ABSTRACT. Managing aircraft landings in the Terminal Area (TMA) is a key challenge in Air Traffic Management (ATM) and has been gaining attention due to the consistent growth of air traffic congestion and delays. The Aircraft Landing Problem (ALP) deals with this issue by optimally scheduling the aircraft landings in the TMA so that the overall delay is minimized. Most modern models and solution methods addressing ALP allow aircraft re-positioning. However, majority of the airports still employ the First Come First Serve (FCFS) policy to manage landings. This study seeks to assess the optimality of the FCFS policy. Mixed Integer Programming (MIP) models are proposed to replicate FCFS, and the solutions are compared with the results from a state-of-the-art (SOA) model. Results suggest that FCFS results in 1.76 times more deviation from the target landing time than the SOA outcome on a single runway. While, in case of multiple runways, FCFS results are comparable with the SOA model outcomes. Findings also suggest that different holding times may result in different runway combinations. Implications of this study can help ATM decision-makers estimate the overall delay/deviation arising from FCFS and efficiently plan the available resource, workforce, and infrastructure augmentation decisions under FCFS policy.

ABSTRACT. Hub Location Problem (HLP) is an important research problem in air transportation, telecommunication and postal service system. Plenty of techniques have been proposed to deal with HLP, including exact methods and meta-heuristics. This study is the first to propose deep-learning based framework evaluated on Uncapacitated Single Allocation p-Hub Median Problem with Complete hub network (USApHMPC). We have designed a measure to extract the inputs of deep neural network (DNN) models from current solutions, and the pre-trained models can restrict the search space of general variable neighborhood search (GVNS). We conduct a series of computational experiments on five representative datasets for USApHMPC. According to the results, with the prediction of the pre-trained DNN models, the DNN guided GVNS (DNN_GVNS) can obtain the same gaps as GVNS in shorter execution time, without compromising solution quality. Our computational results also show that both the solution quality and speedups can be improved as the instance size increases. We believe that DNN_GVNS potentially enables scalability to very large instances and identifies universal patterns.

ABSTRACT. Airlines add extra time to their schedules to control excessive delays. This extra time, known as buffer, has largely increased over the last two decades. However, our study shows a very different behavior across carriers. Studying all flights operated between 2007 and 2017 in the US domestic market we observe that Southwest Airlines presents a very different behavior from all the other carriers and that the presence (entry/exit) of Southwest on a market affects the buffer choices by the other carriers present on the market.

ABSTRACT. In the short term, innovative electric Vertical Take-Off and Landing (eVTOL) aircrafts will enable the spread of air taxi services, disrupting the urban mobility landscape by allowing individuals to obtain significant travel time savings. Travelers’ willingness to adopt the so-called Urban Air Mobility (UAM) services should not be taken for granted, because they may elicit low perceived usefulness, as well as high safety concerns, but also failing in offering competitive fares with respect to other mobility services, such as traditional taxis. This paper aims at investigating the determinants that will mostly affect eVTOL aircrafts adoption and the travelers’ willingness-to-pay for UAM solutions. Starting from a mixed Revealed Preference and Stated Preference survey, data from 4’174 complete Computer-Assisted Personal Interviews were collected at both main transport nodes and points of interest within the metropolitan area of Milan, Italy. These were used for estimating advanced discrete mode choice models, i.e. Panel Mixed Multinomial Logit models, and assessing UAM value of time for different demand segments. Results showed that a high propensity of individuals to consider UAM services as a valid transport alternative exists, and willingness-to-pay for travel time savings using UAM services are far higher than those by cars and chauffer taxis

ABSTRACT. Severe low-level wind shear (S-LLWS; 30 knots or more) near airport runways jeopardizes civil aviation safety. Understanding S-LLWS causes improves aviation safety. It's rare but worrisome for departing and approaching aircraft. Therefore, in order to predict and classify the LLWS severity, this study proposed machine learning models, including Extreme Gradient Boosting, Random Forest, and Light Gradient Boosting Machine, as well as ensemble imbalance learning models, including EasyEnsemble, Balance Cascade, and RUSBoost, and their interpretation by the Shapley Additive Explanations (SHAP) system. This study used Hong Kong International Airport Doppler LiDAR data (HKIA) from 2017 to 2021. This study examined runway orientation, low-level wind shear location, and seasons. Among all the models, the EasyEnsemble performed better and had the highest G-mean and Matthews' correlation coefficient. After that, a SHAP analysis determined factor importance. It was revealed that HKIA runway 25CD is susceptible to S-LLWS. Most S-LLWS occurred in spring and winter. Most of the S-LLWS events were observed at 1 MD from the end of the runway. This research will benefit aviation safety researchers and policymakers.

ABSTRACT. While route planning as a core issue of airline network management has received a lot of attention in academia, the same cannot be said for service closures. This paper analyzes the survival of new intra-European scheduled air services. We estimate a total of seven Cox proportional hazard (PH) models with time-dependent covariates to assess the impact of airline, airport, route and service characteristics on survival probabilities, which include stratified models by business model and by individual airline to estimate separate baseline hazards. The empirical analysis ends in 2019 before the COVID crisis. A key finding is that mainline carriers show a significantly increased likelihood of service discontinuation than low-cost carriers challenging the common notion of low-cost carriers’ footloose strategies.

ABSTRACT. The maritime shipping industry will increasingly switch to low carbon fuels and adopt energy saving technologies (ESTs) to achieve the industry target of decarbonization. Among ESTs, deck equipment, including those based on wind propulsion technologies (WPTs), represents the largest potential fuel savings and a source of increasing innovation initiatives by industry actors. Previous contributions to WPT innovation have addressed barriers and drivers for increased adoption in the industry but failed to consider the specific aspects of the fleet retrofitting market. Through an agent-based simulation model, this work studies the effects of different policy and market scenarios (subsidies, fuel prices, and networking) on the adoption of WPT retrofitting solutions. The proposed model incorporates two decision steps for each vessel to adopt the technology (acquiring awareness of the technology, and a utility decision process to determine the WPT option). The study also expands on previous knowledge by modeling three WPT options and by integrating real world data of technology costs and their fuel savings as well as vessel features. Insights from simulations allow to identify the most convenient policies as well as the potential of alternative models to reduce introduction barriers (e.g., product-service business models).

ABSTRACT. Waterways and navigation operate within the contest of complex systems, but there is a need to examine navigation as related to monthly events. This paper developed a framework to collect and organized these events to assist port managers, operators, and other interested parties in understanding the basic events that occur within a certain waterway sector. By organizing the categories around the three E’s of Sustainability, Economics, Environment, and Equity, the Sustainability Operational Monthly (SOM) matrix was developed as a structured way to highlight these events. This provides a framework for considering operational and monthly events which may be linked directly so to sustainability goals. A mixed approach of published information and local knowledge was used to create a matrix of normal, predictable events which occur in Mobile County, Alabama. The paper concluded that such a matrix could be developed using published sources, but the model does need to be verified with local knowledge. In some ways, this basic research looks at developing a framework to organizing an understanding of the rhythm of a port area that can also be used as an input to other future studies related to navigation sector risk and capacity management.

ABSTRACT. Alternative fuels are essential in order to reach the emission reduction targets set by the IMO. Hydrogen carriers are classified as zero-emission, while having a higher energy density (including packing factor) than pure hydrogen. They are often considered as safe alternative fuels. The exact definition of what safety entails is often lacking, both for hydrogen carriers as well as for ship safety. The aim of this study is to review the safety of hydrogen carriers from two perspectives, investigating potential connections between the chemical and maritime approach to safety. This enables a reasoned consideration between safety aspects and other design drivers in ship design and operation. The hydrogen carriers ammoniaborane, NaBH4, KBH4, LOHC (NEC and DBT) are taken into consideration, together with a couple reference fuels (ammonia, methanol and MDO). After the evaluation of chemical properties related to safety and a scope of the current IMO safety framework, it can be concluded that safety remains a vague and non-explicit concept from both perspectives. Therefore, further research is required to prove safe application of hydrogen carriers onboard ships.

ABSTRACT. International shipping contributes approximately 2% of global CO2 emissions. The IMO has established targets to reduce CO2 intensity by 40% in 2030 and overall GHG emissions by at least 50% by 2050. Achieving these targets requires a comprehensive understanding of the relationship between shipping demand, supply, and emissions and the interconnection with the global economy. This paper evaluates current studies on the future of international maritime shipping, focusing on demand, supply, and emissions predictions. Projections indicate a significant increase in seaborne trade demand by 2035 and 2050, ranging from 22% to 106% and 40% to 230%, respectively, compared to 2020. Fuels, such as biofuels, hydrogen, and ammonia, are expected to have varying adoption rates. CO2 emissions are estimated to range from 0.8 to 2.6 GtCO2/year by 2050, with some projections suggesting the possibility of achieving net-zero emissions. Among different methods, Integrated assessment models (IAMs) are considered suitable for evaluating the sector's future due to their ability to capture complex cross-sectoral interactions, although they have limitations. Future research should focus on refining techno-economic assessments to incorporate the latest developments in shipping technology, fuel options, and policy frameworks, encompassing diverse vessel types and fuels.

ABSTRACT. The shipping industry plays a vital role in the world economy, as it is responsible for 85% of global trade. However, one of the most significant issues related to the shipping industry is the environmental impact caused by the vessel’s operations. In 2018, the IMO set a new target for emissions reduction, aiming to reduce emissions by 50% by 2050, compared to the 2008 level, while new regulations and operational measures have emerged, and they are focused on the operational decisions that will help the industry to achieve carbon neutrality. In addition, trade conflicts and disruptions caused by COVID-19 and geopolitical events have posed challenges for the industry, especially in operational decisions, while due to uncertainty and the stricter environmental regulations, there is a small order book value. This paper presents a systematic literature review of ship investment from 1997-2022, analyzing 73 peer-reviewed articles. It focuses on investment timing, viability, and decision-making in the new-building market, considering environmental regulations and decarbonization efforts. The review identifies research directions, contributions, progress, and knowledge gaps, offering a potential research agenda for the future.

ABSTRACT. Cold chains ensure the safety and quality of perishable goods. Incorrect storage temperatures can cause textural degradation, discoloration, bruising, and microbiological growth. Cold chain logistics involves transporting temperature-controlled items like food, beverages, and biopharmaceuticals. In this paper we wish to outline challenges and opportunities via a literature review of ‘cold chain’ research agenda with a specific focus on transportation and logistics. Previous attempts have been made in addressing the technological aspects of the cold chains, such as efficient energy system and sustainable refrigeration technologies in response to, for instance, delivering a low temperature-controlled products. Our proposed approach here is to set up the ground for logistics and transportation studies and aid the development of cold chain modelling and simulation. We introduce a modelling framework, MILES (Multimodal Integrated Logistics Environment System), originated as part of the UK research initiatives in addressing sustainable road freight, to explore the sustainable cold chain. A conceptual design of an agent-based model using Scottish salmon logistics network was also introduced.

ABSTRACT. Decarbonization of urban goods movements is a pressing issue. About one third of the freight-related CO2 emissions in the Netherlands relates to these movements, consisting of both vans and trucks. Although electrification is a feasible solution, delivery models that not only focus on reducing the carbon footprint, but also the spatial footprint are important. A one-to-one replacement of vehicles does not reduce urban goods movements’ spatial footprint in densifying cities nor the perceived nuisance of the delivery vans. In this contribution, we examine the impact of alternative delivery models in the parcel- and home delivery segment in four future scenarios on CO2-emissions, vehicle kilometres and number and type of vehicles used (2030). Analyses are based on data from three companies in a large metropolitan region in the Netherlands. The results show the impact of electrification of vehicles fleets, transhipment in consolidation points and a network of pickup points. This study illustrates that developing alternative last mile networks can result in a decrease in vehicle (van) movements, and with that a serious decrease in emissions.The implications of the results on the carbon footprint, urban space usage and costs for companies are discussed.

ABSTRACT. For retailers and consumers, the calculation of environmental impacts related to their supply activity or consumption is now a challenge to either optimize organization or change shopping habits. However, retail activities are now very diverse based on the nature of products sold, on their commercial surface and their associated distribution logistics. Indeed, in addition to e-commerce retail, “brick-and-mortar” shops rely on various last-mile distribution systems. In this paper, we propose to assess the environmental impacts of various distribution systems available to households in a given urban area. In order to do this, we propose a coupling of classic transport modeling methods with a life-cycle assessment (LCA) approach. Six distribution systems are modeled and compared. Five are “traditional” retail sectors: hypermarkets, supermarkets, small generalist retail, small food retail and small non-food retail. For all five, we model warehouse activity, shop delivery, shop in use, consumer mobility and delivery packaging. For e-commerce home deliveries, only warehouse, home delivery and packaging are modeled.

ABSTRACT. The objective of this work is to propose a method to analyse the environmental impact of carbon dioxide emissions resulting from use resulting from the use of PP and APS in sustainable urban freight distribution. To this, we conducted a comprehensive bibliographical review using the Bibliometrix tool. The use of this tool led to the obtaining of a promoted framework of information, enabling the modelling of three different scenarios. The simulation of these scenarios aimed to evaluate the environmental implications of the "Pick-up Points" in the urban logistic operations of an e-commerce retailer of "Building Construction Material". The results depicted a reduction of up to 86% in vehicular emissions compared to the current process. However, depending on the process configuration, a loss of service level might affect the customer's decision when choosing delivery through "Pick-up Points".

ABSTRACT. Limited data is available on the size of urban goods movement and its impact on numerous aspects with respect to livability such as emissions and spatial impact. The latter becomes more important in densifying cities. This makes it challenging to implement effective measures that aim to reduce the negative impact of urban good movement and to monitor their impact. Furthermore, urban goods movement is diverse and because of this a tailored approach is required to take effective measures. Minimizing the negative impact of a heavy truck in construction logistics requires a different approach than a parcel delivery van. Partly due to a lack of accurate data, this diversity is often not considered when taking measures. This study describes an approach how to use available data on urban traffic, and how to enrich these with other sources, which is used to gain insight into the decomposition (number of trips and kilometers per segment and vehicle type). The usefulness of having this insight is shown for different applications by two case studies: one to estimate the effect of a zero-emission zone in the city of Utrecht and another to estimate the logistics requirements in a car-free area development.

ABSTRACT. As the need for freight transportation grows, port authorities might contemplate expanding their infrastructure by adding a new terminal. Nonetheless, it is crucial to assess the potential effects of construction truck traffic on current access gates during expansion. This research introduces a simulation-based method to evaluate access gates fluidity throughout a significant port expansion. The methodology incorporates spatial and temporal aspects to establish simulation parameters and a four-level scenario analysis to aid in assessing access gates fluidity. The findings suggest that under normal traffic conditions, access gates capacity can accommodate the construction needs for the new terminal. However, the unloading time for construction trucks at the new terminal needs to be optimized to prevent city-side congestion. Additionally, the study reveals that reducing the number of entries at the main gate would hinder traffic flow, which calls for the implementation of an appointment system during peak hours and seasons to effectively manage traffic fluidity.

ABSTRACT. Different transport models are available in the literature to estimate and simulate the logistical framework of container freight transport. However, many of these models lack the complex interaction within the IWT logistics system, which includes: the relationship between the cost and time calculations, selection of the transport mode based on specific parameters, assigning transport flows to a network based on selected transport modes, and assessing the impact of different IWT innovation initiatives.

A discrete event simulation (DES) model is developed to address this. This model simulates the current container logistics system on the Rhine-Alpine corridor and gives detailed analyses of the impact of different innovation initiatives on IWT container logistics.

Using the DES approach, the current paper presents the methodological framework and the overall architecture of the simulation model. It also discusses the verification and validation process of the model. Based on the verification and validation, the paper finally develops and presents the reference case KPI outputs by which the impact of the IWT innovation initiatives will be measured.

ABSTRACT. The study assessed the impact of new truck routes on urban travel in Metro Manila. The study determined the appropriate operating scenario for truck traffic with or without the truck ban incorporating additional or new truck routes along important corridors of Metro Manila. Shortest path analysis was initially used to assess possible new corridors that trucks can use and finally used a multi-class traffic assignment routine in EMME transport planning software to model the traffic in the network. Vehicle demand of trucks during the off-peak period when there is no truck ban and other vehicles such as private cars and public transport vehicles were modelled. The study determined and compared the link characteristics in terms of travel time, volume, average speed, vehicle-hours travel, and vehicle-delay travel which could be used to quantify travel time savings, vehicle operating costs, traffic accidents, and GHG emissions. Overall, opening new truck routes would improve truck travel in Metro Manila but would decrease the travel time and speed of other vehicles on the network especially those on the routes affected. Recommendations were also provided on how to mitigate the impact of new truck routes on urban travel in Metro Manila.

ABSTRACT. This case study addresses the problem of empty container repositioning (ECR) in the Colombian context at a regional scale. The research was motivated by the massive empty container congestion in 2022 in specific nodes of the logistics network. A Mixed-methods approach is proposed in this research, considering a qualitative and quantitative method that aims to clarify the causes of inefficiency in the system and to formulate improvement strategies. Street-turn has proven to be the strategy with a better fit for increasing efficiency in the ECR system. To measure the potential gains of street turn, a matching algorithm has been developed to pair empty containers with export loads to achieve more efficient utilization of vehicles in the network. The optimization model results confirm significant cost savings and a reduction of empty trips for Colombia's selected regions. However, the effect of the algorithm is limited due to the high container trade imbalances. Further, the research identifies that the actors involved in the ECR system lack incentives to collaborate, making this a barrier to implementing street-turn.

ABSTRACT. The fundamental speed-density (V-K) relationship is used for traffic management. In the past, various single-regime and multi-regime models were developed to model the speed-density relation. These models are deterministic and thus establish an equilibrium speed-density relation under a fundamental assumption that only one speed corresponds to a given density value. However, the traffic flow on urban roads is stochastic, so the premise of deterministic speed-density relations fails to hold. Therefore, it is imperative to develop a stochastic traffic flow model. This study proposes a methodology for developing a stochastic extension for various existing deterministic single-regime macroscopic traffic-flow models. In the proposed extension, the distribution of travel times for a given density is incorporated using a percentile-based indicator, i.e., travel time uncertainty (TTU), using two parameters, namely – α and β. These parameters are argued to absorb the effect of TTU to generate randomly varying speeds. The proposed extension is demonstrated for its applicability using empirical data collected at a corridor level. The outcomes of the investigation using an empirical dataset concluded that the proposed extension captures the inherent heterogeneity in speed-density relation better than existing deterministic models.

ABSTRACT. Road transportation is an essential mode of transportation because of its accessibility and mobility characteristics. There were 17.8 trillion road passengers per kilometer traveling across India in 2017. Road construction and maintenance activities are widespread and create various types of work zones. A work zone is a critical road section from the capacity and safety points of view. The present study evaluates the effect of the work zone on road geometric design and traffic capacity using VISSIM micro-simulation software. First, the simulation model for the road with and without work zone is calibrated and validated. Then, various simulation runs are performed by varying the length, number of lanes, and work-zone taper. The speed, density, and flow are imported from VISSIM software for each scenario, and the North-Western model is applied to calculate the capacity. The results revealed that capacity decreases with the increase in the number of lane drops and increases with the increase in the length of work-zone and tapering lengths. The study’s outcome is helpful for traffic engineers to determine the optimum work-zone length, rate of a taper, and number of lanes to achieve sufficient capacity to handle the traffic demand.

ABSTRACT. This study develops new methods for evaluating detector health using event-based outputs and existing traffic flow theory. In this work, event-based detector data outputs were used to develop empirical vehicle volume-density curves, per Greenshields Fundamental Model. Using integration, these empirical lines were compared with a conceptual volume-density curve for each detector, generated with average headway and posted speed limit data. Detector performance and site information were also used to model a predicted volume-density relationship for each detector based on empirical observation, which was then compared with the Conceptual line in the same manner as the empirical lines. The outcomes of each comparison were then used to create a database for assessing detector health within the structure of an algorithm. The algorithm is presented and discussed, followed by directions for future research, applications for practice, lessons learned, and limitations of this work.

ABSTRACT. Road traffic incidents are a matter of global concern. The accident data plays a significant role in prevention and accident management and getting deeper insights for designing better policies and guidelines. Effective management of the collected accident information should ensure the effective utilization of the information so that multiple outputs can be created and used in various types of safety analysis. We are developing SafeOn – a domain ontology for road user’s safety ontology. SafeOn is developed for India and uses bottom-up approach in Protégé and OWL. Our proposed Safety Ontology (SafeOn) organizes accident for detailed analysis of various aspects of road safety. It offers features of interoperability to integrate with crash data of other departments like healthcare, road design for better insights, policy decision and accident prevention plans. We instantiated SafeOn with accident case of Cyrus Mistry. We integrated the accident information with SafeOn generated the knowledge graph. This graph is capable for speedy analysis of road accidents, can efficiently answer all the questions related to that accident. SafeOn is useful for road safety departments for designing better policy, resolve problems of missing information in hit-and-run crashes and ensure saving life of road users.

ABSTRACT. Despite many research efforts on ride-hailing services and taxis, few studies have compared the safety performance of the two alternatives. One big challenge is the lack of reliable mode-specific exposure data to model ride-hailing and taxi crashes. In addition, crash frequencies by injury severities tend to be spatially and inherently correlated. To address these issues, this study proposes a novel multivariate conditional autoregressive model considering measurement errors in mode-specific exposures. The census tracts in the city of Chicago are set as the spatial analysis unit. The mode-specific exposures (vehicle-mile-traveled) in each census tract are estimated by trip assignments using ride-hailing and taxi trip data in 2019. The modeling results indicate that ride-hailing crashes and taxi crashes are positively associated with transportation factors (e.g., vehicle-mile-traveled, mode-specific vehicle-mile-traveled, and traffic signal numbers), land use factors (i.e., number of educational and alcohol-related sites), and demographical factors (e.g., median household income, transit ratio, and walk ratio). Despite no significant difference between the two alternatives for severe injury crashes, taxis are found to be a safer mode than ride-hailing services in terms of minor injury crashes according to the result of t-tests. This study provides insights into the safety management of different mobility alternatives.

ABSTRACT. Worldwide, Road Traffic Accidents are increasing day by day. Every year nearly 1.35 MN People are killed in road traffic accidents globally (GSR 2019 -WHO). Vulnerable road users are pedestrians, Bicyclists, and 2-wheeler Users. Common causes of road accidents in India are speeding, bad condition of roads, drunk driving, and lack of safe infrastructure. Etc. Developing “Road Safety Index (RSI)” aims to evaluate the Road Safety Assessment of a Road that does not depend upon Accident Statistics and is used to identify and analyze Hazardous Road Ways. Road Safety Audit only checks the Road geometry features like lane width, shoulder width, curve radius, and other dimensions of the road but RSI which was developed in this study will evaluate all the attributes of the road in terms of Road Geometry, Built Environment Conditions, Road Infrastructure, Pedestrian Infrastructure, and Traffic Density & Speed. RSI is a group of safety variables or attributes that defines a road's safety level. PCA was used to formulate the RSI formula. RSI will be a more effective safety check method for urban roads than Road Safety Audits can be used as an accident prevention technique (Pre-Crash Safety technique) for urban roads

ABSTRACT. Extreme value theory (EVT) has seen considerable research interest in road safety area in recent years. This study applies two EVT approaches, namely block maxima (BM) approach and peak over threshold (POT) approach, in two cases. One is a common case that uses the POT approach for crash estimation and the other is a practical before-after case that applies the BM approach to evaluate the left-turn bay extension treatment effects. The data were collected from four signalized intersections in a Canadian city, and time to collision (TTC) and modified time to collision (MTTC) were employed as traffic conflict indicators. The results of crash estimation case show that the estimated crashes are within the 95% confidence intervals of observed crashes, indicating the POT approach can generate accurate crash estimates. In addition, applying the EVT approach in the before-after analysis can help to quantitatively evaluate the treatment effects based on the OR method, because not only the number of crashes but also the number of the most severe conflicts can be obtained from the extreme value distribution. The before-after analysis results show a significant reduction in crashes and the most severe traffic conflicts after the left-turn bay extension.

ABSTRACT. A large number of pedestrian rail conflicts leading to fatalities occur on Mumbai suburban railway network in India. The main cause for these fatal incidents is due to collision of persons with train while crossing railway track. Over 60% of reported cases are track pedestrian incidents and hence need for study. The commuters tend to cross the railway tracks at stations and at mid-section and also walk along the railway tracks. Based on Theory of Planned Behaviour, a survey was conducted through a set of questionnaires including demographics and travel characteristics to measure and analyse the risk-taking behavioural attributes. Sample data of 502 respondents was collected from 19 railway stations on Mumbai Suburban Network. Past studies in this area also reflect pedestrians violate rules rather than making errors. This paper examines the influence of demographic, socio-economic and travel characteristics of railway track pedestrians, and derive significant factors using Multinomial Logistic Regression. It was found that Commuters of younger age, students, unmarried, low-income group and males exhibit risky behaviour by allocating priority to convenience, saving time, ease and other behavioural attributes disregarding safety. This analysis can assist in directing the efforts towards target group for safer mobility of suburban rail commuters.

ABSTRACT. In this paper, we unpack the effects of the determinants of pedestrian crashes using a multivariate analysis approach. We consider four sets of exogenous factors that characterize residential neighborhoods as well as potentially affect pedestrian crashes and the racial composition of such crashes: (1) crash risk exposure (CE) attributes, (2) cultural variables, (3) built environment (BE) features, and (4) sociodemographic (SD) factors. Our investigation uses pedestrian crash and related data from the City of Houston, Texas, which we analyze at the macro-spatial Census Block Group (CBG) level. Our results indicate that social resistance considerations (that is, minorities resisting norms as they are perceived as being set by the majority group), pedestrian facilities, the proximity to transit stops, and road design considerations (in particular in and around areas with high land-use diversity) are the three strongest determinants of pedestrian crashes, particularly in majority Black (MB) CBGs. More generally, BE attributes stand out, by far, as the single most important category of variables influencing pedestrian crashes, while also representing the most differentiating set of variables between MB and majority non-Black (NMB) CBGs.

ABSTRACT. Crash and crash severity is a growing problem along India’s roadways. In 2019, pedestrian share in road deaths in India stood at 18%. The availability of good quality data for statistically significant analysis of pedestrian crashes is scarce, especially for developing and under-developed countries. As such, simulation techniques are being increasingly employed by researchers. This study develops a three-step methodology to proactively predict pedestrian conflicts at urban crossings under mixed-traffic conditions: (a) Development and calibration of on-street conditions in VISSIM and identifying vehicle-pedestrian conflicts using time to collision (TTC) and post encroachment time (PET), (b) Calibrating the TTC and PET thresholds using pedestrian-vehicle conflict analysis (PVCA), and (c) Predicting effects mitigation measure on pedestrian conflict frequency and network-flow. The study area, an urban arterial in Kolkata, India, which has reported highest number of pedestrian crashes in previous years, was successfully simulated using a VISSIM-SSAM-based model, which could predict frequency of pedestrian conflicts with more than 90 percent accuracy. A scenario containing pedestrian signals at the five intersections along the road section was simulated. The model predicted a decrease in the frequency of vehicle-pedestrian conflicts, both at major and minor intersections, from anywhere between 26-51%.

ABSTRACT. Rear-end collisions at the end of traffic jams on expressways tend to be serious accidents due to large relative speed difference. In order to reduce this risk of accidents, it is important accurately to communicate the location of the end of a traffic jam to following vehicles. This study used deceleration acceleration from ETC2.0 probe data as an indicator of emergency braking. Then, the frequency of emergency braking at the end of a traffic jam was compared with and without traffic jam information provided by variable message signs just installed upstream of the congested section. The results showed that when traffic congestion information is available, the frequency of emergency braking is reduced because drivers can check traffic congestion information in advance and pay attention to traffic congestion ahead, which is effective in reducing rear-end collisions.

ABSTRACT. This study examined road users' perception of road traffic safety in Croatia. The data were collected by a survey to identify road users’ opinions on road traffic safety in general and specifically on the so-called four road traffic killers: alcohol, speed, seat belt, and mobile phone. In addition, the users’ opinions on education and prevention measures were investigated. The results show that traffic participants believe that road traffic in the Republic of Croatia is unsafe (68.3%) and have given their suggestions for increasing road traffic safety. Based on this, we can assume that in the future, road safety could be improved with more frequent educational campaigns and infrastructure improvements. To our knowledge, this is the first reported survey study of traffic participants' perception of road traffic safety in Croatia.

ABSTRACT. This paper focuses on the visual distraction effect of mobile phones while driving. Visual distraction is here analyzed concerning attributes related to the driver (gender, age and driving experience) and the road (weather, lighting, and traffic conditions). The influence of the different attributes on visual distraction is investigated through a simulated driving experiment involving 40 volunteer drivers who were asked to perform four mobile phone tasks while driving: check notifications, read text messages, talk on the phone, and write a text message. The experimental results are analyzed using Analysis of Variance and Covariance methods showing that: i) when drivers perceive the worsening of environmental conditions and the related risks, they reasonably focus more on safe driving than on phone activities; ii) older drivers seem to divert their visual attention from the road more frequently when performing mobile phone tasks. Compared to older drivers, younger drivers look at their phones less when reading a message and drive shorter distances without looking at the road; iii) using the mobile phone to send and read text messages while driving is confirmed to be the most visually engaging and the most demanding activity in terms of concentration required.

ABSTRACT. Speed limits that change as per real time traffic, road, and weather conditions are termed as dynamic speed limits (DSL). Road users are informed of speed limit changes in DSL schemes by electronic signs or Variable Message Signs (VMS) placed above the lanes or side-mounted along highways. In India, most of the highways have fixed speed limits which are set for average conditions of roadways. However, due to proximity of several roadside schools, market areas, bus stops and intersections, the speed limits are kept lower at those locations to ensure safety. This causes higher travel time to the road users. DSL has the potential in reducing travel time of vehicles and variability of speed thus helps in enhancing road safety. The present work investigates the applicability of DSL for a typical Indian highway with varied roadside developments and human activities by estimating the travel times with static and dynamic speed limit conditions. The results indicate that there is a significant amount of saving in travel time at various locations due to the application of VMS. A cost-benefit analysis is also carried out for a period of 10 years and recommendations are made for the locations suitable for DSL.

ABSTRACT. This study analyzed the impact of driving environments (real-world and simulated world) and driving conditions (no time pressure and time pressure) on speed compliance and speed adaptation. Professional car drivers were recruited and the data was collected in real-world and simulated world under no time pressure and time pressure driving conditions. The comparison results using Wilcoxon-signed rank test showed that speed compliance and speed adaptation were not consistently significant and were not in the same direction highlighting the influence of various factors like road features and driver characteristics. The generalized linear mixed model results showed that speed compliance was relatively better in simulated world (by 1.11 m/s) than real-world. Further, speed adaptation under time pressure was about 1.63 m/s lower during real-world as compared to simulated world. The findings from this study can provide new insights on road safety strategies and policy implications for limiting speeding-related crash risks.

ABSTRACT. The availability of carsharing in cities around the world has allowed more households to take advantage of the service as an alternative or a complement to private car ownership. While most research has looked at the effect of carsharing on car ownership decisions using carsharing users’ surveys, very few have modelled the choice of car ownership and carsharing jointly using independent surveys. This paper investigates the complex relationship between this joint decision, the built environment, and travel-related attitudes. Using data from two surveys in Montreal, latent-cluster analysis is used to identify a typology of residential neighbourhoods and a segmentation of attitude profiles. Cross-analyzing the two segmentations suggests that those with more positive attitudes towards the car are more likely to own cars and less likely to join carsharing across all neighbourhood types compared to less car-oriented profiles. However, people from all attitude profiles own fewer cars in more central neighbourhoods than in more suburban locations. Finally, a MNL model where sociodemographics and residential parking are controlled for confirms that both the built environment and attitudes independently influence the joint decision. Results also suggest that attitudes are associated with residential location choice, hinting at the presence of residential self-selection.

ABSTRACT. Many studies discuss Residential Self-Selection (RSS) as a confounder of built environment influence on travel behaviour. RSS implies that people choose residential areas that support pre-existing transport routines. Though most studies use travel-related attitudes to include RSS in behaviour change models, Ettema and Nieuwenhuis (2017) claim that travel considerations for residential location choice (TCRC) are more precise to this end. While attitude refers to a mental state towards a travel mode, e.g. preferences for cycling, TCRC describes an actual desire to live in an area that facilitates cycling. Drawing on the relocation decisions of recent movers (N = 339) to a car-reduced neighbourhood in Darmstadt, Germany, our first goal is to revise Ettemas and Nieuwenhuis’ (2017) finding in this particular environment. Our models yield hardly any difference between attitudes and TCRC. Instead, there are very little independent effects of TCRC on behaviour change, once attitudes are taken into account. Our second goal is to identify the importance of TCRC in choosing a car-reduced neighbourhood relatively to other aspects. We find that travel is less relevant than e.g. housing size and price. However, a deeper analysis reveals that particularly car-independent residents put more emphasis on the car-reducing design in neighbourhood choice.

ABSTRACT. In this paper, we examine workplace location (WPL) preferences of workers in an unpredictable future by investigating how workers prefer to allocate their monthly working days among the three WPL alternatives of working from home, from the work office, and from a variable third WPL. Our analysis employs the multiple discrete-continuous extreme value (MDCEV) model, using a 2022 stated preference survey of future work preferences of Texan employees. The results indicate that single young women with young children, those with long commutes and “intolerable” traffic congestion to the work office, self-employed workers, and those in non-essential service occupations have the highest preference for working from home. In contrast, older men, individuals from low-income households, those residing in rural areas, and workers in essential service occupations have the highest preference for the work office. And, for the third WPL, young non-single women with young children, individuals from low-income households, part-time employees, and those in professional, managerial or finance occupations have the highest predisposition. These results provide insights to urban planners, homebuilders, employers, travel demand modelers, and a host of other businesses to achieve specific desired end states, while underscoring the need to collect detailed work pattern information in activity-travel surveys.

ABSTRACT. The increasing diversity of vehicle type holdings and growing demand for EVs have policy implications for travel demand and air pollution. Consequently, it is important to accurately estimate the preference for vehicle holdings of households and the vehicle miles traveled by vehicle body- and fuel-type to project future VMT changes and mobile source emission levels. Leveraging the 2019 California Vehicle Survey data, this study applies a utility-based model for multiple discreteness that combines multiple vehicle types with usage in an integrated model, specifically the MDCEV model. The model results suggest the important effects of household demographics, residence location, and built environment factors on vehicle body type and powertrain choice and usage. We find that a 10% (25%) increase in population density reduces the preference for ICEV pickup trucks by 0.34% (8.4%) and VMT by 0.4% (8.6%). If the walkability index of a neighborhood increases by 25%, it reduces the preference for ICEV pickup trucks by 15% and the associated VMT by 16%. These predictions associated with changes in built environment factors can inform the design of land-use and transportation policies to influence household vehicle holdings and usage that can in turn impact travel demand and air quality issues in California.

ABSTRACT. The COVID-19 pandemic has caused unprecedented disruptions to travel patterns, resulting in a significant decline in transit ridership in Toronto. This exploratory study employs statistical and spatial analysis to investigate ridership changes during different time periods corresponding to changes in government-imposed mobility restrictions. Our results reveal that ridership increased following changes in mobility restrictions, with mixed ridership trends observed during intermittent lockdown periods. The spatial analysis highlights the relative homogeneity of ridership changes across census tracts with bus-only service, while census tracts with subway stops exhibited greater heterogeneity. The findings suggest that bus service users were more resilient to external factors compared to subway service users. These results provide valuable insights into the effects of government-imposed restrictions on transit ridership, highlighting the usefulness of these analyses as a powerful tool for transit agencies to promote public transit usage and plan for future scenarios.

ABSTRACT. This paper develops an integrated urban modelling framework (IUMF) to predict how work from home (WFH) due to COVID-19 may affect travel behavior. First, it conducts a questionnaire survey among working professionals in Halifax, Canada, to collect data on their socio-demographic characteristics, mode choice, vehicle ownership, and intention to WFH post-pandemic. Bayesian Belief network models are developed using the collected 338 responses to calculate the cumulative probability tables (CPTs) of variables associated with the intention to WFH. Next, the ascertained CPTs are used as input to extend an integrated urban modelling framework (IUMF) that is further utilized to simulate individuals’ travel behavior and work from home choices up to 2025. Results indicate that telecommuting cohorts’ auto mode share will decrease substantially in the next two years (2022-2023), whereas walking and biking trips will increase. Trips made alone will decrease up to 2023 and then increase in the following year. The average travel distance of telecommuters is found to be higher than non-telecommuting people. The outcomes of this study will offer policy makers a better understanding of long-term impacts of WFH on transport and land-use systems and help to develop strategies for upcoming challenges.

ABSTRACT. After over 20 years of psychological studies on travel behavior, it might seem the cognitive processes behind travel choices are now well known. However, mobility dynamics are complex and uncertain, meaning we often cannot trigger sustainable travel behavior. Hybrid choice models (HCMs) incorporating latent variables are a powerful tool to analyze travel behavior. Nevertheless, there still needs to be research on the treatment of latent variables, whose indicators are measured at one point in time, making it impossible to analyze within-person characteristics based on changes in these variables. Deriving policy implications with HCMs is not viable, as psycho-attitudinal variables are intrinsic characteristics that are insensitive to changes in the alternatives. Only a shock effect could trigger shifts in people’s psycho-attitudinal characteristics. The objective of this paper is to investigate two aspects: i) to study if and how norms, intentions and perceived behavioral control, change after a strong shock such as the COVID-19 pandemic, and ii) to analyze the differences in the HCMs results estimated by using data collected before and after the shock. The study involves a panel dataset gathered during a Voluntary Travel Behavior Change Program which involved three phases, two of which before and after the COVID-19 lockdown.

ABSTRACT. This paper presents the findings of pandemic scenario simulation within an activity-based travel demand forecasting model – shorter-term decisions simulator (SDS), which is currently implemented in Halifax, Canada. Along with business-as-usual scenario, the study develops four pandemic scenarios, namely lockdown, reopening phase-1, reopening phase-2, and reopening phase-3 focusing on COVID-19 outbreak. Utilizing the scenarios, SDS predicts individuals’ activity-travel decisions during the COVID-19 pandemic. For example, the microsimulation results suggest a 47% reduction in out-of-home activity participation during lockdown, which starts to increase with the reopening phases. It is predicted that 81% people participate in only two out-of-home activities a day during lockdown. Spatial distribution of activities illustrates lower work and school activity participation in downtown areas during lockdown that gradually decrease until reopening phase-2, however, increase in reopening phase-3. Moreover, results suggest that auto mode choice during lockdown scenario reduces by 46% compared to the baseline case. It is predicted to increase by 13% in reopening phase-3 from baseline. Proportion of non-shared travel for different activity-based tours is also predicted to increase from lockdown to reopening scenarios. The findings of this paper will help policymakers to develop essential policy interventions to be prepared for any further epidemic situation in future.

ABSTRACT. In response to the rapid increase in global greenhouse gas (GHG) emissions, 196 countries have made a legal commitment to implement a strategy to decarbonize their economies, under the Paris Agreement, particularly with respect to the transportation sector. As part of their long-term climate actions, these countries are defining various Avoid/Reduce, Shift and Improve (A-S-I) strategies, aimed at reducing or avoiding unnecessary travel, promoting and shifting to public transport and active modes, and improving energy efficiency and vehicle technology. In this paper, we take a closer look at some of the regional and national strategies and policies to reduce GHG emissions in Europe, as well as the models and methods used to assist in policy development. Keeping in mind the limited guidance on concrete avoidance/reduction and transfer strategies mentioned in the climate actions, we list some of the land use and transport interaction (LUTI) models that can be used to improve climate change control at the urban scale. The aim of this paper is to gain a better understanding of how methods and tools can assist in decision making and policy development with respect to GHG emission reduction goals in the transportation sector.

ABSTRACT. This paper examines the relationship between household trip frequencies and residential level of accessibility to tease out the direct and indirect effects of observed behavioral differences, thereby disentangling this bidirectional relationship. We estimate a multivariate ordered probit model system, which allows dependence due to both observed and unobserved factors, using data from the 2016 Transportation Tomorrow Survey (TTS), a household travel survey in the Greater Golden Horseshoe Area (GGH) in Toronto. The modelling framework is used to analyze the influence of exogenous variables on eight outcome variables of accessibility levels and trip frequencies by four modes (drive, transit, bicycle and walk). The results confirm that in addition to strong correlations existing between the residential level of accessibility and household trip frequency, there are also direct effects to be observed. Complementarity between drive-accessibility and transit-trips, and substitution observed between transit-accessibility and drive-trips highlight the neighborhood dissonance of transit riders. Essentially, both jointness (due to error correlations) as well as directional effects observed between accessibility and trip frequencies of multiple modes results offer strong support for the notion that these constitute a bundled choice and need to be considered as such.

ABSTRACT. Abstract: Commuting efficiency is an important indicator to reflect the quality of urban life. Based on mobile phone data, this study examines how commuting efficiency, as measured in commuting distance and time, is associated with different built environment features in Shenzhen, China. The K-means clustering is firstly employed to group different commuting behavior patterns. Then, the gradient boosting classification trees are trained to identify how the patterns of commuting efficiency are influenced by various built environment factors. Results show that: 1) the commuting efficiency is low in the job-dense central areas as destination; on the contrary, the suburbs and exurbs along both sides of subway have low commuting efficiency; 2) the collective contribution of built environment variables to the prediction of commuting efficiency is the largest, and the influence of residential built environment factors on commuting efficiency is larger than that of workplace built environment factors; 3) nonlinearity generally exists in the relationship between built environment and commuting efficiency, and the nonlinear patterns vary among different classes and variables. This study provides scientific basis and policy reference for improving urban commuting efficiency and promoting sustainable transportation.

ABSTRACT. The present study analyses the urban growth patterns of the Mumbai Metropolitan Region (MMR) using satellite data from 1999, 2009, and 2019. Classified land use/cover is used to quantify urban growth, which shows an increase in the built-up area by 89.44% in two decades (1999-2019). All areas except Greater Mumbai and Ulhasnagar show consistent double-digit growth rates (>20%). Future urban growth quantities are predicted using the Markov chain (MC) model, and the predicted quantities are spatially distributed using three Logistic Regression (LR) based models. The LR models consider various causative factors, such as proximity to transportation networks, urban centers and infrastructure facilities, terrain slope, and distance to northings and eastings for capturing directionality. The MC-LR-CA hybrid model has shown the highest spatial accuracy (76%) and is used for predicting urban growth in 2029. The model prediction shows a new wave of peri-urban growth in MMR during the next decade (2019-2029), with overall urban areas increasing to 983 sq. km (an increase of 19.7%). The urban growth zonation maps are also developed that show high growth prospects in rural areas, special planning areas, and smaller municipal corporations.

ABSTRACT. Urban development naturally increases the traffic and in particular the number of trips made by residence in any typical urban area. In general, a new developed area tries to resolve the forecasted additional load by planning transit services. In this article, a transportation system that was implemented in Tel Aviv, Israel, metropolitan area is presented. The system consists of a light rail services connecting a new developed area to the city. This article explores the effect of the new area on the number of trips as well as transit usage, by utilizing a split mode investigation and forecast data which was produced by the Tel Aviv Metropolitan Transportation Forecasting model. The research demonstrate how discrepancies between the transit service - which had been planned for radial long trips to the metropolitan CBD - to the urban development, which consists of large local employment areas that encourages short internal trips causes a system un-efficiency and poor service, as the opposite as would expected. The effects of urban density’s expansion

ABSTRACT. Understanding Built-up evolution and complexity over time is attained to exercise sustainable development and smart implementations in the future. The Spatiotemporal evolution analysis is carried out using the centroid shift model considering the geometry of the built-up from 1975 to 2019 (1975, 1990, 1999, 2009, and 2019). The centroid shift indicates the trajectory of the growth pattern as well as the future direction of growth. The study showed a unidirectional growth pattern till 2009, considering 1975 as the base year; by 2019, the growth direction shifted by 3.52 degrees, and the overall centroid shift magnitude was 2.42 km2. The non-Euclidean geometric nature of the physical world puts forward fractal geometry to understand the complexity of built-up. The mean fractal dimension index shows the growth type in the study area; further, a directional approach towards the mean fractal dimension provides a critical understanding of the complexity around the built-up centroid. Among all the eight directions, NW_W showed maximum built-up growth with infilling growth type, and the E_SE direction showed a significant jump in an area with external expansion by 2019. This direction indicates the future growth direction. The study concludes that complexity analysis critically enhances the Spatiotemporal dynamics of built-up evolution.

ABSTRACT. E-cycling (EC) is often considered a simple ‘upgrade’ to conventional cycling (CC), but important differences exist between the two modes in terms of experiences, values, and worthwhileness. Using Chi2 tests and binary logistic regression, this study analyzes 8543 e-cycling and conventional cycling trips legs across eight European countries collected through the Woorti mobile app (May-December 2019) and evaluates differences in negative and positive trip experiences, valuable activities, worthwhile travel time, trip characteristics, environmental elements, and demographic characteristics. Results indicate that the appreciation of travel time by EC is linked to listening to music/podcasts, thinking, enjoyment, and irritation toward (unsatisfactory) infrastructure and congestion, implying that these trips are more solitary with higher experience expectations. CC use is linked to schedule predictability and a range of trip types, implying that these trips might be associated with trip chaining. These findings suggest important differences between EC and CC trips in terms of how they contribute to the intrinsic utility of travel, with implications for overall happiness and well-being.

ABSTRACT. Few attempts at introducing new personal transport technologies have made as much noise as the relatively recent appearance of electric scooters. In the United Kingdom, urban pilots for shared e-scooter services have been met with significant disruptions stemming from issues that range from the pandemic to regulatory uncertainty, recent political shifts, and slow legislative processes. This paper seeks to address gaps in reliable evidence about e-scooters’ positive and negative contributions to social and environmental development goals grounded in a framework of Transport-Related Social Exclusion (TRSE). Relying on primary data gathered via an online survey among 1,000+ users and non-users of private and shared e-scooters in UK cities and roughly 30 interviews with various stakeholders. We interrogate practices, experiences, and expectations of a myriad of stakeholders in the UK’s urban micromobility universe through eight dimensions of TRSE that encompass from spatial and temporal coverage of e-scooters to issues associated with crime, violence, and discrimination linked with these new modes of transport. The paper expands on current efforts concerned almost exclusively with the environmental, road safety, and reductionist ‘inclusivity’ considerations, adding depth and nuance grounded on key social considerations such as intersectionality, deprivation, and social and cultural values.

ABSTRACT. This study focuses on investigating how well a low-cost bicycle simulator can produce realistic cycling in scenarios with both free-flowing and interacting behaviour. A virtual reality bicycle simulator has been developed using off-the-shelf components and an experiment has then been conducted in which 24 participants have experienced six different traffic scenarios, in Lund, Sweden. These scenarios are replays of real-world traffic scenarios which have been captured on video by three drones flying simultaneously. All road users have been tracked using video analysis and the participants in the experiment have then “replaced” one of the observed cyclists in each scenario. The trajectory of the participants in the virtual environment can then be compared to the trajectory of the observed cyclist in the video. The comparison between participants and observation have been made using speed, lateral lane positioning as well as three different trajectory similarity measurements. These measurements allow comparisons not only a spatial level but also on a temporal level, into the comparison. The result shows that the about half of the scenarios produced realistic cycling with the ones in free-flow condition showing more realistic cycling compared to the ones including interactions.

ABSTRACT. Recently, cycling has increased in popularity. Still, many situations in traffic pose a risk for cyclists. Due to technological progress, however, it could be made possible to detect hazards, warn cyclists and improve road safety. Interactive systems in this area are often evaluated using virtual reality rather than in real-world settings. In this paper, we compare the results of two cycling studies: one in mixed reality (MR, N=32) and one on a test track (N=21). In both studies, we evaluate a system that notifies cyclists of potential hazards, namely getting passed by vehicles with a small lateral distance (MR study) or the sudden opening of doors onto the bike path, so-called "dooring" (test track study). We examined two hazard notifications in both conditions and compared them to a baseline without a hazard notification. The awareness message encoded the hazard type, the hazard's direction, and the exposure time. Our results show different preferences regarding hazard notification. Furthermore, users would require a learning phase to become familiar with the use of such a system, understand its covered functions, and know its limitations. Overall, the system significantly increased perceived safety in both studies: mixed reality and real-world cycling.

ABSTRACT. The paper seeks to present the findings related to the role of subjective factors on the preference for cycling that emerged from a case study on rural cycling behaviour in selected rural regions in the state of Madhya Pradesh, India. The study intended to identify and analyze a set of context-specific subjective factors sensitive to attitudes, perceptions and preferences related to bicycle use, physical environment and travel constraints in a rural setting in a developing country like India. A set of constructs were first defined after referring to the literature on social-psychological theories of mode choice and previous empirical research. A set of graded response items were used to test the validity of the constructs and develop measures for them. Finally, the preference for cycling as a subjective factor was investigated and the influence of other identified subjective factors on it were studied.

ABSTRACT. Roundabouts are bigger in size making it difficult for pedestrians to cross as walking distance or travel time is higher. Around 400 responses were collected from pedestrians using at zebra crossing facilities provided at three roundabouts of Bhopal city along with traffic volume, spot speed and road inventory survey. Ordered Logit Model was employed to analyse the pedestrians crossing difficulty considering qualitative and quantitative variables. Results found that qualitative variables are more significant in predicting pedestrians’ crossing difficulty. 8.56 % increase in directness to zebra crossing, 6.46 % increase in traffic volume and 7.37 % increase in delay in crossing found to decrease pedestrian crossing difficulty by 10%. The study also found that pedestrians feel safer to cross near roundabout when there is presence of pedestrian signal phase than refugee islands. Also, more direct route to reach destination while crossing also affect their satisfaction of directness affecting the crossing difficulty. The study results also implies that pedestrian feels safe when there are not too many vehicles plying on the road, heavy vehicles and there is an availability of pedestrian signal phase. The study will help framing policy recommendations for improving pedestrian environment especially while crossing facilities near roundabouts.

ABSTRACT. Who has spatial access to supportive infrastructure is an important equity question: lack of access to safe infrastructure for cycling may limit who has an option to use a bicycle to meet their transportation needs as well as who may achieve the physical and mental health benefits possible through physical activity. We used a national dataset of cycling infrastructure (Can-BICS), which summarizes the quantity of cycling infrastructure for all dissemination areas in Canada, to measure spatial access to cycling infrastructure in Canadian cities, and to provide a national understanding of inequitable access to cycling infrastructure for equity-deserving populations (children, seniors, recent immigrants, visible minorities, and people with low incomes). In unadjusted associations, recent immigrants and people with low incomes had better access to cycling infrastructure. After adjusting for covariates, access to cycling infrastructure was higher in areas with more seniors, more recent immigrants, more visible minorities, and more people with low incomes, but lower in areas with more children. More importantly, there are still a substantial number of people from equity-deserving living in areas with very low levels of cycling infrastructure. This methodology represents a useful tool for information transport policy initiatives to advance bicycle equity at a national scale.

ABSTRACT. This think piece addresses the challenges of transport in cities related to decarbonization, population growth, and social equity. Present policies, largely built on technical and incremental developments, are caught in a dilemma between increasing accessibility and reducing the negative impacts of traffic: Technical innovations and infrastructure investments increase accessibility but also induce more traffic with negative externalities. Present approaches like electric cars, autonomous driving, and carpooling will likely fail in sufficiently reducing carbon emissions under prevailing conditions of growing urban populations and induced demand effects. Some scholars argue that decarbonizing mobility requires more radical behavior changes. In this paper, we touch on the potential of urban design to rapidly encourage sustainable travel behavior. As a hypothetical starting point, we introduce the E-Bike City, an urban transport policy allocating 50% of existing road space to e-bikes and similar micromobility vehicles, and discuss its possible consequences. Undoubtfully, such a transformation would have far-reaching effects on mode choice and emissions but also travel speeds, accessibility patterns, and social equity. We elaborate on these consequences, how they could be managed, and to which extent they affect the feasibility of the proposed policy. Finally, we invite other researchers to discuss further visions for carbon-neutral mobility.

ABSTRACT. The shared space concept proposes to reduce traffic control to integrate road users. Yet, previous research has shown that defining boundaries to create a pedestrian safe zone is particularly relevant for a successful implementation. Therefore, to determine if road users also expect a protective barrier delimiting the safe zone, this paper presents part of the results of an online survey that explored the preferences of pedestrians and cyclists. A total of 408 participants completed the survey and ranked the alternatives (i.e. none, bollards, bushes, and stones) according to their preferences. Approaches suitable for ranking data were then applied to further understand the results, which indicated that only providing a safe zone with visual separation is not necessarily preferred when compared to the provision of additional physical barriers. Both pedestrians and cyclists prefer bushes over the presented alternatives. As bushes objectively provide less physical protection than bollards and stones, the sense of segregation, rather than the physical protection itself, seems to be particularly pertinent to shared space design. By challenging the concept of user integration, this paper suggests reinterpreting the shared space design in certain contexts to combine more physical barriers in an attempt to better accommodate vulnerable road users.

ABSTRACT. Using survey data of millennials and older adults in Hamilton, Ontario, this study identified four types of daily travelers based on their attitudes and perceptions toward transportation modes. The study also examined the association of different socio-demographic characteristics and trip attributes with the four traveler types. Findings suggest that heterogeneity exists within travel-related attitudes among different traveler types. Further, heterogeneous traveler types exist among individuals belonging to the same generation, with the same living arrangements, and ownership of various mobility tools.

ABSTRACT. Considering aging demographics of Singapore, it is important to ensure participation of elderly population to prevent them from going into social isolation. Access to public transit which in turn provides access to various urban amenities is an important factor that influences social participation and integration. Accessible transport systems help providing equal opportunities for all people in society. There is lack of transit accessibility analysis of aged population (60 or more years) in Singapore based on walking capability of elderly person. The study analyses relative quality of public transit supply and its spatial distribution within Singapore city. The approach adopted to measure public transit supply is Public Transit Accessibility Level (PTAL). We evaluated accessibility at 400 x 400 m and by providing population weightage presented accessibility at sub census zone level. Univariate Moran’s index indicates that the accessibility level and aged population are distributed randomly in different sub census zone of Singapore. The bivariate Moran’s index reveals that underserved public transit areas have less number of bus density as compared to average bus density. The obtained accessibility maps can be useful for the planers to improve accessibility in underserved areas and provide special attention to population in jeopardy.

ABSTRACT. This research proposes a framework for microsimulation modelling of traffic evacuation that takes into account the evacuation of persons needing mobility assistance (PMA). The study develops a novel approach to test and evaluates four designated evacuation routes for emergency evacuation of PMA under different network conditions. The four designated routes are incorporated into a microsimulation model for traffic evacuation. Traffic evacuation microsimulation model executes three distinct traffic volume/conditions related scenarios, to evaluate Average Travel Time (AET) for a single emergency vehicle to exit the peninsula. Three distinct traffic volume/conditions related scenarios are as follows; the first scenario considers that the Annual Average Weekday Traffic (AAWT) volume is used on the network to evaluate AET. The second scenario considers the instantaneous mass evacuation traffic volume used on the network. While the third scenario considers the policy direction of dedicated lane with green signal time given to each emergency vehicle evacuating PMA on the network. The results reveal that the fastest way to exit the peninsula for an emergency vehicle is using routes 1 and 4 under scenario 3, taking only 5 and 6.85 minutes respectively. The second fastest way to evacuate the peninsula is under scenario 1, using route 1.

ABSTRACT. Improving transport accessibility for people with disabilities (PWD) is crucial. Previous studies have shown that PWD experience numerous difficulties when travelling by public/para-transit (Bezyak et al., 2017). If public transit services and policies are not improved to remove barriers for PWD, they will continue to experience limited access. Although PWD experience public transport-related inequities and exclusions, little is known about their travel patterns, possibly because their presence and diversity are often overlooked in transport research, travel surveys, and planning practitioners (Oliver, 2013). This study investigates how PWD use accessible taxis in Toronto, Canada. We applied spatial-temporal analyses and multilevel regression models. Study data comes from a fully accessible taxi brokerage. The dataset includes roughly one million accessible taxi trips from June 2018 to June 2021. The results show that temporal aspects of trips (i.e., departure time, day of the week, and season) influence in-vehicle times. Neighbourhood-level factors, such as average income, unemployment rate, and rate of visible minorities have significant effects on in-vehicle times. These findings contribute to current academic debates on accessibility, equity, and inclusion issues as they relate to disability.

ABSTRACT. One of the biggest challenges in land use and transportation planning is understanding how urban areas can meet the goals and visions of sustainable cities. Contemporary ideologies have identified two main paradigms that contribute to sustainable cities: green urban nature and gray urban nature. The first refers to features that make cities greener, such as parks. Gray urban nature refers to those areas that are gray but are sustainable, such as dense areas or proximity of key amenities that can foster active and low-carbon travel. Accessibility to green and gray urban nature amenities by active modes of transportation is essential to evaluate if cities are sustainable. In this research, we analyze the accessibility to green (parks) and gray (food stores and pharmacies) urban nature in Montreal using the cumulative opportunities measure. The results show clusters of accessibility to green and gray urban nature and that most people can access both types of amenities. From an equity perspective, low-income groups have high accessibility to both, while high-income areas have better access to green spaces. The results also show that people with access to both live in dense areas, which is important because gray spaces in dense areas can have sustainable attributes.

ABSTRACT. Climate-change and the reduction of carbon emissions from personal travel are a top priority for many communities around the world. However, communities are facing pressure to spatially consolidate public resource provision from the perspective of operational cost-efficiency savings. This is the case for public schools, where governments are opting to close under-capacity schools and expand existing schools to accommodate lost capacity. This study quantifies the travel burdens of school consolidation/closure policy through the case of Hamilton, a mid-sized city in Ontario, Canada. Between the years 2011 and 2015, 7% of the elementary schools closed in the city. Specifically, we quantify how these closures changed the accessibility landscape for the elementary school aged population by using spatial availability, a novel singly-constrained accessibility measure. Spatial availability allows for an interpretable comparison between ‘before’ and ‘after’ policy implementation because of its unique proportional allocation property. Analysis on how carbon emissions potentially increased and walk minutes decreased are detailed. Overall, spatial availability decreased in the city and though the policy resulted in short-term operational cost-savings, families, students, and the environment now pay the price. This paper showcases how spatial availability can be used by decision- makers to quantify spatial and travel implications in policy.

ABSTRACT. Cycling is the fastest growing travel mode in cities of the Global North; however, its rapid growth does not seem to be taking place equitably. Notably, in cities with low overall cycling rates a gender gap exists: Men have been found to cycle more for both recreation and transportation purposes as well as to cycle longer distances than women. In fact, approximately two thirds of commuter cyclists identify as men in Canada, the USA, the UK, and Australia. In places with established cycling cultures, such the Netherlands, this gender gap in cycling disappears. This paper reviews current research on gender and cycling in the Global North. Two streams of research that have been used to study the topic are identified. One is largely quantitative and identifies gendered differences in cycling behaviours, perceptions, and priorities. The other uses qualitative approaches to show the ways in which bicycle mobility can be gendered. This paper concludes by calling for the integration of the two streams in both research and policy and showing potential pathways to advance truly equitable cycling cities.

ABSTRACT. Women with a migrant background exhibit different mobility behaviors than non-migrant women. Cultural barriers or lack of access to a bicycle have made it impossible for women from some countries of origin to learn to ride a bicycle themselves or to continue to do so as adult. When women leave their country of origin, these cultural rules are changed in the new living environment and the women have the chance to learn how to ride a bike. Some non-profit associations offer special cycling courses for immigrant women. As there is hardly any evaluation, little is known about the participants, their individual motives and experiences. To learn more about the immigrant women and their personal experiences, qualitative interviews were conducted with participants of cycling courses in the city of Vienna and St. Pölten. Women revealed that they had limited mobility in their countries of origin; many of them were not allowed to cycle whereas their male relatives were. Results show that the course participation increases cycling skills and women’s subjective feelings of safety. Moreover, based on the women’s stories, the picture is emerging, that the participation in the cycling course can contribute to the women’s self-determination, integration, and sense of freedom.

ABSTRACT. Regarding the latest developments in transport research and policy, “mobility of care” (MoC) is a concept that has started to be recognised. MoC refers to trips generated by activities of care for home/family. These activities are mostly associated with women and affect their mobility patterns, thus require observing mobility from a gender perspective. Using analysis with gender-perspective of Santiago’s mobility survey and an own survey we obtain characteristics of women caregivers’ mobility patterns. Findings highlight significant inequalities between genders. Specific results show: (1) twice as many women than men make chained trips because of care reasons; (2) minors conduct care-chain trips, which suggest that in the Global South minors also conduct care-task trips; (3) the presence of children in the household creates a gender gap between women and men that is not present in households without children; (4) immigrant women and single mothers make more stages in a chained trip; (5) 31,2% of trips are done for care-related reasons, with a significant difference between women and men. Our results show that including gender-perspective in transport planning can help reduce gaps between genders and offer ways of reducing poverty, which makes mobility more equitable and sustainable – environmentally, economically, and socially.

ABSTRACT. Some population groups have lower propensity to be mobile than others. The reasons for this divergence in tendencies are difficult to assess namely since some of these groups have vulnerability features and are typically less observed and analyzed in regular surveys. The aim of this research is to compare the mobility of people with and without disabilities. Data from the 2018 Origin-Destination survey for Montreal City (Canada) allows to calculate four mobility indicators. 54% of the people with disabilities are immobile during a typical weekday compared to 17% for the other group. To understand the source of the mobility gap, two estimations with Oaxaca-Blinder decomposition method are used. It has been found that a portion of this gap is explained by different characteristics of the two groups (proportion of older adults, workers, and people with driver license). The gap is also explained by disparities between people with similar characteristics. Women and older adults with disabilities are less mobile than women and older adults without disabilities. The analysis of people with and without disabilities satisfaction suggests that the perception of PT is a factor associated with the mobility gap between the two groups, but further research will be necessary.

ABSTRACT. Motorization rates, a key climate change indicator, are growing globally. Effective mitigation policy requires an understanding of the underlying drivers of auto ownership. Traditional statistical models of auto ownership have been criticized for excluding the social context within which major lifestyle decisions are made. This omission is seen as a contributor to the failure of policy to rein in motorization. This research addresses this concern by exploring the impact of one specific social group reference effect, religious affiliation, on countywide motorization in metropolitan regions in the continental United States. This research finds that religious affiliation rates are statistically significant predictors of motorization rates. This observation both reveals the importance of social reference group effects on auto ownership decisions and the potential value of tailoring sustainable transport policies to specific social groups.

ABSTRACT. Differences in gender in terms of travel behavior have been well-documented, but the experiences that women and men have during travel are understudied. Understanding the gender divide in experiences can indicate the diverse societal needs that can be met through inclusive, equitable mobility policy and infrastructure. During the MoTiV (Mobility and Time Value) project, information regarding trip characteristics (n=38,838), 41 positive and negative experiences, and 18 travel values or valuable activities were collected for four modal categories through the Woorti mobile app from participants from ten European countries (May-December 2019): micromobility (N=8,678), private motorized (N=11,859), public transportation (N=4,907), and walking (N=13,394). Chi2 tests and binary logistic regression models indicate differences in enjoyment, socializing, experiences with other people, autonomy, acquiring tickets, escorting children, facilities, and eating. Further results indicated differences in values such as fitness, browsing, simplicity, accessibility, scenery, and travel for its own sake. Not only are there clear gender divides in observable trip characteristics, but there are also differences in the subjective ways that trips are experienced. Addressing diverse mobility needs through policy and infrastructure can lead to more equitable and sustainable societies.

ABSTRACT. Market segmentation is an essential tool that can be used for the effective and extensive adoption of emerging innovations such as electric vehicles. This study uses a multi-item questionnaire to collect data from young educated Indian students, which is used to understand the factors that affect the adoption of electric vehicles among potential vehicle buyers. Confirmatory factor analysis revealed ten latent variables that impact the adoption of electric vehicles, out of which eight variables, viz. social image, social influence, anxiety, perceived environmental benefits, performance expectancy, effort expectancy, facilitating conditions, and attitude are used for segmenting and profiling potential vehicle buyers into clusters, and the other two latent factors viz. environ-mental enthusiasm and technological enthusiasm are used to measure and analyse the differences in personality traits across the different clusters. Segmentation technique, based on k-means clustering, revealed three clusters in the respondents which are found to show positive, neutral (slightly positive), and negative perceptions towards all clustering variables and are subsequently labelled as “innovation adoption leads”, innovation adoption indifferents”, and “innovation adoption idlers” respectively. The findings from this research provide better knowledge and understanding to decision-makers and can help accelerate the widespread acceptance of electric vehicles.

ABSTRACT. Globally, traffic contributes to about 25% of ambient air pollution in urban areas. Transportation contributes to the emission of Particulate Matter of sizes 2.5 micrometers (PM2.5) that can cause harm to the respiratory and cardiovascular systems, contributing to primary health effects. Past studies have measured the exposure to PM2.5 from transport modes with the help of fixed and portable air quality sensors. However, less is explored in assessing the impact of pedestrianization measures on air quality and exposure levels. The study aims to evaluate the pedestrians exposure to PM2.5 under two situations (a) weekdays - without enforcement of pedestrianization strategy and (b) weekends - when pedestrianization strategy is enforced. The study uses data collected using fixed and wearable air quality sensors during the enforcement of pedestrianization measures from November 2020 to February 2021. The findings indicate that PM2.5 exposure concentration was the highest during weekdays (when motorized transport is allowed along with non-motorized transport). But the exposure levels and inhaled dosage of pollutants are less on pedestrianized weekends (when the street is accessible only for non-motorized transport). The study results would help policymakers shift focus towards sustainable measures such as pedestrianization to improve air quality in a rapidly urbanizing area.

ABSTRACT. Sustainable mobility measures were imposed on cities with the enactment of the Federal Laws “City Statute” (Brazil, 2001) and the “Mobility Law” (Brazil, 2012). Large federal university campuses have areas equivalent to districts and deserve special attention regarding the fulfillment of these standards. The empirical study was carried out on Joaquim Amazonas Campus of UFPE. Considerations were made to analyze and improve the application of these laws on Campus. For active transportation to be effective in campuses, the number of bicycles and the proximity between stations must be greater than in ordinary urban network (Brazil, 2001). This attitude can encourage multimodality for monomodal car users (Buehler et al., 2014). Safety in active commutes will be effective reducing traffic speed with mini roundabouts (Costa, 2010), two-way streets, and separating sidewalks and bicycle paths from roadways (PPS, 2008). The reduction of distances in active commutes contributes to sustainable urban mobility because it facilitates its practice and encourage users (Stein et al., 2012). Reducing distances of car routes promotes decarbonization (SEI, 2021 apud Macário, 2022), legitimizing the opening of new driveways. Finally, the proposed implementation of a bus connection for transferring passengers to Campus and the “Mobility Law” text were discussed.

ABSTRACT. One component of the Department of Science and Technology – Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD) funded research titled, Sustainable Technology-Assisted Route Planning for Region VI (STARPLAN VI), is the partnership with State Universities and Local Government Units (LGUs) in Region VI. The partnership includes enhancement of capabilities of stakeholders in local public transport route planning. Under the PUV Modernization program of 2018, the national government of the Philippines embarked on the challenging and complex task of modernizing the public transport system of the country. The program has several components including regulatory reform, local government unit local public transport route planning (LPTRP), route rationalization, fleet modernization, industry consolidation, financing PUV modernization, vehicle useful life program, initial implementation, stakeholder support mechanism, and communication. The paper aims to highlight the tripartite partnership among Academe, Industry, and Government in addressing transportation issues and problems in the different provinces and cities of Western Visayas, Philippines by way of developing the capacities of the different stakeholders on LPTRP. Furthermore, the paper provides insights and lessons learned on the actual implementation of the research collaboration and partnership project from planning, capacity building, monitoring and evaluation, and documentation of the LPTRP.

ABSTRACT. This article aims to evaluate the impact of governmental plans for the Transamazon Highway (BR-230) on the socioeconomic development of the Brazilian Amazon region. The hypothesis is that inconsistencies in the planning and implementation of these plans have hindered the region's development, as evidenced by indicators such as HDI, income levels, employment rates, and sanitation conditions. The research methodology involves analyzing existing plans and documents obtained from Scopus and classic publications on State action, transport infrastructure, and governmental planning from 1960 to the present. The study finds that the discontinuities in governmental plans have led to incomplete sections of the Transamazon Highway and inefficiencies in the region's transport system contributing to the low levels of development indicated by the analyzed indicators. The article concludes that a more comprehensive understanding of institutional governance and the roles of economic, political, and social actors in formulating and implementing transport infrastructure projects is necessary to foster regional development.

ABSTRACT. National highway Route 228 is a main national highway connecting Hakodate City and Esashi Town in Hokkaido, Japan. At the Kaminokuni Town Odome-intersection, which is located between these two cities, roundabout operations began in October 2019. The percentage of heavy vehicles including trucks and semi-trailer trucks at the intersection is as high as approximately 20%. After the intersection had been improved, an actual driving experiment with a semi-trailer truck was conducted to obtain driving behavior data. The speed of the semi-trailer truck in the roundabout was approximately 15 km/h, and a maximum lateral acceleration of 0.17G was recorded. Both before and after the improvement of the intersection, the proficiency level in roundabout traffic rules, driving performance and safety of heavy vehicle drivers of 10 transportation companies was investigated. As of September in 2019, before the start of the roundabout operation, the proficiency level of heavy vehicle drivers in roundabout traffic rules was low, and the proficiency level in traffic rules that allow the driver to use the truck apron was only 25%. In October 2020, one year after the start of the roundabout operation, the positive effects of shortening travel time and ease of safety confirmation of intersections were demonstrated.

ABSTRACT. In this study, extensive field experiments were performed to determine the appropriate amounts of chemicals required for each road surface temperature group. The experiments were carried out at a road weather proving ground, located in Yeoncheon where road weather (including snowfall) can be artificially created. Four surface temperature groups were predetermined, according to the characteristics of de-icing chemicals on snow. For each temperature group, four different amounts of pre-wetted salt were applied to find the optimal rate for each group. As a consequence, the amount of recommended chemicals for each temperature group was found to be an average of 27.2g/㎡, which is 7.7g/㎡ (22%) lower than the corresponding amount presented in the current Korean guidelines. Applying the results of this study to snow and ice control tasks enables the minimization of the negative impacts of de-icing chemicals, but still maintaining road safety and mobility.