. Light rail transit with shared-use right of way (ROW) has the advantages of low cost, minimal land requirement, and high flexibility. However, its operation and capacity are substantially affected by highway vehicles and traffic signals. Past studies on light rail capacity analysis were limited to single-lane highways with fixed signal control. In view of this situation, this study extends the capacity model to a multi-lane highway with priority signals and proposes a complete computation framework with three modules for four types of critical points. The signal priority module considers the impact of priority signals. The lane flow distribution module determines the traffic flow rate on the shared lane, and the line capacity module computes the line capacity. The proposed framework is validated through simulations with VISSIM software, and results show that it can provide an accurate capacity estimation. The capacity framework can be used by practical operators as a reference for the design, planning, and operation stages.

ABSTRACT. Travel-time-congestion-index is keyed to the differences in actual versus desired travel times for various types of roadways and is found to be influenced by both traffic and geometric characteristics of the roadway. The developed index provides a continuous scale for assessing the level of congestion incurred. In general, the measurement of Level-of-Service (LOS) across the stretches is adopted to measure the level of congestion. However, it is observed that measuring LOS alone does not provide better insights into the reasons for congestion other than the volume-to-capacity ratio. Therefore, this study develops the TTCI by employing traffic and geometric parameters to measure the congestion along the roadways on urban roadway stretches. In addition to the development of the TTCI, LOS is also measured and compared with the TTCI values of the particular stretch. The results indicate that employing all the variables together in a single technique yields much better and more reliable values for congestion indices. The results were also found in line with the field conditions. This study also proposes using TTCI values to design the cordon lines for delaminating the congestion zones and estimating the level of service of the roadway.

ABSTRACT. Understanding transit service reliability is essential for agencies to improve their operations and passenger experiences. Transit travel times that follow mixture distributions would create an additional layer of uncertainty when studying transit reliability. This paper tries to identify segments where transit travel times follow mixture distributions at different analysis levels, namely stop pair level, route timepoint level, and service pattern level. We then identify potential factors related to them. Hartigans' Dip Test is applied to archived transit vehicle location data from Montreal to explore the presence of mixture distributions. The results contain mixture distributions at three analysis levels, and the proportion of mixture distributions varies temporally and spatially. Then we test several classification models to identify the potential factors that affect transit travel time distributions, where we found demand variations, traffic lights, service frequency, and segment lengths have a larger effect on the results. The findings will help transit planners to later pinpoint the issues causing transit travel time variations on each segment, then create strategies to reduce the transit travel time variations thus improving the reliability of our transit system.

ABSTRACT. Spatiotemporal traffic data imputation is of great significance in intelligent transportation systems and data-driven decision-making processes. To make an accurate reconstruction on partially observed traffic data, we assert the importance of characterizing both global and local trends in traffic time series. In the literature, substantial prior works have demonstrated the effectiveness of utilizing low-rankness property of traffic data by matrix/tensor completion models. In this study, we first introduce a Laplacian kernel to temporal regularization for characterizing local trends in traffic time series, which can be formulated in the form of circular convolution. Then, we develop a low-rank Laplacian convolutional representation (LCR) model by putting the nuclear norm of a circulant matrix and the Laplacian temporal regularization together, which is proved to meet a unified framework that takes a fast Fourier transform solution in a relatively low time complexity. Through extensive experiments on some traffic datasets, we demonstrate the superiority of LCR for imputing traffic time series of various time series behaviors (e.g., data noises and strong/weak periodicity). The proposed LCR model is an efficient and effective solution to large-scale traffic data imputation over the existing baseline models.

ABSTRACT. Multi-step traffic speed prediction is a critical issue in the intelligent transportation system. However, due to the multiple spatial-temporal dependencies among roads, this issue is quite challenging. First, some spatial dependencies are not fully explored and exploited, such as those formed by being connected by different modes of transportation. In addition, how to simultaneously consider spatial and temporal dependencies and effectively integrate them needs further exploration. To tackle the above issues, we propose a multi-view spatial-temporal graph convolutional framework MVSTG, which adequately exploits the multi-view spatial-temporal dependencies and their interactions for more accurate traffic prediction. First, multiple graphs (especially those formed by various traffic modes) and multi-granularity historical data are constructed to depict the multiple spatial and temporal correlations. Then the multi-view temporal learning captures the multiple temporal trends by temporal convolution of multi-granularity historical data, and multi-view spatial learning handles the multiple spatial correlations by graph convolution. In addition, view-wise attention-based fusion is proposed to adaptively integrate information. It adaptively identifies the importance of each upstream view and generates multiple integrated results for downstream views. The experiments on two real-world urban traffic datasets demonstrate that the proposed model framework enhances performance on the accuracy of speed prediction.

ABSTRACT. Artificial intelligence is software based; mega projects are large physical infrastructures. We use exploratory research in understanding the merger of both by asking what artificially intelligent, sustainable, and resilient mega projects are and what their underlying theory is. Thus, the goal of the paper is to define an artificially intelligent mega project and identify its theory. To do so, we conducted a literature review on the two different topics and exemplified current mergers of AI and mega projects through two cases. We propose a definition for artificially intelligent mega projects and suggest consequentially an embedded new theory we call scAInce. We suggest that scAInce is a new research field, that explores the influences and impacts of artificial intelligence on our world. We conceptualize how AI mega projects as virtual AI futures might enable sustainability in our built environment. It ends with contributing a definition of what artificially intelligent mega projects are.

ABSTRACT. Accurate traffic volume and speed prediction have a wide range of applications in transportation. In this study, an Attention-Based Long Sort-Term Memory model (AB-LSTM) is proposed to simultaneously predict traffic volume and speed in a critical rural road segment which connects Tehran to Chalus, the most tourist destination city in Iran. Moreover, this study compares the results of the AB-LSTM model with the Long Short-Term Memory (LSTM) model. Both models show acceptable performance in predicting speed and flow. However, the AB-LSTM model outperforms the LSTM in 5 and 15-time intervals in prediction. In contrast, there is no considerable difference between the two models for the 30-minute time interval. By comparing the performance of the models based on different time horizons, the 15-minute horizon model outperforms the others by reaching the lowest MSE loss of 0.0032, followed by the 30 and 5-minutes horizons with 0.004 and 0.0051, respectively. In addition, this study compares the results of the deep learning models that take either of the transformations of the time-series categorical inputs, one-hot variables or cyclic ones, for the 15-minute time interval. The results demonstrate that both LSTM and AB-LSTM with cyclic feature encoding outperform those with one-hot feature encoding.

ABSTRACT. The feeling of safety is one of the most crucial elements of bicycle promotion. Newer bicycle designs with three or even four wheels have constructive possibilities to implement some safety features comparable to a car, e.g. brake, warning, and indicator lights, a seat belt or even a canopy to protect the driver from rain and headwinds. Positioning this kind of vehicles between micro car and bicycle, manufacturers try to address new user groups for which a bicycle has been no option nor a car – or vice versa. Further developments of recumbent bicycles, velomobiles and cargo bikes, the velocar from the 30s is experiencing a renaissance. A new design language based on the car, a higher elevation of the head above street level and the addition of the electric motor mean that a completely new vehicle category may emerge that has the chance to develop from a niche product into a mass product. Would new user groups be attracted by this kind of vehicle? This research investigates the perceived safety of 124 experienced cyclists riding on cycles like cargo bikes and velomobiles with a wide body of nearly one meter.

ABSTRACT. In 2007, the UK’s Manual for Streets (MfS) was published, which set out new approaches to designing priority intersections in built-up areas. This promoted lower visibilities for drivers on minor road arms compared to those in the UK’s Design Manual for Roads and Bridges (DMRB). By reducing the visibilities for drivers, MfS aimed to reduce the corresponding speeds of drivers on the minor road approach, thus reducing the level and severity of collisions. Portsmouth became the first city in the UK to adopt 20mph speed limits in most built-up areas in 2007. Existing studies on vehicle-bicycle collisions at priority intersections indicate vehicles' speed and visibilities as key determinants. However, these relationships in the context of low-speed limit areas have not been explored in the literature. This research evaluates the effect of visibilities at low-speed (20mph) intersections through analysis of 120 locations around the city of Portsmouth. Structural Equations Modelling and Artificial Neural Network models were built and compared to represent the complex interplay between vehicles' speed, speed limits, visibilities, geometries, traffic flows, and collisions. This research sheds light on the effects of reduced visibilities on motorised vehicle collisions with bicycles in the context of low-speed and low-speed limit priority intersections.

ABSTRACT. Digital innovations can greatly help to further improve the safety on our roads. As one of those technologies, the safety analysis through surrogate safety measures can help to detect and analyse areas of conflict in our existing infrastructure. Being able to compute these measures as part of real time systems, they can also be used to warn traffic participants of imminent danger. The presented project aims to the implementation of such a system. In this work, the goals, methodology and first results of the project are presented. The first driving simulator studies show great promises but still need for improvements. Same goes for the first prototype built, which will be deployed at an intersection in Germany in the spring of 2023.

ABSTRACT. While cycling has grown considerably in recent years, it is not as safe as it should be, and the perception of unsafety hinders its further growth. Intersections are the most complex parts of the road network, but cyclists are also particularly vulnerable on road segments when overtaken by motorized vehicles. Laws have been enacted to guarantee safe overtaking events by vehicles with minimum distance and other speed requirements. While there have been several studies on cyclist passing distance using instrumented bikes or vehicles, there have been few attempts at developing an automated system for the safety analysis of cyclist overtaking at a fixed location. This paper presents a computer vision tool to measure the cyclist passing distance and vehicle speeds before, during and after the overtaking. The tool is tested on a case study in Montréal, Canada. It shows that most passing distances are safe, but that drivers fail to comply with the requirement to decelerate while overtaking cyclists.

ABSTRACT. Pedestrian crashes have become a crucial worldwide factor in road safety improvement. This study aims to investigate the hazardous factors that contribute to the crash occurrence of pedestrians using Seoul case data. Census, land use, socioeconomic and environmental data were collected and aggregated by administrative districts, Dong, in Seoul. The potential safety improvement (PSI) was adopted for the identification of high-risk districts. The negative binomial regression model to calculate the PSI was developed using the number of crosswalks as a surrogate measure of pedestrian walking. The estimated decision tree indicates that population-related variables, land use, network environment, and supply of parking lots contributed to the occurrence of pedestrian crashes. The contributing factors to increasing the PSI were also investigated by the decision tree model, and the implications for the infra investment and promotion point are discussed.

ABSTRACT. Sudden large-scale changes like the recent COVID-19 pandemic make the management and planning of transport systems difficult, despite the ever-increasing availability of data. The primary goal of this work is to model transportation data time series using a dynamic model that is interpretable and can be used for long-term forecasting. The Bayesian Dynamic Linear Model (BDLM) is chosen because it can account for complex data and can be easily adapted to the data. A component for the BDLM is introduced to recognize the underlying patterns using temporal control points. A moving-event component is also added to take into account events that do not occur on the same date every year such as sports games. The proposed model is parsimonious and can learn from the data. After providing a brief summary of the theory of the model, experimental results are shown for transport demand data obtained from smart card transaction data for the Montreal subway system. The proposed model is compared to different time series models and shows its superior accuracy.

ABSTRACT. Past decades have been marked by several transformations that have a well known impact on mobility behaviors. In this context, using technologies such as WiFi and Bluetooth allows to gather passive mobility data, useful for ensuring the sustainable development of transport infrastructures. The main advantage of WiFi data over smart-card data or other passive data collections is to give information about the entire trips. As WiFi data collections are quite novel in transport modelling, we still need to confront the results we get to the ones obtained from grounded data sources. However, if we dispose of data on boarding passengers (smart-card data) or on boarding passengers and alighting passengers separately (optical counts) on a regular basis, it is not the case for Origin-Destination (O-D) pairs. This paper proposes to quantify the error between WiFi data and O-D surveys data in order to better appreciate the relevance of WiFi data. By using a theoretical model, we present a way to estimate the error on O-D pairs when the error on volumes per boarding (respectively alighting) is available. This method will allow analysts to control the quality of O-D pairs produced by WiFi data, using count data, which is continuously available.

ABSTRACT. The knowledge of mobility in a territory is essential for local authorities' decision making. The multiplication of sensors in smartphones is an important and reliable data source to analyze users' travels. This paper presents a method for collecting GPS and accelerometer data and a processing workflow to classify users' transportation mode with high accuracy. Recommendations for collecting the measurements are explained. The pre-processing method presented is based on the analysis of time gaps between successive observations. The fusion of GPS and accelerometer data and the calculation of features are performed with a sliding time window. OCC-Transport Mode, a dataset collected with a smartphone application is presented and made public to illustrate the different steps. The performances of several classifiers are compared on the collected dataset and on two public datasets (GeoLife and US-Transportation Mode). The classification accuracy, improved by the joint use of GPS and accelerometer, is close to 100% on the collected dataset. The features resulting from the time gaps are more important than the other features in the classification. The results obtained on two public datasets are discussed.

ABSTRACT. Public transit has been highly impacted by COVID-19, as well as transport demand in general. Using high resolution data from smart card systems, this research investigates spatial and temporal variability of pandemic impact on public transit in Lyon, France. Findings highlight variability between modes (subway, tramway and bus rapid transit) in terms of intensity of impacts, recovery patterns and stability of the shock over time. Results show that central areas recover worse than peripheral areas and west stops recover worse than east stops. Effects of COVID over time globally but not totally clear up, with a faster recovery for subway. Local analysis on specific stops also suggests that public transit associated to medical facilities less endures COVID-19 impacts than employment zones or universities.

ABSTRACT. This study investigates the uniqueness of metro users by comparing the trips of a user to those of other users. If the users’ trips are different from all the others, this user is called unique and could be identified from the large metro trip datasets. We further analyze users’ uniqueness when only some of the trips are available. The one-week metro trip data of Chengdu, China is investigated, which contains around 2.2 million users. The effects of temporal resolution and the number of trips on the user uniqueness are explored. Results show that when considering all the trips, the user uniqueness increases from 48% to 93% as the temporal resolution increases from one day to one minute. When the temporal resolution is one minute, one trip could identify 84% of the users. But when the temporal resolution is one day, one trip only identify 2% of users. However, two and eight trips could raise the value up to 34% and 48%. The user uniqueness increases with the number of randomly selected trips and the temporal resolution. Finally, we show that metro trip datasets with a low temporal resolution still suffer from privacy concerns and are vulnerable to user reidentification attacks.

ABSTRACT. Crowdsourcing through telematics and mobile platforms has been heavily researched for transport applications in the last decade, falling in the realm of intelligent transport systems (ITS). The value of crowdsourced data lies in enabling the participation of the ‘crowd’ for a human-centric, user-oriented, and reliable information system. On the other hand, there is a need for robust systems beyond traditional data collection methods, especially in public transport. Telematics is generally understood as a method of monitoring vehicles and other assets by using GPS technology, onboard diagnostics and dashboard applications. This study demonstrates the power of crowdsourced open data for promoting fuel efficiency and eco-driving practices on bus operations through the pilot implementation of a real-time smartphone-based bus monitoring system. The platform is integrated with SafeTravelPH, which public transport crowdsourcing app. Through collaboration with operators and drivers, the prototype collected real-time data on vehicle location, passenger boarding and alighting and vehicle occupancy feeds. An innovative approach in capturing vehicle operating parameters, including engine RPM, speed, and fuel levels, is implemented using image processing and artificial intelligence (AI) techniques. Various fuel efficiency indices that can provide sound basis for the evaluation of bus driving behavior and fuel-efficient bus operations are presented.

ABSTRACT. Modeling a two-step process consisting of the discrete choice and its consideration set formation has been studied in the transportation literature. Such modeling can be developed dramatically by observing the actual consideration set. Thereby, this study proposes a novel model to address the endogeneity issue that can occur in the two steps using a probit-based multivariate modeling framework. The proposed probit model incorporates instrumental variable methods in the discrete choice and its choice set formation model components. It also allows the correlations between alternatives and dependency between the consideration set formation and conditional discrete choice. The model has a high-dimensional open-form structure, and thus we propose a tailored Markov chain Monte Carlo algorithm for the parameter estimation. The simulation study demonstrates that the proposed model adequately addresses the endogeneity bias on parameters corresponding to the endogenous variable. Our model will be helpful to better understand to what extent a policy variable of interest truly affects the discrete choice and its actual consideration set formation.

ABSTRACT. In Taiwan, V2G is a concept mainly in the planning or testing phase in the current scenario. This study thus proposes the extended unified theory of acceptance and use of technology (UTAUT2) with risk perceptions to investigate the effects of factors influencing people to use V2G services. We collect 365 samples for model estimations, and results show that performance expectancy, effort expectancy, and price value positively relate to attitude, in turn leading to use intention. Overall, respondents are likely to use V2G services thanks to the attributes of electricity bill saving, the higher price of selling electricity, benefits to power system stabilization, and ease to use. However, the risk perceptions (i.e., battery safety, range anxiety, and inelastic vehicle utilization) of V2G services are the barriers to respondents’ adoption of V2G services.

ABSTRACT. This paper focuses on the discrete outcome estimation problem, which involves testing multiple hypotheses that can affect both interpretability and predictive accuracy. While a few studies have proposed a mathematical programming approach to assist with hypothesis testing and estimation, there is limited knowledge regarding the effect of also considering both in-sample and out-of-sample model performance criteria during the search for a specification. To address this knowledge gap, a multi-objective optimization framework is proposed including both in-sample goodness-of-fit and out-of-sample predictive accuracy to generate multiple unique specifications and perform extensive hypothesis testing considering simultaneously potential explanatory variables, their functional forms, nonlinearities, heterogeneous effects, and correlations. A metaheuristic was designed and implemented to solve a proposed multi-objective nonlinear mixed-integer mathematical programming problem. Experiments including various datasets and discrete outcomes were used to illustrate the efficacy of the proposed framework to find specifications that are either very similar or dominate those reported in literature, considering both interpretability and predictive accuracy. Results showed the value of using an optimization framework to support the modelling decisions by enabling extensive hypothesis testing and including multiple performance criteria as well as complex data characteristics to discover important and generalizable insights.

ABSTRACT. The application of machine learning techniques, more specifically kernel-based techniques, to discrete choice modelling using large datasets is limited by the great number of parameters to be considered when building the kernel matrix and the size of the kernel matrix itself. The spatial and temporal complexity is such that these methods are not applicable to large sample sizes. However, there are techniques that allow generating a low-rank matrix approximation to the kernel matrix, one of them is the Nyström method. One limitation of the Nyström method is that the quality of the kernel matrix approximation depends on the proper choice of landmark points. In this work, four variants of this technique are implemented, a basic uniform method, one based on the K-means algorithm and two different implementations of a non-uniform method based on leverage scores. Later, in the experimentation, we conduct a comparison of these methods applied to two big transport mode choice datasets, which contain a large number of samples and variables. Finally, these results are compared with Multinomial Logit and other techniques currently relevant in the Machine Learning field.

ABSTRACT. Decision-makers' choices are of great interest to several scientific areas whose efforts are focused on understanding and forecasting their behavior, such as transportation. Choice modelling has been dominated by static representations (e.g Random Utility Maximization) of preferences due to their ease of implementation, transparent economic interpretability and statistical coherency. Unlike static compensatory approaches, the Decision Field Theory (DFT) model explicitly includes the attribute scrutiny process within the choice decision, making it more closely related to the behavior that is observed in practice. However, the DFT model lacks the RUM model's microeconomic interpretability and has statistical limitations regarding the identification of the model parameters. This research introduces the "RUM-DFT" model, encompassing ideas from both approaches. Using Monte Carlo simulations and applying the proposed model to a database of real choices, it is first shown that the proposed approach can properly i) identify the parameters of the deliberation process, ii) replicate the dynamic behavior of the utilities during the deliberation process; iii) retains full economic interpretability, since the estimated coefficients correspond to marginal indirect utilities when there is perfect knowledge of the information search process, and iv) that using a RUM model results in inconsistent estimators that may lead to spurious recommendations.

ABSTRACT. Mobility-as-a-Service (MaaS) provides travelers with a single digital travel platform that integrates information, booking, and payment that offers significant discounts. Existing MaaS studies mainly focus on commuters’ daily mobility instead of tourists’ mobility during their stay at destinations. MaaS is quite suited to the tourism, because it provides tourists who usually lack travel information, such as tourist attractions and multimodal services, with a convenient, economical mobility option. To explore tourist preference for MaaS, this research examines survey data from a sample of 491 tourists’ stated preferences by using the latent class choice model. The results identified three preference groups, naming MaaS Skeptics, Neutral MaaS Supporters, and MaaS Enthusiasts, whose preferences are diverse about mobility services, latent attitude variables, and other individual characteristics. The price of the Maas bundle appears as a critical factor for MaaS skeptics, but not for MaaS enthusiasts. MaaS supporters and MaaS enthusiasts tend to prefer shared mobility services such as shared electric scooters to public transport. Lastly, the paper discusses implications for an MaaS bundling strategy toward sustainable tourist mobility in terms of buddle attributes, including public transport, shared mobility, price, and discounts at designated shopping and sightseeing attractions.

ABSTRACT. This study attempts to deepen our understanding of people's activity spaces and relationships with their personal networks. Within this perspective, individuals' home structures their daily activity-travel, motivated by their productive, reproductive, and socialization needs. The study focuses on observing and understanding the relationships between their activity-travel spatial distribution and the characteristics of their social space, represented by their personal networks. Departing from the idea that not all spaces will have the same meaning, we recognize people's spaces that are not only productive. In other words, during a given time (such as the days of the week), a person could anchor specific locations not only associated with work but also with another set of locations related to socializing or shopping activities. The analysis explores the relationships between the activity space patterns, the size and shape of their spatial and social space, and the role of peoples' sociodemographic and personal network characteristics. Social space variables include the individual's personal networks' structure, attributes, and activity spaces (using kernel density measures). The systemic effects hypotheses are tested using multivariate statistical models.

ABSTRACT. The current study investigates the perception of tourists related to various pedestrian attributes that influence choice of walk in a destination. The choice of mode by tourists is highly influenced by travel satisfaction. The need of the tourists varies from that of general pedestrians. Therefore, the present study identifies 21 important pedestrian attributes based on tourists’ perception and studies the influence of their satisfaction on selecting walking as a mode of transport in the destination. Three popular tourist places namely Digha, Murshidabad and Nabadwip in Eastern India were selected for the present work. A paper-pencil based survey was conducted to collect satisfaction of tourists on a five-point Likert scale. The research framework for the present study was constructed based on the extensive literature review to establish the hypothesis. Structural Equation modelling technique was use to study the effect of various micro attributes on the choice of walk. This result found that most of the attribute satisfaction have high influence over choice of walk in the destination. Although the results are case-specific, the methodology can be used to formulate policies and measures for improving pedestrian infrastructure based on tourists’ perception in other tourist destinations.

ABSTRACT. As a side effect of the COVID-19 crisis, employees have gained greater discretion in deciding on appropriate work from home arrangements. Work place accessibility, particularly for commuters without full car availability, exerts an influence on work trip production levels, thus calling the often-assumed invariance of personal trip generation rates to networks into question. This may necessitate a back-coupling path of the transport level of service to the trip generation stage, often omitted in practice. Motivated by the identification of necessary post-pandemic adjustments to existing passenger transport models, this paper accentuates these new conditions that may possibly magnify the comparatively small but still measurable effects of accessibility on trip rates. To establish these points, the current literature is examined and two German NHTSs, one cross-sectional and one longitudinal, are analyzed from this aspect. It emerges that the supply side influence on the proliferating telework modulates per-capita trip rates, whereas ambiguous results are obtained on the compensatory generation of trips for other purposes that keeps the overall trip rate largely constant. The findings suggest that the non-negligible network influence on WFH should be addressed. A solution for operationalizing bidirectional supply-demand interdependencies within the four-step model sequence is proposed.

ABSTRACT. In recent years, several ancient heritage sites have undergone through major urban regeneration process to improve the quality of public spaces and tourists’ spatial experiences. The efficiencies of these projects depend on the acceptance of users. The post-occupancy evaluation of users’ spatial experiences is yet to be carried out in the redeveloped public spaces. This research article aims to evaluate the travel experiences of visitors in the recently developed Heritage corridors of Varanasi city. The applied method involves interviews with 270 visitors. Structural equation modelling is used to measure the impact of the different factors of the redeveloped corridor project on the travel experiences of respondents. The outcomes of this research reveal that respondents are more pleased with factors related to aesthetic quality and imageability than the infrastructure of the heritage corridor project. The outcomes of this research could be used to improve the shortcomings of the heritage site.

ABSTRACT. Many travel demand management strategies cannot be implemented effectively without first understanding route choice behavior. In addition, route choice behaviors have become more personalized due to the diversity of activity patterns and the complexity of urban networks, making it difficult to analyze route choice preferences in detail on a large-scale. Based on the anonymous travel trajectory data of 4,551 family-used EVs in Shanghai, this study explores travelers’ route choice preferences and regularities in different travel scenarios. We introduce the concept of entropy-weighted propensity score to reveal the heterogeneity of travelers’ preferences for different characteristics of the route choice and explore these preference differences in different travel scenarios of trip distance, trip type, time period, origin and destination locations, and land use mix. We then propose a sample-weighted K-means clustering method to discover three distinct route choice behavior modes: travelers with high variability and low rationality, low variability and low rationality, and high variability and high rationality. Our findings enrich the current understanding of route choice behaviors, which can not only provide empirical support for improving the effectiveness and accuracy of route choice models, but also provide practical recommendations for alleviating traffic congestion by implementing personalized traffic demand management measures.

ABSTRACT. Recently, demand forecasting models based on regression analysis have been developed at the station level to cope with the limitations of conventional four-step models when predicting passenger flow in public transport (PT) networks. This study aimed to directly estimate the passenger flow distributions of the Shizuoka bus network using network properties quantified by several centrality indicators and socioeconomic variables in three conventional regression models: ordinary least squares, Poisson, and negative binomial. Two representations of the PT network, in infrastructure and service space forms, were applied to compute unweighted and weighted graphs. Hyperpath-based calculations were utilised to identify the optimal service attributes from a set of attractive lines as a link weight. The best fit of Poisson regression model suggested that passenger flows could be explained not only by the network properties but also by factors identifying the characteristics around station. The findings from this model are expected to be useful for informing strategic development policy during the evaluation and reorganisation of bus operations and routes for maximum efficiency.

ABSTRACT. As one of the most complex maneuvers in road traffic, lane change has attracted extensive academic attention. So far, the notion of lane change has been classified as either mandatory or discretionary. This work examines mandatory lane changes (MLCs) executed for exiting freeways and ascertains how costly (or not) missing exits can be. We conduct an empirical analysis of two datasets collected in the Minneapolis - St. Paul metropolitan region. Outcomes suggest MLCs for exiting are not ‘mandatory’ regarding the extra time and distance travelled. Although both time and distance costs for missing exits are statistically significant, the extents are not immense. The average additional travel time is less than half a minute while the average additional travel distance is no more than 2 kilometres. Findings from this study provide new perspectives on the characterisation of lane change, and we argue that new models should consist of discretionary, mandatory, and costly lane changes.

ABSTRACT. The COVID-19 pandemic has affected everyone's life and how people spend their time. In this surrounding of changes, leisure activities and leisure-related travel gain special attention. Little is known about how affected people behave over time under the circumstances of a pandemic. This paper analyzes the impact of the COVID-19 pandemic on leisure activities and leisure-related travel patterns in Germany. The evaluation is based on the unique data set of the German Mobility Panel (MOP), a panel survey where individuals participate for one week in three consecutive years. The analyses show that the different stages of the pandemic drove changes in how people behave in their free time. During the first fall of the COVID-19 pandemic, significant decreases in travel demand are identified across all sociodemographic groups. With the relaxation of preventive measures during the summer of 2021, the previous plunge of leisure activities between 2019 and 2020 slowly returned in the direction of the initial state of 2019. Furthermore, it can be seen that the impact of sociodemographic characteristics such as gender, economic status or occupation status varies between the years and different leisure travel indicators.

ABSTRACT. In this paper, we examine the non-domestically cooked meal (NDCM) preferences of individuals for their dinner meals by studying the monthly count of NDCM meals by channel type: eat-out, eat-in takeout, and eat-in delivery. Data from a 2022 online survey collected in Texas is employed to estimate a multivariate joint model. The results suggest the important impact of workplace location on dining channel choice. The results also show clear evidence of complementary and substitution effects at play; the delivery channel complements eating out, but substitutes takeout. Similarly, eat-out has a substitution effect on eat-in takeout.

ABSTRACT. The ubiquitous use of smartphones and the availability of vast amounts of transport related led to the emergence and deployment of smartphone applications aimed at providing information. These travel apps, several of them aimed at voluntary travel behavior change (VTBC), lead to the development of research aimed at investigating their influence on travel behavior. Here we aim to study the role of Technophilia and Goal Framing Theory in the adoption intention and situational use of a prospective VTBC travel app. A Structural Equation Model is developed to empirically test a sample of 971 respondents collected in two suburban corridors in the Lisbon Metropolitan Area. Our results support that Goal Framing Theory is relevant to explain the adoption of VTBC travel apps. Gain and Normative motives are more relevant than hedonic motives, pointing to the importance of their tangible benefits. Our results also support the importance of Technophilia and the current use of travel apps to influence the intention to use VTBC apps.

ABSTRACT. At the 27th Annual Conference of the 198 Parties of the United Nations Convention on Climate Change (known as COP27) in Egypt in November 2022, experts warn that CO2 emissions, which contribute to Greenhouse Gas (GHG) is all time high. This has an adverse impact on the health of the planet, people and economies across the globe. One of the major contributors to CO2 emission is the transportation sector. The objective of this study is to examine causal relationship between transportation infrastructure, institutional quality, economic growth and CO2 emissions in developing countries from 2005 to 2021. A vector error-correction model (VECM) and quantile-on-Quintile regression (QQR) are used to study the dynamics between these variables. The empirical evidence suggests that there exist strong short-term and long-term relationships between transportation infrastructure, institutional quality CO2 emissions and economic growth in these sample countries. Hence, policy-makers in these countries should explore co-development policies pertaining to transportation infrastructure development and institutional reforms to reduce CO2 emissions; and, put these countries on the path to sustainable economic development.

ABSTRACT. In Europe, electric vehicle (EV) policies and investment in manufacturing are driving EV sales growth and contributing to its climate ambition towards 2030 and beyond. In this study, we investigate manufacturers’ plans for producing EVs and batteries, and compare these to four possible EV sales scenarios in Europe towards 2030 and 2035. In each scenario, we project the required capacities and estimate the investment needs to meet different targets. If Europe targets a transition to about 60% new EV sales by 2030 (100% by 2035), planned EV production capacity of 4.8 million for 2030 would fall short of the needed 9.2 million in that year by about half. With tentative announcements included, the gap closes to 2.0 million. Results for batteries are more encouraging: firm manufacturer plans could meet most of our scenarios for 2030 targets, and tentative plans are fully adequate. Overall, more investments in EV production and policy support would be desired for more rapid scenarios.

ABSTRACT. This study creates local pathways for the decarbonization of non-urban road transportation and integrates these pathways into an energy system model. In this study, social-technical pathways generation uses a participatory approach, involving municipal officials of three non-urban Swedish municipalities that represent different town sizes. One of the main conclusions is that generating pathways benefits from using a participatory approach since local targets and local resources are considered. Four pathways are identified, differing in terms of electricity production self-sufficiency, use of biofuels, and flexibility of public transport. The feasibility of these pathways in meeting short and long-term targets depends on local resources availability and the possibility for municipalities to make necessary investments in new technologies and infrastructure. The four pathways are integrated into a cost-optimization energy system model, which compares their environmental performance and cost-effectiveness. This cost-optimization analysis outlines how the needed investments are distributed among the general public, municipality, and private entities. The model can compare reaching local short-term goals versus meeting national long-term climate targets and thus clarifies whether certain decarbonization technologies are bridging technologies or part of the long-term technology mix.

ABSTRACT. The UN General Assembly has designated 17 Sustainable Development Goals (SDGs) and 169 related sub-goals, which the developed countries will try to achieve by developing new strategies with each other. Since one goal may overlap or conflict in some way for another; it is believed that there are most efficient ways about achieving progress on any given aim when taking advantage of positive synergies while reducing negative tradeoffs between them all at once - rather than focusing solely on just some single aspect alone (Global Sustainable Development Report, 2021). Therefore, the aim of this research is not only to investigate the intricate relationships among selected SDGs but also determine how they are related in terms of transportation-related variables and propose a roadmap for countries around them. The SDGs that were initially selected by Nilsson et al. (2016) are also the main SDGs evaluated in this research. The researchers found that changing one SDG had an impact on all the others by way of fuzzy cognitive maps and detailed scenario analysis. The team also developed a roadmap for policy makers who want to make changes in their country's direction based off this research, which can be used as guidance.

ABSTRACT. On-demand transit (ODT) has long been touted as a solution to many of the issues that plague traditional fixed-route transit (FRT) in less densely populated areas. This paper studies the results of an ODT service that was entirely implemented during the Covid-19 pandemic. The ODT service was deployed in the municipalities of Beloeil and McMasterville (BM) by exo – Réseau de transport métropolitain, a regional transit agency for the Greater Montreal Area. ODT not only replaced the FRT that had been previously in place but improved the service at the same cost to the user and at a saving to the operator since ODT required one fewer bus. The pilot-project was therefore considered to be a success. Large-scale data on each trip was collected permitting analyses on the characteristics of trips, user satisfaction, service improvements both in terms of coverage and frequency and environmental impact. ODT attracted new users who had never previously used the FRT service in BM. A large percentage of the trips taken using ODT would not have been possible using the former FRT service. Finally, ridership has continued to grow with the ODT local ridership surpassing 2019 levels of pre-pandemic FRT local ridership.

ABSTRACT. Interchanges are well-known moments of friction in the door-to-door mobility chain. Friction may happen at different levels and dimensions, including i) low perceived quality of intermodal terminals, ii) walking long distance, iii) loss of time, iv) extra costs, among others. Yet, changing mode of transport is almost inevitable in an urban mobility system. Hence, emphasis must be placed in improving the perceived quality of such locations. The SmartHubs project aims to contribute to a better understanding of mobility hubs. The SmartHubs project is a co-funded R&D project by the European Institute of Technology Urban Mobility (https://smarthubs.eu/). This manuscript presents the preliminary results of an ongoing research on tailored business models for different types of hubs. The SmartHub project defined six types of mobility hubs with different characteristics and purposes. Hence, six business models have been proposed. The business models will help decision-makers implement viable smart mobility hubs.

ABSTRACT. The aim of this paper is to discuss the planning history of Italian HS network, to underline the differences in approaches and outcomes between the original network design and the most recent developments. To do that, we periodize the history of the construction of the network into phases, each one characterised by differences in who plans, how and what is planned. The paper then discusses strengths and weaknesses of each phase, in terms of outcomes but especially of planning coherence. The Italian case is then used for a broader discussion on the pitfalls of infrastructure-centered planning in rail transport.

ABSTRACT. Competition is at the heart of the European Union's (EU) roadmap in the field of transport. In rail transport competition started late and took time to deploy. Just now, some years after the 4th railway package, competition is becoming a Europe-wide affair rather than a collection of single – and often small and short-lived – national experiences. Today it is possible to draw a first picture of how open-access rail competition will be in the coming years. The paper starts providing an overview of the varied experiences of “on track” competition in Europe to date, on a country basis. Based on that, some general discussion is drawn. Then the paper focuses on a new case, the entry of the Italian company Trenitalia in France, on the main country’s route, the Paris-Lyon. The characteristics of the newcomer’s business model are recalled and its medium-term profitability is studied through a model.

ABSTRACT. Should governments invest into high-speed rail? Do improvements in the conventional railway network deliver better value for money? This dilemma is among the leading themes of transport policy in many countries around the world, including the US, the UK, China, and several member states of the EU. In this paper we argue that the debate on railway policy should not be degraded into a binary decision between high-speed and conventional rail: for the first time in the literature of public transport economics, we treat speed as a continuous decision variable in the optimisation of intercity transport provision, together with service frequency, pricing, and the level of public funding. Among several other policy-relevant results, we find that the welfare maximising speed is an increasing (concave) function of demand. The model indicates that the welfare maximising high-speed rail service should be provided at lower frequency and higher fare levels. However, even with these optimal supply variables, its operating and capital cost recovery ratio is lower than the optimum of conventional rail alternatives.

ABSTRACT. By using a data set of 536 observations from 29 OECD countries for the 19 years from 1995 to 2013, this study investigates the factors affecting rail investment with panel data analysis. Among the pooling OLS, the fixed effect, and the random effect models, the fixed effect model is selected by statistical test. It seeks to clarify how investment is affected by factors such as demand, managerial, and regulatory factors. The main results are as follows: (i) factors positively affecting investment are output as a measure of train-km, capital stock as network length, GDP per capita, and the competitiveness of passenger railways; (ii) the competitiveness of freight railways has a negative effect; (iii) The highspeed train ratio itself is not significant; (iv) a larger government debt ratio tends to weakly decrease investment; (v) accident rate has a weak positive relationship with investment, but as the government debt ratio increases, the accident rate’s effect on investment decreases; (vi) among regulatory factors, investment weakly increases as the ratio of public ownership, vertical integration and overall regulation increases; (vii) deregulation of entry and greater competition in the market do not affect investment.

ABSTRACT. Papers based on systematic literature reviews demonstrate that the scientific literature on PFIs and PPPs have been captured by industrial economics and, more specifically, by the theoretical developments of the principal-agent relationship. We propose in this communication to explore another paradigm, that of identifying the foundations of the public economy that deserve to be revisited in cases of public-private partnership. To do this, we will deal with what we consider to be the main economic controls of a transport policy, which suggests five questions. The WACC being in principle higher in a PPP case, what are the implications for the level of subsidy? Since the WACC is higher in the case of PPP/PFI, under what conditions can this option be profitable for public finances? Is the optimal tariff that which optimizes the welfare function or that which optimizes the income of the private partner? Must the optimal ranking of various projects be based on the socio-economic rate of return (ERR), on the financial internal rate of return (IRR) or on another criterion? What happens to the value for money criterion in the case of the evaluation of a program of several projects?

ABSTRACT. Land use diversity is one key features of neighbourhoods to reduce car dependency and increase accessibility to local opportunities. This paper proposes to evaluate scenarios optimizing spatial distribution of local opportunities to better fit the distribution of day and night activities. Hence, COVID-19 has changed the typical distribution of people across space, due to full or partial virtualization of activities, questioning where opportunities should be positioned. We thus evaluate the opportunity density per square kilometer, per night and day population, with the current opportunity distribution and with two proposed scenarios. Furthermore, we evaluate two scenarios of restaurant redistribution that could result from the teleworking. The results show that the current distribution of opportunities better fits the day population distribution. Nonetheless, the population distribution could,in the upcoming years, lean towards the night population distribution with the virtualization. Strategic planning oriented towards a distribution in proportion to the night population would increase proximity for large proportion of the population. Also, the restaurant closures scenarios in some parts would have dramatic effects on the density of restaurants for the population, but it would then be possible to encourage a redistribution of opportunities by adapting them to locations where the population is concentrated.

ABSTRACT. The public transit system acts as one of the important guiding factors for urban development. People prefer to reside along the transit corridors to get the perks of a better livelihood. Transit corridors improve the character of a city, reform connectivity, regulate growth, and generate employment. Traditional theory neglects differences in the relationship between different types of transport routes and land use development when explaining urban land use patterns. The purpose of the research presented is to provide an empirical analysis for studying differences in the impacts of the development of the BRTS corridor on existing land use. To address these issues the research analyses the land use transformation along a public transit corridor, here highlighting the Bus Rapid Transit Corridor (BRTS) corridor in this study. Pimpri- Chinchwad has tremendous growth potential considering the existing development scenario. The area needs an appropriate Transit-Oriented Development Plan for space under the influence of the selected BRTS stretch. The results can help to interpret a suitable land use plan for the selected Pimpri-Chinchwad BRTS study corridor; ultimately, leading to the use of the adjacent land parcels at their maximum potential.

ABSTRACT. Urbanization has led to rapid rise in migration of people from rural to urban. Having risen in population leads to increased demand of land for housing and services, in case of rapid growth, it proves difficult sometimes to keep it in balance. This imbalance is haphazard development which puts burden on nearby utilities, services and infrastructure. To prevent this, proper land use plan is to be created and have a planned road network as well. Planning of each individual is feasible by other methods but the interrelationship between them can’t be ignored for which a traffic impact assessment needs to be carried out. The planning after that should be incorporated with consideration of factors affecting of land use and transportation as well as aims to be achieved through it. Land use management techniques contribute to mitigate various traffic issues by helping better planning of land uses. Small neighbourhoods can be planned as theories suggested throughout history avoiding traffic, mixed land use, better human health etc. The LINE proposed plan, Bables etc. are some of them. Overall developing cities with consideration of this relationship will reduce pollution, traffic congestion and also improve overall health of citizens and quality of life.

ABSTRACT. Transit and land use integration is one important strategic for future urban development. This paper uses the 3SFCA model to estimate Metrorail accessibility and the extending local Geary's C statistics to examine the spatial relationship between Metrorail accessibility and the density, intensity, and mixed structures of urban land use at the traffic analysis zone (TAZ) level in central Shanghai. The results indicate: 1) The distance from the CBD and the year of rail transit construction are major factors influencing Metrorail network accessibility. While the spatial distribution of TAZ Metrorail accessibility is in the shape of a mono-centric circle structure;2) Rail transit layout has a strong guiding effect on urban spatial pattern. 3) TAZ Metrorail accessibility is positively correlated with land use patterns in the majority of areas, with the exception of single-function university towns, industrial districts, and central historical protection areas. Finally, we propose that future urban planning should integrate local population density, employment opportunities, industrial types, and individual travel demand in order to provide land-use and transportation policies to improve the efficiency of urban operations.

ABSTRACT. Public agencies can take a leading role in catalyzing TOD by leasing or selling public lands to developers and facilitating development through public-private partnership. In particular, park and ride sites with a high level of access to transit system can be leveraged to initiate TOD by constructing affordable housing and commercial or mixed-use properties. To provide effective planning support, this research developed a multi-criteria prioritization tool to identify the most promising public lands for TOD and tested it on the park and ride sites owned by Washington State Department of Transportation. The tool was developed through a Delphi process, which is an effective approach to evaluate relevant indicators by synthesizing opinions of experts from various backgrounds. Five categories with a total of 14 indicators were selected as measures of TOD suitability under different scenarios. By computing and com-paring suitability scores, this tool can be used to prioritize potential TOD sites.

ABSTRACT. Urban rail transit system has increased dramatically over the past decades in China, in response to the broad adoption of Transit Oriented Development (TOD) strategy. Scientific interests were drawn in understanding the determinants of rail transit ridership, particularly the built environment factors. Unfortunately, existing literature investigating the relationship between the built environment and rail transit ridership overly relied on cross-sectional research design and outdated and fragmented traditional data. To fill the research gap, drawing on a rich set of non-traditional data (e.g., mobile phone positioning data and point of interest data), we construct a multisource panel data set over four years and then develop panel regression models upon it to establish the causal link between the built environment and rail transit ridership. The panel regression results show that the density of the resident population, restaurants, and health care facilities significantly impact ridership. The influence of the built environment on ridership in the morning and evening peak hours and off-peak hours on weekdays and at weekend has a temporal difference. There are also differences between boarding and alighting ridership. The findings help to inform future TOD planning.

ABSTRACT. In this paper, we analyze three electric drive concepts, which might contribute to a sustainable transport sector and ensure emission-free transport in future. To estimate the respective greenhouse gas emission saving potential, extended field tests in real-world operations are indispensable, politicians say. By means of a SWOT analysis, we succeeded in highlighting that each considered technology has a certain predestined area of application due to its individual advantages and disadvantages. Moreover, we found that they can complement each other. Furthermore, we determined that the acquisition of numerous vehicles, the appropriate charging and refueling infrastructure are decisive and need to be considered in such field tests - e.g. called as an “innovation corridor”. As a result, an innovation corridor enables us to investigate in a large-scale the use of electric drive concepts under monitored but realistic real-world conditions. Even if the different electric drive concepts are at different technology readiness levels, an innovation corridor ensures measurable progress for each of the electric drives and paves the way for an emission-free transport in future.

ABSTRACT. To achieve the German climate protection targets, a change to climate-friendly drive systems in road freight transport is required. For this reason, alternative and climate-friendly drive systems for road freight transport have been continuously launched on the market or tested in field trials in recent years. One of the technologies currently being tested in real-world operation is the eHighway system. The eHighway system is a combination of an overhead line hybrid truck and an overhead contact line infrastructure. To establish the eHighway system in the long term, it must be possible for transport companies to integrate this system into transport processes cost-effectively and with the least possible effort. Therefore, the objective of this study is to evaluate technical and operational success factors and barriers influencing the adoption of the eHighway system. We used expert interviews, written surveys, and analysis of vehicle data to obtain our results. We found that transport companies had no major restrictions concerning the technical equipment of the OH trucks. Furthermore, we have not found any operational restrictions in the use of OH trucks while the OH trucks can be integrated into different transport structures.

ABSTRACT. The electrification of road freight transport on highways using an overhead contact line system is being tested in Germany. In this paper, we investigate the availability and functionality of such a system based on unique real-world data gathered in the ELISA field test. We conclude that the largest downtimes can be justified by the novelty of the system. Based on our experiences, we expect a high availability of the system in the future. To substantiate our results, we first categorized the reasons for downtimes occurred. Based on this, we further analyzed these downtimes and focused specifically on the longest downtimes as one of the most influencing barriers for future operation and market implementation. Subsequently, we show how the availability of the system changes when individual reasons for downtimes are reduced in time. With our research, we pave the way to map future operating cases. We contribute to decision-makers and all people who have to decide whether overhead contact line technology should be used on highways in the future, or not.

ABSTRACT. German legislation sets forth that anthropogenic greenhouse gases must not be emitted from 2045 onward. In contrast, road freight transport is projected to grow significantly. If sustainable solutions for road freight transport are implemented swiftly, Germany will not be able to meet its climate protection targets. This study analyzes the eHighway system—an overhead contact line-based electrification of trucks—to completely erase the road freight transport’s carbon footprint. Based on more than three years of field test operation with over 500.000 real-world driven kilometers, we estimate the saving potential of directly emitted greenhouse gases from five pilot overhead contact line trucks that use the eHighway system (O-trucks). We found that with only a five percent electrified stretch of a trip, 14 to 17% of direct greenhouse gas emissions can already be saved. We argue that with an electricity mix based upon renewable energies and an appropriately extended eHighway network, road freight transport is capable of offering transport with net-zero greenhouse gas emissions. We provide a benchmark for further research in evaluating eHighway technology and for comparing it to alternative drive technologies. In addition, we make our results based on a unique data set freely available to all further research.

ABSTRACT. Aligned with the 2050 NetZero goals, the decarbonization of road freight transport is a recurring topic that has motivated considerable research works in the last few years and attracted significant government interest. In Colombia, the road freight transport sector moves 96,217 ton-km and represents 4,61 \% of Greenhouse Gas (GHG) emissions; policymakers have made progress in establishing regulations and incentives to achieve the emission reduction goals. A few works have focused on determining quantitatively the scenarios under which these policies will be effective. Consequently, the proposed work is the first in Colombia to evaluate the impact of the policies and regulations on the freight fleet configuration, logistic practices, and technological renewal decisions in the transport sector quantitatively, enabling each decision-maker to select the implementation time. A framework based on simulation is developed to determine plausible future scenarios that combine incentives and restrictions regarding the rate of adoption of different technologies using valuable freight governmental data. The simulation tool provides economic and environmental pathways to evaluate the benefits of adopting current and future policies to accelerate the decarbonization of the freight transport sector.

ABSTRACT. We aim at studying how environmental preferences matter when consumers negotiate with sellers in order to contract for delivery at home. To do that, we build an economic laboratory experiment where pairs of participants bargain for choosing either the click-and-collect option, which is free for consumer but implies for him private transportation costs, or the delivery-at-home option, which is pricey for him, but externalize transportation cost to the seller. In addition, in our game, transportation triggers environmental costs that are borne by both partners. We have 3 different treatments: The first one, as a benchmark, corresponds to an ultimatum bargaining game about the last mile cost with environmental costs. In the second one, we deliver a message about environmental impacts of transportation to the buyer, whereas, in the last one, the same message is delivered to the seller

ABSTRACT. Driving restriction policy is a commonly used measure to control congestion and air pollution in many large cities across the globe. The growing international literature that empirically investigates the effect of this policy on air quality yields conflicting findings. Yet, existing studies tend to overlook individual travel reactions to the driving restriction policies, although the policies are designed to reduce travel directly. To fill this gap, this study uses individual-level travel survey data to trace out environmental consequences of driving restriction policy through its direct effect on individual driving behavior. The new analytical framework addresses the endogeneity problem and obtains consistent estimates of the coefficients of interest, by using exogenous variables and a two-stage estimation. The point estimates suggest that, in the short run, driving restriction policy does not affect the total concentrations of PM2.5 pollutants. This insignificant relationship between driving restriction policy and air quality suggests adaptative individual behavior in response to rigid policies and calls for innovative approaches to address driving-related air pollution.

ABSTRACT. The study aims to estimate the energy demand and emissions from the tricycle sector in Quezon City using a bottom-up approach derived from the Tier 2 methodology prescribed in the IPCC Guidelines for National Greenhouse Gas Inventories and the EMEP/EEA Guidebook. In 2020, the whole tricycle fleet of the city accounted for 417,530,510.96 vkm of transportation activity with an estimated 11.36 ktoe of energy demand, or about 14.5 million liters of gasoline. Tricycle emissions considered in this study are NH3, Pb, CO2, CO, CH4, NOx, N2O, SO2, NMVOC, and PM2.5 which produced a total of 37,154.19 tons of CO2e. Policy scenarios until 2050 were simulated which include the Business-as-Usual (BUA) scenario, shift from two-stroke to four-stroke engines for tricycles, and refleeting of existing tricycles to electric tricycles. It was found that 848 e-trike units must be deployed each year to reach the goal of 30% emissions reduction by 2030 and 1,626 e-trikes yearly thereafter to reach zero emissions by 2050.

ABSTRACT. This study investigates fine particle matter (PM) levels in a Toronto community located in close vicinity to an airport and two major highways. A partnership was formed between a local neighbourhood association, university researchers, government agencies, and the local port authority to estimate transport impacts on air quality and understand the role citizen science can play in addressing air pollution. To assess fine PM levels, citizen scientists placed low-cost sensors (Dylos DC1700) on balconies and inside homes for 19 weeks between 2020 and 2022. Analyzing meteorological effects on outdoor fine PM counts, we find evidence that traffic sources increase mean outdoor fine PM. Investigation of reference station concentrations of NO2 and PM2.5 indicate that high levels of fine PM outdoors are the result of urban traffic emissions. Due to COVID-19 restrictions, the airport was not operating at full capacity during the campaigns, and thus the impact of the airport on fine PM is inconclusive. Indoors, fine PM counts increase during self-recorded indoor activities. During periods with minimal indoor activities, indoor fine PM counts closely follow the outdoor signal. Further activities are planned to assess community engagement and model the effects of different policies on reducing air pollution in the neighbourhood.

ABSTRACT. Air pollution is one of the major environmental problems globally, and it is a significant challenge to reverse the problem for low and middle-income cities in the global south. In most cities, traffic-related emissions are responsible for the highest percentage of air pollution problems. In Latin America, different strategies have been implemented to improve transportation and air quality, such as vehicle operation restrictions, vehicle fleet renewal incentives, less polluting fuels and vehicles, and infrastructure improvement strategies. However, there needs to be more documentation on the benefits of transportation policies in developing cities. Our investigation aims to provide evidence of short-term emission benefits of implemented and future strategies in Bogota. We update the emissions inventory using a bottom-up approach, coupling a transportation model with COPERT emission factors adapted to typical traffic operating conditions and the technological distribution of Bogota´s vehicle fleet. We found that light vehicles contribute more than 70% of CO and SO2 emissions and more than 50% of VOC and SO2 emissions, while transit and inter-municipal buses contribute the highest PM2.5 emissions. Additionally, we estimate short-term emission benefits of infrastructure improvement strategies compared to a scenario of no investment, obtaining a relative emission reduction of between around 2%.

ABSTRACT. We analyze whether more connected street networks such as grids are associated with more land consumption by streets. Using data from census tracts in 20 large US counties, we find a strong, negative correlation between street connectivity and the fraction of land allocated to streets. We find a similar negative correlation for recent (post-1990) development in a sample of 200 cities around the world. However, the connectivity-land tradeoff is not inevitable or mechanistic. In earlier periods of development (pre-1990), there is no correlation in the global cities sample. We identify two design approaches that avoid the tradeoff: larger block sizes, and providing connectivity through pedestrian pathways rather than vehicular-oriented streets. In particular, housing developments that prevent or discourage through movement by cars but feature extensive pedestrian cut-throughs and other paths allow cities to maintain high connectivity with little land devoted to streets. In turn, less land devoted to streets may create space for higher densities or more land for parks and other public amenities.

ABSTRACT. With the tremendous social and economic relevance of urban areas, and the environmental impacts of urban mobility, transport planning departments face considerable challenges in addressing these environmental, social and economic aspects. In this context, the paper explores preferences, challenges and barriers of urban transport planning by conducting a survey among urban transport planning authorities within the trinational Upper Rhine region. The answers obtained from the surveys were exploited by quantitative (e.g., Analytical Hierarchy Process, AHP) and qualitative approaches. The results reveal that the economic dimension of sustainability plays the most important role in urban transport planning departments, while also the requirement has been identified to engage citizens to a wider extent in the planning process. Furthermore, findings emphasize the need to strengthen the position of urban planning departments both within their own institutions and within their administrative hierarchies. Moreover, planning and implementation processes for sustainable urban mobility systems require substantial acceleration. For research, the analyses emphasize the need to support urban transport planners with the development of instruments and formats to facilitate a wider integration of citizens in the transport planning process, and to provide urban transport planners with tailor-made models, methods and data.

ABSTRACT. Accessibility is a relevant condition for social inclusion, depending on both context (transport systems, land use patterns, temporal availability) and individual features; it may be used for measuring people’s ability to participate in social life and activities that contribute to their well-being. In this frame, the paper proposes an Inclusive Accessibility by Proximity Index (IAPI) as a tool for assessing active mobility-based accessibility levels to the services deemed essential for local inhabitants while recognizing the impact of the physical and perceptual characteristics of urban spaces and paths on active modal choices. By considering the responses of different mobility profiles (pedestrians, cyclists, people with reduced mobility) to the urban environments they live and cross daily, IAPI can help direct the construction of planning and urban design measures aimed at promoting walkability and cyclability and improving accessibility via active modes to everyday services, thus envisioning a more sustainable and inclusive city. Taking a cue from the experience conducted in the testbed of Bologna (Italy), the paper describes the methodology for constructing and applying the index, presents the results obtained, and outlines the future steps planned to make the tool more scalable and sensitive to the contexts of use and analysis.

ABSTRACT. This paper uses a unique dataset for 2,535 Singapore residents aged 55 to 70 years in 2021 to investigate three related questions important for transport planning in Singapore: (i) the predictors of one-way commute time longer than 45 minutes; (ii) the relationship between commute time and life satisfaction; and (iii) the relationship between working from home (WFH) and life satisfaction. We found that 45.5% of Singaporeans living in flats built by the Housing and Development Board (HDB) and using walk-cycle-ride (WCR) modes were intensive travelers with one-way commutes of over 45 minutes. Transport and land use planners seeking to increase usage of WCR modes and reduce commute times should provide more direct public transport services, reduce walk-and-wait times, disperse employment closer to non-mature HDB estates, and encourage working from home (WFH). Contrary to the “commuting paradox”, longer commutes did not correlate with lower life satisfaction. The 2020 pandemic led to a dramatic shift to WFH. By 2021, 30% of respondents reported WFF with WFH more prevalent for higher-income workers. WFH did not appear to be associated with higher levels of wellbeing; however further research is needed on this relationship, especially for workers aged 18 to 55.

ABSTRACT. This paper focuses on characteristics that are invariant to local transport policy and examines the associations of these so-called contextual factors with car use and car ownership. Based on a sample of 44 large German cities, regression models illustrate that contextual factors explain a substantial share of variance regarding car trips and car ownership at city level. In comparison with car trips and car ownership, the variance explanation for car distances is rather moderate. Residual analyses demonstrate that neglecting contextual factors leads to biases in comparative studies and consequently in the evaluation of urban transport policies. There is a risk that cities with favourable contextual factors may be mistakenly viewed as successful examples of transport policy, whereas successful policies in cities with less favourable contextual factors may be overlooked.

ABSTRACT. The direct observation of cars, pedestrians, cyclists, and other street users is necessary to evaluate the three main street functions, namely mobility, access, and place. Therefore, a methodology for collecting, preprocessing and analyzing data of street users based on video data analysis is presented in this paper. In the proposed methodology, the trajectories and the types of street users, their instant speed, and direction of movement are automatically extracted from the collected videos. These data are then analyzed in a new software tool, the Studio application, to derive street function evaluation indicators. The proposed method is applied to comprehensively assess the changes after speed hump installations in four residential streets in Montreal, Canada. The results demonstrate the value of direct street user observation and the proposed semi-automated method. The empirical results of the proposed method show that the speed of cars has decreased by 20-30% at all sites, while there have been significant changes in the flow and characteristics of vehicles, cyclists, and pedestrians in the study areas.

ABSTRACT. Although there are various studies that evaluate the optimal design of public transport systems in radial structures, there are few that analyse which urban characteristics are relevant to recommend different public transport modes, particularly in small towns that lack the resources needed for such studies. Based on results from social cost minimization models, we classify small and medium-sized cities of Chile into three categories according to population, density, CBD location, and topography. For smaller towns (type A) subsidies to regular public transport seem unnecessary. In intermediate cities (type B) our models recommend promoting public transport services through shared taxis, a typical transport mode in Chilean cities in which a taxi carries up to 4 passengers on fixed routes or zones. Finally, in the largest cities in the sample (type C), it is recommended to subsidize the operation of bus services that produce less externalities than shared taxis, particularly congestion in the city centre. The methodology used can be extended to more complex structures and incorporate data from other countries, in order to formulate useful public policies in diverse contexts. That said, transitions between categories are challenging for the governance of public transport systems and should be considered in further studies.

ABSTRACT. Public transport services represent one of the main solutions for promoting a more sustainable urban mobility system but, in many Italian urban areas, there are still many critical issues about the level and quality of offered services. Starting from such issues, this study proposes a new method for the estimation of the overall annual level of bus services, for overcoming the limits of the existing models, hardly dependent on the historical expenditure criterion. The new method is based on the identification of the effective transport needs and the robustness and availability of the input data. The database built for the study is related to 54 municipalities, with a population from 80,000 to 360,000 inhabitants, and it is composed by a large set of indicators about supply and demand of the bus services network and of the territorial characteristics of the municipalities. The definition of the level deals with the systematic analysis of the bus network characteristics and riderships in many Italian cities and towns, characterized by a supply of public transport services mainly based on buses.

ABSTRACT. The need for a better measure for the context of understanding accessibility levels to public transit (bus) services in an urban environment was identified via the study. It evaluates the factors that need to be considered affecting the concept of "ease of access" in a sustainable platform. Evaluating the available sustainable transportation measures, models, and tools gives a comprehensive understanding of the avenues that have been considered and the quantitative and qualitative disparity among the existing indicators. The Sustainable Urban Transportation Accessibility Scorecard (SUTAS) was developed in response to the demand for more accurate and measurable indicators of accessibility to public transit services in urban settings. The incorporation of indicators focused on highlighting the accessibility quotient and striking a delicate balance between giving adequate space to the other dimensions of sustainable transportation. This inclusiveness strengthens the scope of the improved criteria with solid quantitative outcomes. The study further elaborates on how every indicator can be improved to increase the validity of its score by highlighting its parameters. Thus, the developed SUTAS can assess the accessibility quotient to public transit (buses) in an urban context, both in terms of individual city assessment through a timeline and in comparison amongst cities.

ABSTRACT. Transit ridership prediction models have traditionally been developed using aggregate data at the stop, route, or neighborhood levels. In contrast, less attention has been given to developing ridership models for different groups of transit users, including groups of users that use the transit less frequently, such as cash fare users. This study aims at providing an empirical investigation of the factors affecting the use of transit by different segments of users. Using data extracted from Saskatoon Transit’s farebox system, several segments of users are defined based on their travel patterns (i.e., frequent, in-frequent, and casual users) and the used fare payment method. Fare options analyzed include using exact cash payments, disposable cards, smart cards loaded with multiple options (monthly, yearly, economic), and multi-ride packages (10-ride packages). The results of the models suggest the usage of transit is more associated with built environment and transit service internal factors, than socioeconomic factors. The study provides transit planners and professionals with a better understanding of the relationship between the built environment, transit service, and socioeconomic factors and the use of transit by different groups

ABSTRACT. Integrated passenger freight transport (IPFT) is a tactical solution that can potentially reduce travel demand and, hence, the costs of first- and last-mile services. Although scientific interest in the study of IPFT has increased in the last decade, IPFT contributions are mostly related to the definition of a general framework, whereas several operational aspects remain less investigated. To address this research gap, a Delphi survey was conducted among international stakeholders who have already worked in this field. The aim was to verify the minimum requirements satisfied upon the introduction of the IPFT in both urban and rural contexts as well as fare reduction for users, which are necessary to compensate for the differences compared to passenger-only and freight-only services. The results of the survey indicate the necessity of an efficient service in terms of information, environmental footprint, and security for passengers (but less for freight transport), while other attributes, such as cleanliness on board, reveal discrepancies. These findings are useful for policymakers and practitioners who can use them as a benchmark for the definition of service performance requirements that must be satisfied when designing a new service.

ABSTRACT. A great interest of Smart Transportation System operators is to use data to understand its complex dynamics and make their decisions accordingly. While there is an increase in accessible data, current methods suffer from various gaps: traditional statistical methods are limited in processing new types of data, and often impose strong constraints (e.g., parametric function form, linearity); traditional transportation engineering methods (as simulation models) often come with heavy computational complexity; and Machine Learning (ML) tools tend to rely on statistical associations. Defining causal knowledge from the transportation domain for ML models can potentially overcome those gaps; however, it is done implicitly without a formal framework. This interdisciplinary research proposes a Hybrid Dynamical Systems Thinking Approach (HDSTA), using systems thinking for causality interface implementation for data-driven decisions in transportation. HDSTA will provide guidelines on how different parties as experts, data scientists, and Transport Management Centers (TMCs), can work together to define a knowledge graph for the transportation system model. The outputs, a graphical and text description, will serve (1) experts in choosing and defining the variables' cause-effect relationship; (2) ML modelers in defining a causal function; (3) TMCs in making data-driven decisions for the benefit of the public.

ABSTRACT. Two lane two way roads constitute a major portion of road network in India. A major proportion of head on collisions occurring on two lane undivided highways are due to passing maneuvers that drivers fail to complete safely. Passing maneuvers are very complex and risky. Detailed observation and understanding of these maneuvers has significant implications on traffic flow and safety. The main objective of the present work is to analyse the passing characteristics of different categories of vehicles on undivided roads under heterogeneous traffic in different flow conditions. The passing characteristics of different types of vehicles under heterogeneous traffic conditions were observed and the relationships of various parameters involved were investigated. Also the effect of flow rate on passing characteristics is analysed. Binary logistic regression model was used to determine whether the available gap is accepted for passing on the basis of gap size and gender. Models were developed to predict the duration of passing also. The results obtained from this study will be useful to understand the passing characteristics of vehicles in heterogeneous traffic conditions. The understanding of parameters related to passing will be useful inputs in the development of micro simulation models for heterogeneous traffic.

ABSTRACT. This research attempts to understand decisions regarding the tour mode in educational tours, which include tours for schools, training courses, higher education, postgraduate education, and all other institutions that provide professional qualifications. Once the tour patterns have been established, one step in the Activity-Based Model (ABM) that must be taken into account is tour mode estimation. The quality-of-service attributes and tour/trip specifics all have an impact on the mode of travel, as do the socioeconomic and demographic characteristics of individuals and households. Using these influencing factors, a choice model must be created to estimate the tour mode. The primary objective of this study is to estimate models to understand the tour mode selection of students enrolled in both school and higher educational institutes in the Western Province of Sri Lanka. The household visit survey data from the Urban Transport System Development Project for Colombo Metropolitan Region and Suburbs (CoMTrans 2013/14) was used to compile the necessary trip information. The approach used to estimate the tour mode choice model is described in this publication. The authors present a method to identify the tour modes from the trip modes.

ABSTRACT. The present study evaluates the capacity and Level of Service (LOS) of the Electronic Toll Collection System (ETC), commonly known as FASTag in India. For capacity analysis, service headway is considered. The service headway is composed of processing time (includes reading the FASTag) and the clearance time of the vehicle. Videographic data were collected at three different toll plazas located on National Highway (NH-48) in India. The results showed that compared to the Manual Toll Collection (MTC) system, the capacity increased by 77% with FASTag lanes. Further, a model for capacity estimation based on traffic composition is developed. Lastly, the LOS thresholds are developed based on volume to capacity (V/C) ratio. Field engineers will use the present study thresholds to evaluate traffic operations at FASTag lanes.

ABSTRACT. Worldwide growth of cities is unstoppable and a great challenge for urban development and architecture. The existing transportation facilities and buildings do not always provide a suitable level of safety, and level of service. The present study focuses on analyzing the effect of composition (population), inclusion of buffer space and door widths on the capacity of a doors. The relationship between total times versus door width and capacity versus door width were established. Capacities were estimated for a room with single door and double doors with different composition. Comparison of capacities for a room with single door and double doors (Door-1 and Door-2 are 1m apart) has been done for 100 cm width with different composition. It was observed that capacity increases as the width of the door increases in a room with single door. In the case of room with double doors, the congested flow observed in Door-1 and uncongested flow observed in door-2 due to herding behaviour.

ABSTRACT. The present study deals with the design aspects of the queue area length and number of toll lanes required at the toll plazas. The queue data and service headway data are collected at seven different toll plazas in India. The linear relationship is developed between average and maximum queue length. Further, the level of service (LOS) thresholds are develop based on queue length using k-means clustering. The queued vehicles are considered due to ease in the estimation of the count of vehicles in queue practically in the field. The result shows that for design LOS-C the queue area length should lie between 102.00m to 174.24m. The output of the present study will be useful for better design of queue area length in the field, to cater to the upcoming traffic demand. The queue length is further correlated with queue delay for determination of the time required to clear the tollbooth. Moreover, the required number of toll lanes with an increase in the use of Electronic Toll Collection(ETC) locally called FASTag is also evaluated. The present study can be used to field engineers for designing the queue area length and number of toll lanes in prevailing traffic conditions.

ABSTRACT. Testing Sidewalk Autonomous Delivery Robot (SADR) safety performance under real world conditions is important to evaluate readiness for large-scale deployment. Currently, testing SADRs for their safety in public is not allowed in the Netherlands. Little is known about the risks associated with SADRs, and the risks are difficult to assess because the robots are of a novel category and continuously evolving. In this study a dynamic assessment framework for the safe and sustainable performance of SADRs is proposed. This assessment framework is premised on different levels of difficulty of the Operational Design Domain (ODD) and proposes to evaluate the safety performance of SADRs against location characteristics that cause this difficulty. The ODD difficulty of an operational environment can change over time due to changing factors in the urban environment. These factors include changes in infrastructure quality and traffic levels, but also growing complexity of tasks in a living lab. By recognizing that an ODD is not static, SADR development can be driven by progressive performance assessments geared towards sustainable performance. Also, SADRs can be safely tested in public, because by applying the dynamic assessment framework within living labs, ODD-specific testing exemptions can be awarded to SADRs with specific, dynamic configurations.

ABSTRACT. Road crashes continue to be the leading cause of death across all age groups despite several efforts being taken by the government and non-government organizations. The brunt of traffic fatalities affects males and females differently. Studies on assessing gender-wise exposure to road safety are limited in the Indian context. Therefore, an attempt is made to understand the role of gender in fatality-risk assessment. The aim is to evaluate the change in exposure to different motorization growth scenarios for males and females. Fatality-risk model is developed based on the interaction between the victim (pedestrian, bicyclist, two-wheeler, car, and bus) and threat (pedestrian, bicyclist, two-wheeler, car, bus, and environment) road users combined with the at-risk distance travelled by modes for Bangalore Metropolitan Region, India. Traffic fatalities are estimated based on the severity of the interaction between victim and threat modes. Significant reduction in road crashes for both genders is observed for the High Bus scenario, which assumes that 80 % of the total motorized distance is travelled by bus. Maximum traffic deaths are estimated for the High Car scenario. The study can be extended to the simultaneous evaluation of multiple road users.

ABSTRACT. Several studies in high income economies indicate that young and novice drivers are more likely to be involved in motor vehicle crashes MVC, especially those with fatalities. This topic has not been explored in middle- and low-income economies in the global south. We estimated associations between the number of road crashes and fatality probabilities with driver characteristics using a random forest algorithm, applied to the official driving license and crash data in Colombia between 2007 and 2020. We find that age accounts for 32.5% of the risk of an MVC and experience for 25.5%. In the case of fatal MVC driver’s experience accounts for 53.5% importance and age at 25.0%. We also show the interaction of these two factors for different types of licenses and show that probability of MVC and fatal MVC decreases with the combination of age and experience, with thresholds between one year for motorcycles and three years for light duty vehicles. These results are useful in advancing new licensing requirements, like novice driving license with restrictions, to help reduce the high incidence of injuries and deaths from MVC in Colombia. The methodology is also applicable for studies in other countries when analyzing large databases.

ABSTRACT. Increase in traffic noise especially by motorcycles at residential roads is a common concern for many residents affecting their living environment. This paper attempts to measure the noise characteristics at few predetermined points along four residential roads in two different residential areas. The selection of points to measure noise level at the selected residential roads is to understand the changes in noise level as the vehicles approach at and near the road humps. To corroborate the field measurement of noise level at the residential roads, this study also considered the perceptions of the residents in the selected residential areas on the effects of road humps in reducing traffic noise level. The results show though the traffic noise levels before and at the road humps decrease significantly but it is not the case at points immediately after the road humps as the vehicles begin to increase its speed. The relationship between the residential areas and the perceptions of the residents on both daytime and nighttime noise level was found to be statistically significant. The perceptions of the residents on whether road humps can reduce traffic noise were also found to be statistically significant when related with the residential areas.

ABSTRACT. Regardless of how fuel efficient the cars are or how little pollution they emit, cars need to be parked somewhere and the average car spends about 95 percent of its life parked. National Urban Transport Policy- 2006 of India suggests that the parking charges should be calculated based on the real estate value of the land on which the cars are parked and bringing restrictions in the supply of parking. At present India follows a parking minimum approach. The main objectives of the study include the assessment of existing parking norms, parking supply, and demand. The study proposes to change the pricing method based on the real estate value and assess its acceptance by using a willingness to pay survey. A combined revealed and willingness to pay survey was conducted to understand the existing parking behaviour and response to the new parking pricing method. People have shown a willingness to shift to public transport with the introduction of parking pricing. The study also probed the possibility of introduction of penalties in the case of development control violations.

ABSTRACT. Illegal parking of vehicle on roadside is one of the current issue that attract significant attention of the transportation planners. In developed world, several studies have been conducted on this issue. However, limited literature available in the developing countries. Thus this study was the first attempt of such study in Afghanistan as a case of developing country. This study aims to compare the current demand and available capacity of the vehicle parking areas in Khost city. In addition, the personal attributes and behaviors have been investigated for the drivers who have parked their vehicle on the roadside illegal as well as in the legal parking areas. The data was collected using the countering method (for the demand and capacity comparison) and interview method (for the drivers’ attributes and behaviors). It was found that those who were fine before, have experience of living abroad and military personnel were more likely to park their vehicle in the legal parking area. In addition, the respondents who have not been fined, as well as those who have private business and those who are not educated were willing to park their vehicle illegally on the roadsides.

ABSTRACT. This study analyzes the effects of various variables on bus service quality, as well as how service quality and personal attitude affect overall satisfaction with public buses. A total of 552 responses were collected using a questionnaire which capture factor analysis was used to uncover unobserved latent features and to generate two measurement models: for service quality and personal attitudes of bus users. Subsequently, Structural Equation Modelling approach was used to estimate interrelationships among aforementioned parameters. Three latent variables were identified representing service quality and two latent variables were obtained representing personal attitude of customers. Information, safety, and security (γ = 0.61) had the most major influence on service quality followed by comfort (γ = 0.43), and accessibility & availability (γ = 0.36). Similarly, perceived value (γ = 0.79) had greater impact on personal attitude than that of behavioral intention and involvement (γ = 0.56). Overall satisfaction of customers with bus services was influenced by the service quality of buses more than personal attitude. The findings of this study will be useful for government, planners, and operators to implement new strategies to boost customer satisfaction with public buses.

ABSTRACT. In this paper we address the problem of designing the logistics network of a fertilizers manufacturing firm operating in a developing country. The objective of this study is to establish a transportation and warehouse development plan to support the new distribution chain of a world-class manufacturing firm in Ethiopia. We focus on the distribution component, and investigate decisions about the number, size, location and management of warehouses, the selection of the transport mode, the allocation of products to warehouses and the flow of products throughout the network. Considered as a decision support tool, the mathematical model is flexible and integrates strategic and tactical decisions. Realistic business models were used to explore three possible configurations of the distribution network. Each scenario was evaluated and measured through a detailed numerical study.

ABSTRACT. Road networks with in metropolitan cities are witnessing humongous traffic congestion, and this hampers the public transit connections with in the cities. Consequently, the expansion of cities routes around peripheries, and connections with the suburbs industrial area for logistics has become cumbersome for the end users. For effective implementation of mobility plans in Indian cities, there is a necessity to investigate the network connectivity of Indian cities as a precursor to the initiation of these plans. In this study, we have assessed the existing road network structure of two rapidly developing, manufacturing and industry-based metropolitan cities of India namely Nagpur (Maharashtra) and Indore (Madhya Pradesh). The research paper involves examination of built structures, Kernel road density (road centreline density) and gross density (total area under the roads) through spatial assessment. The approach for network assessment inculcates Graph-Theoretic measures, by creating undirected road transport network graphs (only links and edges). The study is done on micro (intra-city) and macro (inter-city) level for parameters like alpha, beta and gamma measuring connectivity. The evaluation of alpha, beta, gamma and kernel density indicators in Nagpur and Indore ponders on emerging need to re-evaluate the public transit connections of the cities.

ABSTRACT. Many Vietnamese medium-sized cities are facing rapid urbanization and population increase, putting pressure on controlling private vehicles and developing public transport. The majority of urban traffic in Vietnam is borne by private vehicles, especially motorcycles, which account for 65 percent of travel demand and more than 80 percent of mixed traffic flow. This paper examines the joint effects of household vehicle ownership and other factors using household travel survey data collected from residents in Can Tho, Vietnam. Estimates from the multinomial logit model reveal that motorcycle ownership, along with other socioeconomic factors, trip purpose, personal attitudes, and spatial environment factors, has a strong influence on mode choice. These results strongly suggest that a connection between motorcycles and public transport should be further considered when developing the overall transport strategy in motorcycle-dependent cities. The motorcycle will provide high local accessibility for short distances and public transport feeder services, they perform a valid and valuable function. Therefore, careful consideration of motorcycle access and use may be required and the role of motorcycles should be recognized in future public transport planning.

ABSTRACT. School trips share a significant portion of the traffic in peak hours in Colombo, Sri Lanka. Therefore, understanding the distribution of school trips among predefined origin and destination zones is important in managing school traffic. The applicability of the studies carried out in other countries to the Sri Lankan context is limited due to the socio-economic factors in the study area. This study mainly focused on identifying the distribution of home-to-school trips within Colombo, the capital district of Sri Lanka. A methodology is developed using home visit survey data to construct a travel O-D matrix for home-to-school trips attracted to the government schools located in the Colombo district, followed up by mathematical models to estimate the school trip distribution. The outcomes are presented using an O-D matrix for home-to-school trips followed by O-D desire lines. Further, the study uses multiple linear regression techniques to identify mathematical models to estimate the number of inter-zonal and intra-zonal school trips between origin-destination pairs in the study area. The mathematical models proposed in this research can be calibrated and used for other developing countries with similar school education systems for better estimations.

ABSTRACT. This article applies supervised machine learning tree-based algorithms to predict the performance of flexible pavements. The algorithms used were Decision Tree, Random Forest, and eXtreme Gradient Boosting (XGBoost). Likewise, the International Roughness Index (IRI) was adopted to represent the pavement's quality. Data to develop the machine learning models were collected from the Long-Term Pavement Performance InfoPave database. From this database, 55 experimental sections of asphalt concrete on granular base and asphalt concrete on bound base were selected. Also, only pavements without maintenance or rehabilitation were considered. For training the models, the features were the structural number, annual average daily truck traffic, precipitation, and temperature; IRI was the target. Finally, the best model developed was the XGBoost (R-squared of 0.98), followed by the Random Forest (R-squared of 0.95).

ABSTRACT. Departments of transportation (DOTs) are responsible for maintaining the roadway network at certain pavement levels and operational performance. While these two metrics are often looked at separately, we developed a framework in a previous study that integrates pavement and operational considerations and allocates for the interaction between them. This paper expands on the developed framework to zoom in on a work zone allocation module that better represents realistic operations and constraints while making decisions at the network level. The focus of this paper is on the development of a systematic and comprehensive methodology to optimize the allocation of networkwide pavement treatment work zones over space and time. We hypothesized that an adjacency function would be highly correlated with the travel time obtained by running a full-scale simulation. The findings indicated that the adjacency computation achieved a high R squared of 0.96, which confirms the hypothesis of the strong relationship between the developed adjacency function and network travel time.

ABSTRACT. The objective of this study was to investigate the economic viability and assess the sustainability of various pavement maintenance and rehabilitation strategies of flexible pavement. The major research scopes included formulation of maintenance strategies based on Pavement Condition Index, assessment of cost-effectiveness through Life Cycle Cost Analysis (LCCA), and estimation of environmental impact through Green House Gas (GHG) emissions. At first, a flexible pavement section was designed with an analysis period of 18 years with three alternative strategies that include standalone and a combination of patching, mill and overlay. Next, LCCA was estimated and it was found that mill and overlay at every 10 years interval offers the most cost-effective solution. Furthermore, Life Cycle Assessment was carried out at various stages of construction. The findings revealed that mill and overlay had the minimum GHG emission followed by the alternative that combines patching and mill and overlay. In summary, mill and overlay was found to be the cost-effective and sustainable maintenance strategies among other alternatives. Overall, it was envisaged that the methodological framework developed in this study would help road agency, policymakers, and other stakeholders to devise rational alternative strategies and then decide the cost-effective and sustainable solution for flexible pavements.

ABSTRACT. Whitetopping is an efficient rehabilitation strategy for distressed bituminous pavements to extend their service lives. Concrete overlay is placed over existing bituminous pavement with shorter joint spacing and a lesser concrete thickness. In this type of pavement, dowel bars are not provided and the load transfer is done by the natural mechanism of interlocking action of the aggregate particles. This paper investigates the influence of overlay thickness, bituminous layer thickness, its elastic modulus and bonding condition on the load transfer efficiency (LTE) of the aggregate interlocked joint in whitetopping. A three-dimensional fnite element model of whitetopping has been developed for this purpose. The results indicate that the stiffness of bituminous layer in load transfer is more prominent for thinner concrete overlay than a thicker one. For lower thickness, the stiffness contribution of bituminous layer is more pronounced for bonded interface condition than for an unbonded one thus affects the flexural stress and the LTE. With increase in overlay thickness the flexural stress is found to reduce significantly for all configurations.

ABSTRACT. A modified wheel tracker testing method is used to understand better the rutting failure of flexible pavements made of Hot Mix Asphalt (HMA). Flexible pavement rutting is one of the most noticeable pavement distresses worldwide when subjected to traffic load and is a significant safety concern to transportation agencies because it affects the handling of vehicles. Asphalt slabs or cylindrical cores are typically inserted into a steel container and tested in this manner. As a result of this research, a new wheel tracker test rig was developed and constructed to measure the material's response to the load applied accurately. This study aims to analyze the influence of various aggregate gradient percentages and test the rutting resistance of asphalt mixtures using modified wheel track equipment. The experiment included hot mix asphalt samples with aggregate gradations up to 19 mm and three different aggregate sizes.

ABSTRACT. Geogrids are commonly used for pavement layer reinforcement and to build a construction platform over weak subgrade soils to carry equipment and facilitate construction of pavement without excessive deformations in the subgrade. Geogrid reinforcement is used in permanent paved roadways in two major application areas – base reinforcement and subgrade stabilization. The present study applied the AASHTO (1993) (Guide for Design of Pavement Structures), IRC: 37 (2012) (Guidelines for the design of flexible pavements) and IRC: SP: 59 (2019) (Guidelines for use of geosynthetics in road pavements and associated works) methods for design of geogrid-reinforced pavements using 20-year design life. Relevant design data were obtained to design the pavement, and a comparison was made between different design results.

ABSTRACT. This study investigating the perceived challenges of all tourism in Nigeria. To do so, Primary data were employed to achieve the set objective using descriptive and inferential statistics. The primary data were elicited through a well-structured and concise questionnaire. It was observed from the regression analysis output that the most significant variables that influenced most (has the greatest influence for challenges to air tourism as considered by the arriving international passengers at the MMIA were (in descending order) lack of awareness, lack of all-in-one package, price of packages, poor transport connectivity and fear of security and safety issues. It was noted that all the factors were very significant.

ABSTRACT. The SARS-CoV-2 pandemic became a turning point for the global air industry as it stopped normal operations, with different regional and national markets closing themselves to either stop or curb the spread of the virus. Those extraordinary administrative measures put an essential strain on the ability of airlines to operate regularly, thus creating a rationale for the disbursement of state aid. The article presents the state aid system for air carriers domiciled in Poland and the entire air transport industry. The Polish market is relatively small, corresponding to less than 4.5% of all passengers transported by air in the European Union in 2019. The article describes the impact of the system of public support measures on the only two airlines still domiciled in Poland that provide regular transport services – LOT Polish Airlines (the historical/national air carrier) and ENTER Air (a charter air carrier that during the last ten years has debuted on the regular transport services market). Even though the treatment of those two entities was not equal, the measures provided helped stabilise their financial conditions from 2020 to 2021. However, their future growth prospects will be heavily impacted by inflation-induced cost rise in 2022 and subsequent years.

ABSTRACT. Adverse effects of urban freight transport intensify in cities of developing nations due to limited infrastructure and faster growth rate. The present study of Surat, India is a case where 40% of the total freight trips generated by the textile manufacturing industry alone. The city witnessed an average annual growth rate of 13% in the last decade. Majority portion of the textile manufacturing industry is located in old city which has dense land use and narrow streets. The industry is developed in clusters spread across the city and therefore generates several local freight trips during the manufacturing and value addition process. Total freight trips from the industry are estimated and major routes affected due to textile freight movement are identified. A 3 kilometer stretch of city’s ring-road is bottlenecked thereby affecting major corridors connecting rest of the city. An alternate network is proposed and simulated over the existing network. Benefits from the proposed network in terms of reduction of the overall traffic and improvement in the level of service along the major corridors are discussed. The study aims to improve the traffic flows in dense commercial area with minimum modification in existing land use.

ABSTRACT. Small Air Transport (SAT) is defined as services operated by airplanes with passenger capacity between 9 and 19 seats and pressurized and unpressurized cabin compartment. SAT currently represent a small niche of air transport services, but having the potential for contributing to the connectivity of regions. This paper introduces the strategic model DESAT (Demand for European Small Air Transport), designed and implemented to estimate demand for SAT services in Europe. The model covers 30 European countries (EU27, United Kingdom, Norway and Switzerland) with a zoning system including more than 1,400 zones. Within DESAT model, SAT is considered one of the available modes of transport for trips between zones, in competition with conventional air services, car, train, coach and, in some circumstance, ferry. The focus of the DESAT model is the estimation of the market share of SAT services, for the base year 2019 and for future years from 2025 to 2050 in five years steps. The main outputs are the number of yearly SAT passengers and the corresponding number of flights. The user interface provides aggregated indicators and some mapping of zone-based estimations, while results by OD pair are also produced and can be downloaded for more detailed analysis.

ABSTRACT. This study investigates carbon emissions of consumer goods companies in urban delivery transport with improvements in several aspects: 1) disentangling the emissions based on their driving patterns; and 2) applying a consumer goods company's perspective. The emission of one-month urban delivery assignments from a consumer-goods giant in Shenzhen, China is analyzed. Results show that the driving operation of acceleration is the most effective driving operation in creating emissions. Distance, gross vehicle weight, and rate of low-speed roads are the top-3 effective influencing factors on emission. An associated discussion is also given. It is hoped to deepen the understanding of emissions in urban delivery transport from a company's perspective and provide insights for policy-making.

ABSTRACT. Landside capacity is determined by facility operation, management action is an important part of measuring it. These management measures link the capacity assessment process to long-term airport planning. Recognizing these needs and their potential financial, managerial, and community consequences may prompt a rethinking of what "adequate" landside capacity entails, leading to eventual agreement among all parties that the issues are well understood and proposed solutions are reasonable. First, consider balancing service across components or other short-term capacity solutions. Stronger traffic enforcement may reduce curbside congestion when taxi dispatching and courier service access are improved. This paper deals with the development of the methodological framework for landside development activity nodes in a new Mediterranean tourist airport, based on different revenue streams. A series of fundamental, layered plan concepts contribute to the overall framework for development of Airport Landside area development. Their composition and interaction on the site represent the physical manifestation of the Development Principles and inform the concepts and policies of each Framework Plan Element. The landside development plan addresses the unique characteristics, needs, and impacts of landside area development in a new airport. Understanding the key issues and concerns of the stakeholders is critical to creating a successful plan.

ABSTRACT. This paper attempts to analyze the impact of the covid-19 pandemic on the Indian airlines and mitigate the possible way outs to bring the aviation sector back to pre-covid-19 times. A comparison of passenger numbers in India and global aviation for the pre and post COVID-19 period is highlighted. This study uses the autoregressive integrated moving average (ARIMA) to forecast air passenger and freight demand for the Indian aviation industry. Findings suggested that ARIMA, is appropriate for short-term forecasting of all four commercial aviation sectors (international passengers, international freight, domestic passengers, and domestic freight). The Indian aviation business is susceptible to losses due to its vulnerability to cyclical economic disruptions such as fuel price increases, inflation, currency devaluation, and demand shocks. This study will help in knowing the recovery of the airline market and the way out to achieve pre-Covid numbers of demand and supply.

ABSTRACT. Urban freight distribution contributes greatly to trading activities and the dynamics of a city. As much as it fulfills consumer needs, it also has certain negative impacts. The negative economic impact involves infrastructure damage, congestion, wastage of resources, and traffic inefficiency. Fixed costs, transportation costs, and penalty costs must be taken into account when calculating the cost function. The capacity of the delivery vehicle is higher than the total goods it carries and the time duration at each stop must not precede the pre-defined time window. The dairy sector in India is predicted to develop at a CAGR of 14 to 16 percent. The transportation cost during shipment of perishable goods includes only fuel cost. The fuel cost is directly dependent on the distance of transportation. The urban distribution is one of the major factors in supply chain and as the urban freight is increasing this distribution need to work more efficiently and with minimize cost and lose. This paper focuses on the study of Bhopal Sanchi dairy by looking into its existing supply chain and using ArcGIS software for analyzing route optimization, and recommendation of routes, which also helps in fleet optimization.

ABSTRACT. The modelling of the transport sector varies broadly in scopes and methods when looking at the fields of transportation research and energy systems analysis. This is mostly due to the interdependence and interoperability of the transport and the energy sector. When analysing these two different research fields the modelling of the charging infrastructure for battery electric vehicles varies greatly in methods, assumptions, and data availability even for the same specific modelling scope. Semantic web technologies such as ontologies are in this context a useful tool to address the issue coming from the volume and diversity of the data involved and provide a formal common knowledge representation. A number of ontologies exist both for the transport as well as for the energy sector, but as the modelling of future mobility-energy systems requires an integrated approach between the two sectors, it is not always clear where the boundaries are and how these relate to each other. The purpose of this work is thus to provide an overview of the overlaps and boundaries between these two sectoral representations and research fields, and a starting point for the definition of their interactions by providing an operational example of data harmonisation using graph data structures.

ABSTRACT. Understanding the impact of various factors on train arrival delays is a prerequisite for effective railway traffic operating control and management. Existing studies model the train delay prediction problems using a single, generic equation, restricting their capability in accounting for heterogeneous impacts of spatiotemporal factors on arrival delays as the train travels along its route. The paper proposes a set of equations conditional on the train location for predicting train arrival delays at stations. We develop a seemingly unrelated regression equation (SURE) model to estimate the coefficients simultaneously while considering potential correlations between prediction residuals caused by shared unobserved variables (e.g., driver characteristics). The operational data for high- speed trains on Sweden’s Southern Mainline from 2016 to 2020 is used to validate the proposed model and explore the effects of operation-related factors on train arrival delays. The results confirm the necessity of developing a set of station-specific delay prediction models to understand the heterogeneous impact of explanatory variables, and SURE provides more efficient parameter estimations than the traditional ordinary least squares regression (OLS). The important factors impacting train arrival delays include the scheduled and actual running time, scheduled dwell time, and train arrival delays at preceding stations.

ABSTRACT. This study reconstructs ancient China's transport system, exploring its intersection with societal networks. We begin by procuring population data indicative of years 2, 742, 1102, and 1522. The transportation matrix, inclusive of roads, rivers, and canals, is subsequently reconstituted. In continuation, we ascertain the transport accessibility for heavy goods. Our accessibility model reveals that history lends itself to a more coherent explanation through quantitative research. We then deploy a gravity model to examine the correlation between transport systems and social networks. The model delineates how transport, particularly travel duration, influenced societal interconnections. The implemented gravity model further highlights the steady deterrent of travel time, suggesting that transport infrastructure might sustainably govern social networks on a historic spectrum. Finally, our research draws on the analysis of five key capitals throughout history, along with other connections inadequately modeled by the gravity approach, to discuss the self-perpetuation effects of social networks. We discern that cities with elevated political stature or a sizable population/economic foundation tend to exhibit a more robust self-reinforcing influence on their social networks.

ABSTRACT. Digital technologies have become essential tools that enable traceability in supply chains. In low-income countries, traceability represents a challenge due to the complicated structure of the supply chains and the involvement of multiple stakeholders. Thus, it is vital to construct a framework for digital traceability systems (TS) that can be implemented by low-income countries. This research developed a framework for digital TS, using the Ethiopian coffee supply chain as a case study. Although the implementation of traceability technologies in the Ethiopian coffee supply chain is still low, the results of the logistics audit revealed that the usage of traceability technologies improves downstream of the supply chain. The traceability framework developed in this study ranges from paper-based TS to fully digitalised TS. Stakeholders from low-income countries can use the framework developed in this study to adopt a TS for their supply chains in line with their needs and current digitalisation levels.

ABSTRACT. Shinkansen, a high-speed rail in Japan, has been in use for approximately 60 years since it started service in 1964. The Shinkansen has promoted the movement of people and has had a significant impact on the demographic changes of the areas along the Shinkansen lines. This study aimed to analyze the population change around the Shinkansen station using tertiary grid data from the National Population Census. Specifically, we estimated the causal effects of Shinkansen stations on population changes in the surrounding areas between 1995 and 2015 using the propensity score method. In the analysis, we calculated the average treatment effect in the treatment group (ATT) using the weighting, stratification, and matching methods of the propensity score method. In particular, the propensity score matching method calculates ATT using subclassification matching, nearest neighbor matching, and caliper matching, and the results are compared and examined. Finally, the inverse probability weighting (IPW) method was used to calculate the average treatment effect (ATE), which was compared with the results obtained by multiple regression analysis. The findings show that the population grew by an average of approximately 300 people per block within a 15 km radius of the Shinkansen stations.

ABSTRACT. Urban consumption is becoming more multi-channel. E-commerce has prompted the development of new kinds of freight facilities. The Covid-19 pandemic interrupted supply chains, and increased consumer dependence on online purchases resulting in the birth of Q-commerce, a new sub-vertical in the E-commerce business. There is little understanding of the characteristics, requirements, and impacts of this sector both in literature and in planning documents. The objective of this research is to understand the freight patterns and their associated externalities within an urban area for this emerging trend in E-commerce and assess if planning documents address these issues adequately. The paper is developed in two parts, with the first presenting a case study-based investigation of various Q-commerce grocery companies operating in Delhi. The second section of the article examines freight and E-commerce provisions in various statutory and non-statutory documents from different categories of cities. The study brings out the externalities associated with Q-commerce last-mile delivery at a local neighborhood, and inadequate provisions in planning documents related to E-commerce and highlights the planning implications.

ABSTRACT. This paper introduces service-based and infrastructure-based route diversity metrics for measuring the redundancy of public transport systems, considering the overlapping of efficient routes within multilayer networks. Service-based route diversity quantifies the number of efficient routes between an origin-destination (OD) pair, accounting for overlapping transit lines, while infrastructure-based route diversity considers overlapping road segments utilized by the transit lines. To capture the interplay between supply and demand, the study combines the supply-side factors, including the public transport network and service frequencies, with the demand-side factor, represented by passenger OD flow distribution. This integration results in a set of "relative" route diversity measurements, which identify areas with high travel demand but low route diversity, signalling reduced redundancy in the face of disruptions. The proposed metrics are applied to a case study of the multimodal public transport network in Jiading District, Shanghai, demonstrating their effectiveness in assessing network redundancy. The analysis provides valuable insights for public transport planners and operators to optimize transit lines and schedules.

ABSTRACT. One of the components of a new model, called INTRAMOD, for Indonesia’s domestic freight transport is the logistics model. The logistics model describes shipment size choice and the choice between five different transport chain alternatives involving four main modes: truck, train, vessel and plane. This paper presents the work to forecast the disaggregate transport chain and shipment size choices for Indonesia’s domestic shipments by applying a deterministic and a stochastic approach. Using a standard economic order quantity (EOQ) model with a consolidation assumption, a deterministic approach is used to determine the transport chain and shipment size, minimizing total logistics cost. As an alternative for this, a stochastic model aims to improve the logistics choice modelling by employing data on the manufacturer's revealed preferences (RP) and stated preferences (SP) regarding only the transport chain choice. The chosen specification for the stochastics approach is utilizing the multinomial logit model. Using the demand elasticities for all alternatives with respect to changes in its transport cost, a comparison will be made between the two approaches. In addition, it is concluded that the deterministic model is susceptible to sticky and flip flop behaviors. In contrast, this circumstance is absent from the stochastics approach.

ABSTRACT. Switches and crossings are prone to failure making them important drivers of unreliability in the operation of railway systems. This unreliability is directly linked to punctuality which continues to limit, among other factors, railways’ mode share. Therefore, using historical train operation and maintenance data, this paper assessed the impact of switch faults (switch failures and switch inspection warnings) on the delay of a train. The study investigated the increased chance of a train being delayed in the event of a switch fault and the average size of delay that can be attributed to a switch fault. We find that 1) in the event of a switch failure trains have a 1% increased chance of experiencing a dwell delay, a 0.7% increased chance of experiencing an arrival delay, and a 0.1% increased chance of experiencing a departure delay for non-stopping trains; 2) that the impact of switch inspection warnings on train delays is negligible; and 3) on average, a train is delayed by six extra minutes in the event of a switch failure. This study serves as a step towards quantifying primary delays and their origin in the railway system which is necessary for accurate simulation and prioritization of maintenance resources.

ABSTRACT. Building dry ports facilitate intermodal freight transport in import and export corridors, especially for landlocked countries. Selecting the optimal location of the dry ports is a crucial component of dry port planning. In this study, the criteria literature used to choose optimum dry port locations have been summarized and presented to logistics experts to identify final lists of criteria relevant to the case of Ethiopia. Following the survey, a simple multi-attribute ranking technique (SMART) was used to weight the criteria. Accordingly, out of the seven final criteria, closeness to road networks and railway were found to be the two most important criteria whereas the distance from the seaport was the least important criterion. We input these weighted criteria into GIS to identify the optimal locations for dry ports in the case study area, Ethiopia. Finally, the areas close to the road and railway infrastructures together with the areas with a higher score of the rest of the criteria were mapped as the most and moderately suitable areas. The results indicate that the location of existing dry ports aligns with the suitability map found in the study.

ABSTRACT. Trade hubs and wholesale markets are major freight handling/generating areas in cities involved in urban and regional goods distribution. Freight transport infrastructure is capital intensive which requires due diligence to get maximum benefits and efficiency with overall sustainable city development. Due to the scarce availability of land in urban areas, there is a need for optimum usage of freight handling areas in cities. This research paper is based on an empirical study carried out in the city of Jaipur in north India. The paper assesses the efficiency of five major freight handling areas in case a city using the Data Envelopment Analysis (DEA) method. Primary data for operational efficiency of freight handling areas supplemented by secondary data for the year 2019 is used for DEA analysis. DEA CRS-based efficiency model is used for assessing the efficiency analysis of freight handling areas. A sensitivity analysis of parameters has been carried out to assess the robustness of the results.

ABSTRACT. The basis of the efficient functioning of city logistics systems are effective information flows and ability of knowledge extraction from the fast growing data resources. Due to that it’s significantly important to support it by intelligent transportation systems and implement telematics-based solutions. However, many specific risks can happen during the implementation of IT-based tools in urban freight transport systems. Understanding risk management entails understanding the fundamental factors of project risk. The risk is often the same, regardless of the nature of the project. Nevertheless, the specificity of city logistics influence on the specificity of risk management during the implementation of IT tools. The paper is focused on the risk management in IT projects in generally, as well as the risk factors in the city logistics IT-based measures implementation. The principles of risk management in the project are presented. However, the Authors pay the special attention on the importance of the human factor in the management of ITS projects and in the risk management. Next, based on the reference model of risk management in terms of urban freight transport measures’ implementation, the Authors highlight the risk factors related to the implementation of ITS tools for UFT planning.

ABSTRACT. We define Social Vehicle Routing Problems (SVRPs), where preferences of drivers and vehicles, feasibility constraints between vehicles and requests, and network metrics, inform the management of the fleet. We propose new algorithms for SVRPs, first returning a feasible matching between drivers and customers and then an optimizing feasible plan for routing the vehicles through their matched locations. We give matching algorithms for achieving fairness for drivers (i.e. FEF1, FEQX, FEFX), efficiency for drivers (i.e. FSWmax), and fairness and efficiency for customers (i.e. FSWmin). Finally, we also give fixed-parameter tractable routing algorithms for fleet fairness (i.e. maxTRAVEL) and fleet efficiency (i.e. totTRAVEL).

ABSTRACT. The proliferation of light commercial vehicles (LCVs) in urban areas has revolutionized urban operations, playing a crucial role in facilitating diverse commercial activities and shaping the urban mobility landscape. However, the exponential growth of LCVs and the freight sector has raised environmental concerns due to heightened air pollution, carbon emissions, and traffic congestion. To address these pressing issues and explore sustainable alternatives, this research aims to investigate the impacts of LCVs on the environment and propose effective strategies for mitigating their negative effects, thereby promoting a greener and more sustainable urban transportation system. This paper discusses an overview of alternative fuels and an analysis of the viability of electric vehicles for local level distribution in Dehradun, India. The literature review provided an overview regarding the criteria used by previous studies for public charging infrastructure facility to specify the optimal locations of electric vehicle charging stations. The research findings demonstrate that while the initial investment cost of electric LCVs is significant, their total lifecycle cost proves to be substantially lower than that of gasoline, diesel, and CNG vehicles.

ABSTRACT. The weight information of trucks traveling on the road is of great significance for traffic safety and management especially for real-time road capacity prediction, freight operation, and emissions estimation. The current truck weighing system via loadometer or on-board unit is difficult to equipped and maintained with just sampling weight data instead of real-time weight information. In this study, we propose a truck weight estimation method in a deep learning framework using vehicle motion data only. A corresponding on-board unit is designed and equipped on traveling trucks in a natural driving environment to detect and transfer the data automatedly for model training and verification. A deep-learning framework with classification-regression algorithm is proposed for weight estimation. Specifically, the Gate Recurrent Unit (GRU) and Deep residual network (ResNet) are applied to classify and estimate the truck’s weight, respectively. The results of cross-vehicle estimation show that, for the per-minute pointwise estimation, the average error above Q3 is less than 2.70%, while for the trip-based estimation, the average value of the absolute relative error is 2.24%. The proposed method is approved to estimate the truck’s weight dynamically and accurately with just vehicle motion data, which would be useful for vehicle safety and intelligent traffic.