ABSTRACT. Over the years that Nigerian Shippers’ Council and Bureau of Public Enterprises designated some places for Inland Container Depots (ICDs) and Container Freight Stations (CFSs) in Nigeria, most of these dry ports are yet to fully become operational. This paper therefore examined the constraints against the use of ICDs and CFSs and also identify factors responsible for seaport- hinterland logistics problems in Nigeria. Respondents are stakeholders in selected shipping companies. Of the 743 targeted population 253 (34.1%) was sampled using stratified random sampling technique. Principal Component Analysis was used to extract the major factors hindering port-hinterland logistics in Nigeria. Although the Principal Component Analysis PCA classified the causative factors into five; Scree plot identified seven factors and the communalities of the analysis using 0.4 as threshold value showed that, location with strategic capacity, cost of operation, inadequacy of ships, park management and cargo handling equipment with 0.958, 0.798, 0.706, -0.652 and 0.400 respective factor loadings were the identified problems. The research concluded that, optimal utilization of rail transport and stringent enforcement is very important to realizing efficient freight flow with provision of other identified major factors in port-hinterland logistics.

ABSTRACT. Synchromodality aims to induce a mode shift in the hinterland container transport chain by enabling a dynamic mode and route choice based on real-time information on the demand, network status and resources. The concept’s sophistication level poses many challenges, which can be classified under three pillars: operational-technical, technological and behavioural/organisational. While the two first pillars are extensively shed light on in the existing research, the behavioural/organisational aspects are largely underexposed and often neglected. Therefore, this paper focuses on this third pillar. It unravels the complex behavioural/organisational nature of synchromodality by developing a conceptual twofold framework that depicts the organisational configuration of both a unimodal or intermodal (business-as-usual) and synchromodal hinterland transport chain. Since the framework demonstrates that significant organisational adaptations to the business-as-usual hinterland chain configuration might be necessary, additional measures should likely be taken to realise support from all actors and enable the set-up of a synchromodal freight transport chain. Consequently, the behavioural/organisational assumptions often adopted in studies executed in the operational-technical pillar should not be seen as evident. Further research on these behavioural/organisational aspects is highly needed to bridge the gap between synchromodal transport research and practical applications.

ABSTRACT. In recent years, logistic transporters and shipping carriers/liners have had to juggle objectives, such as cost, time, and emissions, in conducting their operations. To understand the trade-offs between these objectives, we present a multi-objective and multimodal transportation model, which we solve using the lexicographic approach to account for the hierarchy among the mentioned concerns. Based on the ranking defined in the literature, we focus on unidirectional flows to customers located along the Ontario-Quebec trade corridor from Western Europe. We also considered different optimization objectives (tri-objective, cost, duration, emissions) to make a comparative assessment of the impacts of logistics decisions. The obtained results highlight, in an international context, the importance of the costs related to road transport, while maritime transport monopolizes a significant share of CO$_2e$ emissions due to the interport distance. Thus, in a reality where transport decisions are mainly cost-oriented, it seems more practical to emphasize the role of multimodality in the land-based distribution network to alleviate the economic and environmental brunt tied to truck haulage. Finally, our findings underline the importance of the proposed model as a decision support tool given the significant financial gains if, for instance, the port of Montreal could handle vessels of larger capacity.

ABSTRACT. Intermodality is regarded as one way of achieving more sustainable transport solutions. To make intermodal transport the preferred solution among shippers, it must be attractive according to the concept of generalized transport costs. An extended model for generalized transport costs is developed, forming the basis for a principal discussion on the conditions that make one transport solution preferable to another within the context of maritime logistics. This model is then applied to the context of the Northeast Passage to discuss the necessary requirements for making an intermodal transport solution attractive relative to the current main route from Northeast Asia to Northwest Europe through the Suez Canal. Even though intermodality could be preferable in principle, current solutions cannot compete with either Arctic routes using unimodal solutions with high ice-class vessels or with the Suez route. Due to uncertainty and limited empirical evidence, a sensitivity analysis is conducted, focusing on the variables with the greatest impact on the result. Policymakers and stakeholders can consider the findings to improve transport competitiveness via the Northeast Passage.

ABSTRACT. Sea-rail intermodal transportation around the globe faces complex challenges at different degree that affects the satisfaction of shippers' needs. An efficient cargo flow between the port and its hinterland depends particularly on efficient connectivity between the seaport and rail. Sea-rail intermodal can be a cost-efficient and green alternative to unimodal road transportation. Inefficient sea-rail connectivity in the seaport slows cargo flow and affects the port capacity. Different factors could affect the system efficiency and create bottlenecks in the system. A discrete event-based simulation approach is adopted to assess the bottlenecks in the sea-rail connection in a case study that affect the flow of cargo and generate congestion. The data were collected from the port of Trois-Rivières which is our case study where a previous study identified bottlenecks in the sea-rail intermodal system in the port. So, this study is an introductory investigation of the system efficiency using a simulation approach. In order to mitigate the bottleneck in the port, and accelerate cargo flow, different scenarios of proposed strategies were examined in our case study such as increasing the share of trains to transport cargo and increasing the number of conveys of trains per day.

ABSTRACT. Railways are vulnerable to extreme weather events. Some of these are expected to increase in frequency and severity in a warming world, prompting adaptation efforts. To inform these efforts, we have analysed railway operations data from Sweden in the period 2001-2020 to learn more about the past effects of extreme weather events on train delays. We have used a database containing some 1.6 billion records regarding train movements and a total of almost 11 million delay hours. Studying the delay attributions, we find that slightly less than 1% of delay hours are attributed to extreme weather, but that in the most extreme month, this had risen to about 11%. We find that storms are the biggest contributor, closely followed by fire and snow, and that the trend is towards more such delays. Studying the size distributions, we find that the delays are largely driven by the most extreme of the extreme events, following distributions that are mostly exponential but have even more extreme peaks. In future work, we hope to quantify and illustrate how these hazards and delays are likely to evolve under a changing climate, and to propose adaptation measures.

ABSTRACT. The main goal under public transport emergency evacuation planning and management is to ensure timely and safe evacuation of passengers from transport facilities including vehicles. Practical experiments are difficult to conduct as they involve risk to people as well as it is difficult to evoke conditions pertaining to emergency evacuation. In that case, modelling through simulation can be a good alternative. In this study the effectiveness of vehicle designs under emergency situations are evaluated for double decker train coaches introduced by Indian Railways. In this study simulation of passenger movement in emergency and smoke dispersions are modelled using Pathfinder® and Pyrosim®. Through simulations this study is able to develop the matrix for required safe egress time and the available safe egress time for various conditions. It is observed that the time required for all the passengers to evacuate under normal conditions is less as compared to the time they will need to evacuate under emergency conditions. This can be due to the crowding and herding that is observed at the exit doors. It is found that factors like door width, number of doors and their position and passenger heterogeneity has a significant impact on the total evacuation time.

ABSTRACT. Delay is a service quality measure in urban and intercity rail systems, reducing their operational efficiency and reliability. Accurate estimation of train delays is one of the main challenges in railway operation due to complex interrelations among the operating elements and inherent uncertainty associated with their behavior. Markov chains have recently been used, in this respect, to model variability in departure and arrival delays of trains in running and dwelling processes. In this study, we measured the performance of delay-based homogeneous and non-homogeneous Markov models and benchmarked them with artificial neural networks, support vector machine, and random forest models. The results show that Markov models can make comparable predictions. Moreover, due to their interpretability and transparency, the Markov chains allows us to gain insights into delay transitions in various processes and to make statistical inferences, such moment estimations and occurrence probabilities for delays. Model comparisons also imply that the process of train running and dwelling is memoryless.

ABSTRACT. Road freight transport is the most used mode, and its importance is expected to increase. Access to any location is the main reason for its proliferated use. However, the industry faces myriad challenges due to acting in a complex, dynamic environment. Effects, such as rising customer expectations or the need for sustainability, increase the pressure for decision-making. Operational planning is particularly affected due to numerous decisions and short lead times. Furthermore, decisions can become unfavorable within minutes due to external developments, such as traffic jams. Technological developments have led to storing more data. Machine learning, is regarded as powerful to generate valuable insights for road freight transport. However, despite some successful lighthouse projects, practitioners struggle to identify use cases. Even though information on operational planning is available, a lack of machine learning knowledge hinders implementation. To support road freight transport practitioners in reaping the envisaged benefits, a machine learning implementation guideline is proposed. Design science was used to develop the guideline, established on a multi-vocal literature review. Existing frameworks and their drawbacks were identified to build a guideline addressing all phases relevant to machine learning projects. The guideline was evaluated with a use case from a road freight transport company.

ABSTRACT. The development of agent-based modeling in traffic simulation allows for the modeling of traveler movement and decision making using predefined rules and variables. In this context, machine learning techniques have evolved to investigate the prospect of improving and overcoming some limitations of these tools through learning, exploration, and even retraining of original models. This paper focuses on the reproduction of the models that simulate variables reflecting traveler decision making, such as mode choice, travel distance and duration, and waiting time. A variety of data-driven techniques have been employed in this regard to model these features resulting from unanticipated activities in a dynamic environment. The proposed approach will be based on synthetic data generated from various simulation scenarios, that will be followed by a data preparation process. Therefore, the robustness of the built machine learning models was tested and assessed in different and new situations in order to evaluate their capability to reproduce the models responsible for generating the stated variables. Experiments show that the suggested solution has a high level of robustness, implying that it can replicate the final results of these models.

ABSTRACT. In recent years, numerous research efforts and pilot projects have shown that cargo bikes in combination with micro depots (MD) are a sustainable alternative to motor vehicles, especially in urban logistics. However, a holistic modelling, optimisation and evaluation of freight transport systems requires a close examination of all interactions, both on the strategic as well as on the operational and tactical decision-making level. In this study, we optimize the logistics network of micro depots for a two-stage distribution at urban level from distribution centres via micro depots to the end customers. Additionally, we evaluate the impact of cargo bikes and electric vehicles on the infrastructure layer of a multi-layer network and design a tool for strategic transport and logistics network planning. We introduce this integrated approach to solve the two-echelon location routing problem, i.e. LRP, by using microscopic agent-based transport simulation and divide-and-conquer heuristics. Finally, we evaluate our results by applying our framework on a case study focusing on courier, express and parcel (CEP) market for Berlin, Germany and comparing different scenarios. The proposed metaheuristic could significantly reduce the number of MD in the delivery area together with increasing total utilization of cargo bicycles in the presented case study.

ABSTRACT. Synchromodality has evolved as a concept to improve freight transport and modal shift by utilizing the supply chain's existing managerial, technical, and technological resources to synchronize multiple stakeholders in real-time. The current implementation of this approach in actual transport and logistics systems is scarce in part due to the lack of visibility on critical processes. This paper conciliates fundamental attributes of synchromodality, shows how they are connected to visibility, and proposes the federated data space concept as a facilitator to improve visibility on the fundamental process of synchromodality. Finally, we identify the mode selection authority as a trigger of key processes in synchromodal ecosystems.

ABSTRACT. Rail-truck intermodal transportation plays a vital role in freight transportation. In this paper, we have developed a model for designing an optimal rail-truck intermodal transportation network. The locations of intermodal terminals are not pre-defined, and the proposed model determines the optimal locations of intermodal terminals, the number and type of intermodal train services, and the freight routing. The proposed optimization program is used to study numerical examples, and sensitivity analysis is performed to gain the following managerial insights: first, a reliable estimation of demand is needed when designing a network as it affects the network structure. Besides, a reliable estimation is necessary to avoid losing potential customers due to lack of capacity in the network. Second, it is crucial to have enough terminal capacity to meet demand, however, extra capacity will not necessarily result in lower overall cost.

ABSTRACT. COVID-19 has seriously affected freight transportation and received increasing attention. However, the effects of the epidemic on transportation modal shift have not been comprehensively explored. Based on the monthly panel data of 21 Chinese provinces from September 2021 to August 2022, the paper adopts a difference-in-differences (DID) model to investigate the epidemic’s impact on the modal shift, including heterogeneity and moderating effects models. We also emphasize the spatial spillover effects and conduct a spatial difference-in-differences (SDID) model. The results indicate that the epidemic has promoted the modal shift from road to waterway but has no long-term promotion. In provinces with well-established waterway infrastructure, higher green levels, and a policy foundation, the epidemic has a more significant improvement in the modal shift. The lower waterway freight rates also can enhance the influence. Moreover, the epidemic has positive spatial spillover effects in neighboring provinces. The decomposition results indicate that the spatial spillover effects are mainly between the province with the epidemic and the neighboring provinces without the epidemic. These findings can provide decision-making reference to the transportation sector in promoting the modal shift from road to waterway in the post-epidemic period.

ABSTRACT. Stimulating the modal shift from road to railway of automobile transport facilitates the construction of a low-carbon freight system. This paper investigates the pricing problem of railway operators for automobile transport from the Yangtze River Delta region to the seven regions of China, taking into account the choice behaviour of shippers, the profit objectives of railway operators, and the modal shift targets of the government. Moreover, the monopoly railway operator’s cost of automobile transport is calculated. The results show that the profits of railway operators are affected by their costs and road competition. The mixed logit model considering the interaction effect has a better model fit. With the increased distance, the value of time in automobile transport decreases. When railway operators of automobile transport seek to maximise profits, the optimal pricing from the Yangtze River Delta to the seven regions is different in China. To achieve the government’s targets of modal shift and unchanged railway operator profit, the government can reduce rail access charges, and the required reduction varies from region to region. This study aims to help railway operators of automobile transport with pricing and to provide analytical tools for government policy making.

ABSTRACT. Estimated Time of Arrival (ETA) forecasts can be used to dynamically adapt the route planning for the pre-and post-haulage of intermodal transportation in response to delays on the main leg. However, the quality of the ETA forecast depends on various factors. It changes over time and generally increases as the train under consideration approaches the destination terminal. For freight forwarders, it is not readily apparent if and when they should reschedule. This results in a dynamic and stochastic Pick-up and Delivery Problem with Time Windows and clustered release dates (PDPTW-crd). A complex optimization problem that has not been tackled in the context of intermodal transportation so far. This paper discusses the intermodal transportation setting in detail, including the key features and unique characteristics. We develop a model capturing these key features. Further, we present a simheuristic algorithm to analyze the clustered dynamic and stochastic ETA forecasts and propose a simulation study based on real-life data.

ABSTRACT. To investigate the impact of urban freight and land-used related decisions on energy efficiency, congestion, and emissions, the authors developed a Behavioral Microsimulation Software (BMS) that simulates freight vehicle tours generated in a study area. At the most general level, the BMS provides aggregate performance metrics. At the detailed level, it outputs the freight vehicle tours and their corresponding characteristics. This study sheds light on the impact of the location of logistic facilities on the delivery operation to businesses in metropolitan areas. Thus, the goal of this research is to quantify the impacts of three scenarios in a metropolitan area: (i) location of a new distribution center in the outskirts, (ii) location of a new distribution center in the core, (iii) relocation of an existing distribution center from the outskirts to the core. The impacts discussed are vehicle-miles traveled, deliveries per tour, and the number of tours. The authors developed a case study focused on the New York State Capital Region (USA). The results indicate a reduction in total vehicle-miles traveled when locating distribution centers closer to the area's urban core, where demand is concentrated, compared to when they are located in the outskirts of the area.

ABSTRACT. Micro hubs are considered to be a possible solution to increase the consolidation of inner-city deliveries: in the City of Rotterdam it is a pontential measure to increase the logistic efficiency in and around the planned zero-emission zone. When designing the configuration of microhubs in an urban setting multiple aspects should be considered, such as their location, the type of vehicles to operate them, and the business model to be adopted for their operation. And although the topic is much studied it remains difficult to predict how different microhub configurations affect the transportation system in terms of transport movements, number of traveled kilometres, etc. This paper describes the use of the Tactical Freight Simulator (TFS) to investigate the impact of microhubs on the transportation system in case they would be implemented at a wider scale across the city centre, and make a comparison with the current state of last-mile delivery. The case study explores three different design aspects: location, type of vehicles (delivery robots, cargo bike, LEV), and the business model (individual/full collaboration). Results show that the largest reduction of vehicle kilometers can be achieved in the scenarios with full-collaboration between the CEPs.

ABSTRACT. Few studies have investigated the feasibility of carbon reduction policy with a decision trade-off perspective of urban delivery companies. With a routing planning toolkit provided by a navigation map, this study retrospectively simulated three route scenarios, namely, the cheapest, fastest, and shortest route alternatives, for one-month delivery assignments by a daily consumer-goods giant in Shenzhen, China. A microscopic path-based emission simulator simulated the carbon emissions for each route scenario. The results show that the total emissions reduction only ranges from 3.68% to 4.64%. The minor effects of carbon emission reduction in routing decision trade-off suggest the low feasibility of delivery companies would voluntarily choose the route with the least carbon emissions without cost reduction stimulation. Understanding the drivers of differences across route alternatives elucidates how urban green logistics policies could work well in the current infrastructure and market environment.

ABSTRACT. In recent years, innovative city logistic concepts for courier, express, and parcel (CEP) shipments have raised particular interest in contributing to a more sustainable transportation system. One solution can be the utilization of existing urban rail infrastructure. A so-called 'cargo tram' transports goods to an intermodal city hub, where cargo bikes cover the last leg to the receiver. Although conceptional studies exist, detailed analyses of the effects on the overall transportation system still need to be carried out. Hence, in this study, we develop a methodology that integrates urban rail-based parcel transport into an existing agent-based modeling framework. Instead of a single mode choice, a two-stage selection model based on transport chains is developed, comprising a rule-based and utility-based stage. The model is applied to the city of Karlsruhe, Germany, where the overall effects of rail-based parcel transport are simulated and evaluated in different scenarios. The results show that the realization of a rail-based parcel transport can reduce the overall mileage and number of trips caused by CEP shipments. However, the potential is driven by several factors, such as the number and location of city hubs, the maximum range of cargo bikes, and the overall evaluation of the cargo tram.

ABSTRACT. Collaborative last mile solutions, such as the collaborative use of parcel lockers, jointly used logistics facilities in inner city area, and white-label delivery play an increasing role to alleviate inefficiencies particularly caused by failed home delivery attempts and generated externalities associated with last mile deliveries. However, there is limited research on the impacts of collaborative delivery approaches in last mile logistics. Therefore, this paper explores the extent to which collaborative delivery solutions contribute to a more sustainable urban transport and what impacts can comparatively be observed on relevant parameters (e.g. number of trips, mileage performed, costs, emissions) in one single case study. For this purpose, a synthetic world for the City of Hamburg, Germany, has been built up focusing on the parcel market with respectively parcel service providers as well as their private and commercial customers. Based on this, a reference scenario and three collaborative distribution scenarios (e.g. white-label delivery, collaborative use of parcel stations) are developed which are simulated by the microscopic agent-based transport simulation MATSim and the integrated logistics behavior model Jsprit. Results strongly indicate that positive transport-related, economic and environmental impacts could be achieved through the implementation of collaborative delivery solutions.

ABSTRACT. Emergency vehicle preemption (EVP) is one of the common traffic signal preemptions to prioritize the right of way to emergency vehicles at signalized intersections by terminating active signal timing plans and running preemption plans. However, such mandatory signal changes can disrupt arterial signal coordination when an emergency vehicle travels through a well-coordinated signalized arterial. Selecting an exit strategy in traffic signal controllers to recover from EVP is less emphasized and very limited research has been conducted to utilize the exit strategy to minimize disruptions of EVP on arterial signal coordination. Therefore, this research summarized EVP operations along with preemption modules in North America Econolite Cobalt signal controllers and investigated five available EVP exit strategies. The impacts of five exit strategies on arterial signal coordination were evaluated and compared on a signalized arterial through hardware-in-the-loop simulation in four different simulation scenarios. From simulation results, it was found that the EVP tends to worsen intersection operations by increasing the total vehicle movement delays at preempted coordinated intersections. The performance of different exit strategies is influenced by the route of the emergency vehicle and the EVP activation point. Additionally, the selection of an EVP exit strategy depends on different operational objectives after EVP.

ABSTRACT. Automated traffic signal performance measures (ATSPMs) can be an innovative technique that allows for data-driven management for traffic signal timing. Currently, two types of data are mainly used to produce ATSPMs, which are controller event log data and vehicle movement trajectory data. Vehicle telematics data can provide a huge amount of vehicle trajectories moving along signalized arterials, which indicates a breakthrough for trajectory-based ATSPMs. In this paper, we aim to compare the two approaches from a practical perspective. Vehicle telematics data is an emerging data source that has been commercially available in the United States. In addition, the paper presents a case study of the Reno-Sparks Region in Nevada using vehicle telematics trajectories to evaluate signal performance for two arterial segments. The case study shows that vehicle telematics trajectories can be a viable source for ATSPMs. As a result, we conclude that trajectory-based ATSPMs can fit transportation agencies’ needs, especially for those that don’t have enough resources to upgrade intersection infrastructure for performance measure purposes.

ABSTRACT. The traffic signal control (TSC) temporally assigns usage of space and time at intersections and is considered as the basic countermeasure for improving the efficiency of road networks. Recent studies favored the algorithm developing of adaptive TSC with deep reinforcement learning (DRL) because its active learning property is more applicable to complex traffic situations. However, DRL-based methods have always been accused of lacking robustness. Unpredictable disturbances, such as the traffic arrival surge, may provoke instability hazards in the adaptive TSC algorithms driven by artificial neural networks. To this end, this study proposes an online learning algorithm for adaptive TSC problems based on deep Q networks, namely the robust learner, which highlights the feature of good robustness. Combined with knowledge of traffic practice, several significant improvements are made to the DRL algorithm that describes the TSC queue evolution. Results of simulation experiments indicate that the proposed robust learner can lead to more stable control performance under multiple random seeds compared to the learning algorithm without corresponding modifications. Meanwhile, the proposed method is with faster adaptability to traffic state transition, such as a surge of traffic input.

ABSTRACT. Synchro, PTV Vistro, TransModeler, Tru-Traffic, and TranSync are software programs part of different software packages that can all be used for traffic signal coordination tasks in countries that use ring-barrier signal controllers. Each program has different functions, features, inputs and outputs. Synchro, Vistro, and TransModeler all require volume inputs to make an analysis while Tru-Traffic and TranSync do not require volumes. The same arterial will be modeled in all five programs and phase sequence and offset default optimization functions will be executed separately for Synchro, Vistro, Tru-Traffic and TranSync. The average travel time and average number of vehicle stops will be simulated using TransModeler, a third party traffic simulation program to ensure results are not biased. Results showed that Synchro and Tru-Traffic had the lowest travel time through the whole arterial and the least number of stops. TranSync’s optimization was slightly behind Synchro and Tru-Traffic. Vistro’s optimization followed TranSync with a slightly longer travel time and slightly more stops. The usability of the time-space diagrams, reference phase options, management of timing plans, and management of timing plans for multiple arterials will be compared. TranSync has the most arterial-level features by far compared to the other four programs.

ABSTRACT. Crossing pedestrians may significantly affect the capacity of left-turn (LT) lane at signalized intersections when they are sharing the same signal phase in the left-hand traffic system. Although vehicles must yield to approaching pedestrians according to the Road Traffic Act in Japan, the phenomenon that they cross in front of pedestrians frequently occurs. The objective of this study is to estimate left-turn lane capacity based on vehicle yielding maneuver model to pedestrians considering pedestrian volume, crosswalk length and signal timing. The vehicle yielding maneuver model was developed by using the observed data of several crosswalks in Japan. Finally, a Monte-Carlo simulation was conducted by applying the proposed vehicle yielding maneuver model. In addition, the simulation results were compared with the calculation results based on the current method in the manuals of Japan and U.S., as well as the observed data.

ABSTRACT. Anticipatory Adaptive Cruise Control (AACC), as defined in this paper, builds on ACC automation and connectivity features of IoT-enabled TCP-S to allow a following vehicle to automatically adjust its cruise control through access to information on the speeds of three or more of the vehicles further downstream. This paper analyzes the behavioral effects of a mixed traffic environment in which AACC and manually-driven vehicles co-exist. MIXEM, a microsimulation package, is developed manually-driven and AACC-equipped vehicles by three-phase theory. In the case of a signalized intersection scenario, the AACC reduced the approach clearance time by half for a fully-equipped vehicular traffic flow compared to non-equipped vehicles. The fixed bottleneck scenario indicated the potential of AACC in reversing the state of traffic from wide-moving jams to synchronized flow, thus altering the shape of the fundamental diagram (FD). AACC is shown to be effective in reversing capacity drop phenomena while increasing bottleneck discharge flow rates. The results show that the AACC driving responses that proactively maintain the ideal distance, responses, and speed project a mirror-induced behavior on manually-driven vehicles traveling in their vicinity. These findings support the potential of AACCs as floating traffic regulators that induce good driving behaviour.

ABSTRACT. The combustion of fossil fuels as the principal source of energy in transportation systems contributes to the extensive emission of Greenhouse Gas (GHG) and NOx, thus further exasperating global warming and health risks. In this paper, travel time, GHG and NOx emissions reduction on urban road networks has been investigated by considering an anticipatory routing strategy for different types of Electric Vehicles(EVs) into the network of connected and automated vehicles. The procedure was then replicated for non-connected and automated vehicles to compare the results and show the efficiency of both moving towards alternative fuels, connectivity, and automation in terms of health and environmental issues. The downtown Toronto road network is used as the case study and highly detailed data are synthesized using a calibrated traffic microsimulation and MOVES. A well to wheel analysis The results of this experiment show that in a mixed fuel environment with equal shares of EVs and Conventional Vehicles, connectivity and automation showed to improve the GHG cost to a great extent. In another observation of this case study, the impact of electrification proved to be more prominent than the effect of connectivity and autonomy of vehicles in the network for reducing both NOx and CO2.

ABSTRACT. Intelligent Transport Systems (ITS) can improve transport systems while reducing their negative impacts. The deployments of ITS applications are highly dependent on telecommunications technologies, which must be tested either in field experiments or in simulation. The traffic simulation is the least expensive and most flexible solution. Yet, models require large amounts of data and expertise to develop, and the impacts of their parameters on their outputs for ITS applications have not been much investigated. Using the Simulation of Urban Mobility (SUMO) tool as an example, this article attempts to build automatically a simple large-scale traffic model for the Island of Montreal and evaluates how this model performs. This paper considers microscopic and a mesoscopic models, along with three traffic assignment methods. The outputs are compared to travel times from global navigation satellite system (GNSS) data and from Bluetooth sensors, and a sensitivity analysis is also performed for several output indicators at different scales. The results highlight the trade-offs between more detailed and accurate microscopic models, and faster, less accurate, mesoscopic models.

ABSTRACT. This study proposes an event-triggered bi-level control method for multi-lane freeway on-ramp merging sections under a connected automated vehicle (CAV) environment. The controller consists of a scheduling layer and a trajectory planning layer. As a most prominent feature of this study, the scheduling layer makes lane-changing and facilitating vehicle decisions based on the impact of these vehicular-level decisions on traffic efficiency. Specifically, a mixed integer nonlinear programming (MINLP) model is formulated with the objective of minimising total travel time and meanwhile discouraging unnecessary lane changing maneuvers. The lane-changing and facilitating vehicle decisions jointly define the optimal driving sequence of each mainline lane after merging. With the indications from the upper-level model, the lower-level model is responsible for planning cooperative lane-changing and merging trajectories. Two typical case studies are analysed to explain the proposed controller’s decision-making and demonstrate its effectiveness.

ABSTRACT. Motorcycle food delivery riders (FDRs) are highly vulnerable to crashes. Some of these crashes with FDRs are caused by the drivers of other vehicles. This paper assesses perceptions and observed riding behaviors of FDRs by drivers through a survey and analyses factors related to drivers' crash risk with FDRs. Results indicate that the drivers observed unsafe behaviors like tailgating and weaving. Observed unsafe riding behavior of FDRs were associated to driver demographics, driving characteristics, and personality trait anger. Perceptions related to motorcycle riding by FDRs were affected by driver motorcycle riding experience and personality anger trait. The drivers with motorcycle riding experience showed better understanding of FDR riding behaviors. Driver age, employment, motorcycle riding experience, traffic violations, emotional state while driving, factor scores for observed FDR violations, and perception regarding easiness to swerve a motorcycle affected the crash probability with FDRs. Moreover, only dual-licensed drivers with more than 5 years riding experience had a lesser crash probability with FDRs. Therefore, motorcycle riding behavior awareness and training regarding mixed traffic conditions are necessary to reduce the crash risk with FDR. The results could help develop strategies that contribute to improving safety in mixed traffic environment by reducing biased perceptions regarding FDRs.

ABSTRACT. The present work investigated riding behaviours of motorcyclists in a mid-sized Indian city where road infrastructure, public transportation systems are not well developed and enforcement is low. A paper–pencil based questionnaire was designed to collect responses from the motorcyclists who commute in and around Asansol city. Analysis of data have shown the risk-taking tendencies of the motorcyclists although majority of them have sound knowledge on safe riding behaviours and traffic rules. This clearly justifies that it is not only the awareness about the road rules, but an equal emphasis is also necessary on enforcement. Exploratory factor analysis produced four latent factors accounting for 64% of the total variance. The factors are coined as: ‘traffic errors’, ‘control errors’, ‘safety perception & attitude’, and ‘deliberate violations’. Poisson-regression model reveals that ‘control errors’ (i.e., the errors committed related to controlling the vehicle) is most influential to predict crash risk. In addition, crash risk was observed to be directly correlated with riding experience. The findings justify due considerations are necessary in formulating policies related to reframing of the issuance and renewal of drivers’ licensing system, enforcement and road-engineering interventions for holistic enhancement of safety of motorcyclists, especially in the context of developing nations.

ABSTRACT. This study aimed to investigate the association between drunk riding, unhelmeted riding, unlicensed riding, and running-off-road (ROR) crashes. Multiple logistic regression was used to calculate the adjusted odds ratio (AOR) by using Taiwan National Crash Data for 2011–2016. The results revealed that unhelmeted riding increased the risk of drunk riding and unlicensed riding by 138% (AOR = 2.38; CI = 2.34–2.42) and 47% (AOR = 1.47; CI = 1.45–1.49), respectively. The risk of unhelmeted riding increased with blood alcohol concentrations (BACs), and riders with the minimum BAC (0.031%–0.05%) had nearly 5 times(AOR = 4.99; CI = 4.74–5.26) higher odds of unlicensed riding compared with those of riders with a negative BAC. Unhelmeted riding, drunk riding, and unlicensed riding were associated with 1.21-fold (AOR = 1.21; CI = 1.13–1.30), 2.38-fold (AOR = 2.38; CI = 2.20–2.57), and 1.13-fold (AOR = 1.13; CI = 1.06–1.21) higher odds of ROR crashes, respectively. Riding without a helmet may induce drunk riding and unlicensed riding. The three risky riding behaviours (i.e., unhelmeted riding, drunk riding, and unlicensed riding) significantly contributed to ROR crashes. The risk of unhelmeted riding and ROR crashes linearly increased with BACs.

ABSTRACT. Road crashes are the leading cause of death all over the world. This study considered four type of control variables to analyse the riders’ behavior at the speed breaker. The control variables are a) inadequate infrastructure, b) rider psychology, c) individual characteristics, and d) advance warning systems. The rider psychology is influenced by introducing distraction and time pressure situations. The rider behavior was estimated using three performance parameters: 1) Time Till Impedance (TTI), 2) Speed Reduction Ratio (SRR), and 3) Speed at a speed breaker. The generalized linear models were developed to quantify the rider behavior based on the rider and infrastructure characteristics. The results showed that the poor visibility of the speed breaker resulted in a 12.3 kmph higher riding speed on the speed breaker. Results also revealed that advance warning system can act as distraction to the rider and deteriorate the riding performance. Overall, findings indicate that visibility of the speed breaker, rider psychological riding state, and individual characteristics can significantly influence the riders’ response to the road infrastructure and technological interventions. Therefore, to improve the road safety effectively it is very important to consider the road user’s behavior and adaptation to safety interventions.

ABSTRACT. Large ownership and usage of motorcycles in many developing countries cause significant road safety issues. This study uses big trajectory data collected from over 1600 motorcyclists over a 1.5-year period from Karachi, Pakistan. Trajectory data is coupled with self-reported crash information along with motorcycle rider characteristics to predict the likelihood of involvement of a motorcyclist in a crash in the near future. The formulated problem has considerable significance for motorcycle insurance companies and such organizations/start-ups that manage a fleet of motorcycles to run their businesses. A random Forest-based machine learning algorithm is employed by taking inputs based on a variety of features derived from trajectory data. These are mobility-based features, acceleration event-based features, aggressive overtaking event-based features and motorcyclists' socio-economic features. In total, 89 features are used and SMOTE technique is employed to address the highly imbalanced nature of the binary outcome (crash/no crash). Recall, precision and f1 score of the developed model for test data indicate the reasonably sound predictive performance. The model is useful in identifying risky motorcyclists and provides opportunities for insurance companies to introduce insurance plans that are dynamic and based on driving performance.

ABSTRACT. As the nations embark into the second decade of action for road safety, it is opportune that we critically review past mistakes and emphasize thrust areas to meet road safety targets. Road safety of vulnerable road users (VRUs) and hit-and-run road crashes are two such areas that have had alarming trends in the past decade and necessitate concerted efforts. India, as the world leader in road traffic fatalities, is observing threatening numbers of VRUs and hit-and-run road crashes. The present study focuses on providing a solution to these correlated road safety issues by predicting the unknown striking vehicle type in case of hit-and-run road crashes involving motorized two-wheelers as the victim. Delhi, the capital of India, is the study area for the experiment. Predictive techniques such as supervised learning classification models are employed. Ensemble learning technique, such as Random Forest, has been found to perform best and have the maximum capability to predict the unknown striking vehicle type in hit-and-run road crashes involving motorized two-wheelers. The study findings are helpful for traffic enforcement agencies and policymakers to strategize action and execute prevention plans to improve the overall road safety situation.

ABSTRACT. The safety concerns of child pedestrians is gaining an increased importance these days. They are a vulnerable group of road users because of their specific traffic behaviors and safety perceptions. This study attempts to give an extensive overview of the literatures available regarding the behavior of child pedestrians on streets using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The overview was carried out focusing on the literatures published till 2022 all over the world. A total of 54 literatures were reviewed. The primary aim of the study was to analyze the available literatures based on study locations, methods of data collection, parameters influencing child pedestrian behavior on roads, safety perception among children and existing models for analyzing the behavior of child pedestrians. Overall findings across the literatures reveals that majority of the studies were conducted in China. It was found that ‘supervision’ was the most frequently considered parameter in a major proportion of the studies. The most commonly used model to analyze the behavior of child pedestrians was found to be multivariate regression. To the end of the review, key insights and limitations of the study is also presented.

ABSTRACT. Car access is practically a necessity to get around rural areas in the US. Yet approximately 4.5 million rural residents do not have access to a household car. Research on rural–nonrural mobility disparities is limited. This paper addresses the gaps in the literature by evaluating and quantifying: (1) the scope and scale of rural car access, (2) socioeconomic and (3) mobility characteristics of these not owning a car in rural areas. To address these questions, we used a rural–nonrural classification to evaluate differences in car access and travel outcomes between rural and nonrural areas. The results reveal stark rural-nonrural disparities in sociodemographic and mobility characteristics by car access. Rural zero-car households earn 1.7 times less than their nonrural counterparts, and in rural areas, Black or African Americans are 3 times more likely to be carless than their white peers. When compared to their nonrural peers, rural zero-car travelers are 4 times as likely to not travel on a given day due to lack of transportation options. Collectively, evidence highlights mobility justice and inequity concerns that rural zero-car households face, which merit additional attention and policy interventions to improve rural mobility, sustainability, accessibility, and equity.

ABSTRACT. Transport is responsible for a quarter of total carbon emissions as reported by the COP26 summit. Public transport travel is widely known to have less environment impact, but how the awareness influences traveller’s choice of mode(s), whilst considering the interplay of a wide range of other factors, is under-researched thus far. The study aimed to gain understandings of commuters’ travel with attention to their attitudes towards the environment, accessibility, convenience, and safety. A questionnaire was designed, and 730 useful responses were collected to provide a representative sample of the Bangkok Metropolitan Region population. Descriptive analysis led to an understanding of the commuter population characteristics with private car followed by urban rail being the most popular. Principal component analysis (PCA) was implemented to reduce 20 attitudinal statements into an uncorrelated set. The four components retained from the PCA were labelled as “impact of travel behaviour”, “willingness to purchase low-polluting cars”, “safety and convenience”, and “attitudes to private motorised transport”. The component scores were analysed with attention to the respondent’s gender, age, and self-defined commuting transport mode. Age and mode identity firmly influenced the component especially active transport users. This research has provided decision-makers with scientific evidence for more sustainable transport options.

ABSTRACT. There is an ongoing public debate on the necessity of a more sustainable transition in transportation and mobility that can make a decisive contribution to fight climate change. This debate increases pressure on companies to improve emission balances of their transportation and mobility operations. Success is not only measured by creating measures to reduce emission balances, but to enforce them internally. With this study, we show how internal communication successfully supports the introduction and establishment of more sustainable mobility concepts while maintaining employee satisfaction. Using the example of mobility budgets, we show how the acceptance level of such necessary measures can be increased by specifically addressing the three basic psychological needs (autonomy, competence, and relatedness). Based on 20 problem-centered interviews with mobility experts as well as results from company workshops with potential end-users, we identify ways to successfully introduce mobility budgets in companies. Through our findings, we construct an acceptance model and define several success factors that implicate concrete (communication) actions for companies.

ABSTRACT. Travel behavior of persons is typically modeled as a function of their socio-demographic factors. However, travel behavior remains relatively stable over time unless a life event (such as household relocation) occurs and triggers a change in travel behavior. Most of the existing travel demand models regenerate travel behavior of agents from scratch at every model run. The inability of these models to represent the habitual travel behavior and change in travel behavior due to life events tends to exaggerate policy sensitivity and results in longer model run times. In this study, we examined the travel behavior of persons between two consecutive years using a mobility panel survey. Weekly trips by activity type and mode are compared between persons with and without five different life events. The results show that life events impact travel behavior, but the degree of impact varies by the type of life event, trip purpose and travel mode. In some cases, the impact is found to be negligible but for many other cases the impact is profound. It is concluded that such dynamics in travel behavior should be represented by travel demand models for more sensible policy testing and computationally efficient travel demand modeling.

ABSTRACT. Many travel behaviour studies focus on the interaction between attitudes and travel behaviour, but in doing so have used a multitude of attitude measurements. These studies often use surveys where respondents are asked to indicate their level of agreement with a set of attitudinal statements. However, this set of statements sometimes varies very widely between studies, making it difficult to compare results across studies as well as complicating a thorough understanding of the motivations underlying travel. This paper therefore uses a repeated cross-sectional approach where the same set of attitudinal statements was asked in an online survey organized in 2016 and 2020 in the Greater Metropolitan Area of Sydney, NSW, Australia. Findings indicate that the same type of travel attitudes persist over time (in this study: a negative attitude towards travel in general, and a positive attitude towards cars). Moreover, these travel attitudes remain characterized by (largely) the same set of attitudinal statements, indicating at least some stability in the measurement of travel attitudes. Findings of this paper can thus be helpful in reducing the heterogeneity of attitudinal statements included in travel surveys.

ABSTRACT. Smartphones enhance access to real-time and static information across various travel modes and give additional decision control to the users, thus enabling them to consider a variety of transport options available to them. Smartphone ownership has been growing at a healthy rate in India, and app-based mobility services are already operational. However, there is limited knowledge about the usage patterns of such apps, and sparse research has been carried out on the potential impacts of these mobility apps on the use of a diverse set of transport options, especially in Indian cities. So, an attempt has been made in this study to classify app users in Delhi according to their usage of mobility apps using the K-means clustering technique. Further, the multimodality of the individuals in these groups, based on their frequency of use of various modes of transport for commute and non-commute trips, has been tested using Shannon’s Diversity Index. The study discovered varying patterns of use of various modes of transportation by users from various socioeconomic groups who were clustered based on their use of mobility apps. The findings from the study have the potential to provide a basis for more informed policy decisions related to multi-modal transport.

ABSTRACT. Multimodal travel behavior is a key to the sustainable design of infrastructure. For this, significant leverage could be achieved in everyday travel. To better understand the underlying mechanisms of multimodal travel in everyday life, this work examines the relationship between the variability of activities and multimodal travel. Besides descriptive analyses, the study provides a regression comprising activity-related characteristics as well as framework conditions of multimodal travel of employees. The results show that engaging in various activities leads to using more than one transport mode. Especially leisure and shopping activities increase multimodal travel behavior. Complex travel needs are another driver of multimodal behavior, measured as a high variation of distances traveled and a high number of linked trips. Furthermore, the results indicate that multimodal travel behavior is a phenomenon of the transition from weekdays to weekends.

ABSTRACT. This article provides evidence on the organization of care activities and the forms of mobility they generate, also considering the impact of the COVID-19 pandemic, which has increased caregiving responsibilities and has exacerbated several forms of inequality related to them. Using data collected from Chile through a survey conducted at the beginning of the COVID-19 pandemic, a segmentation of the caregivers is performed, generating different profiles that characterize them. A joint multivariate model is estimated, identifying observed and unobserved effects impacting the level of stress, ease of movement, and struggle with telecommuting of caregivers. Results show that gender significantly affected the level of stress, ease of movement, and work-related activities at home during the pandemic (women are more stressed and have more spatial difficulties and work-related issues at home), even after controlling for other socioeconomic characteristics, pre-pandemic behavior, and unobserved factors.

ABSTRACT. The concentration of tourist flows to specific areas may lead to overcrowding of destinations and generate negative impacts such as alienated local residents, degraded tourist experiences, and traffic congestion. To overcome these issues and ensure public safety and make areas more convenient, effective planning and management by government and destination managers will be essential. In this study, 20 Wi-Fi packet sensors were used to collect data from the Higashiyama area, Kyoto, Japan. At the same time, a manual count survey was carried out to acquire real pedestrian count. Based on the data we first study how the real pedestrian counts can be estimated based on the Wi-Fi observations. Then we try to evaluate the crowding level of visitors on a street. As a result, the correlation between Wi-Fi packet sensor observations and real pedestrian count may fit well with the exponential function was identified and how the installation height and environmental conditions influence the data collection of the sensor was estimated. The crowding level of each link could be defined with the criteria of PLoS. This can help the local government or destination managers to balance pedestrian flow on neighbour streets in order to release crowding and improve tourists’ experience.

ABSTRACT. Effective transport planning strategies seek to improve urban transportation systems by addressing traffic congestion problems, identifying emission hotspots, incentivising  public transit and adoption of electric vehicles. Strategy makers are increasingly relying on new emerging methods such as full population scaled agent-based simulation models to study the interaction between mobility patterns of the commuters and their impact on the transportation systems. This is because the behavioural changes in daily travelling patterns of commuters play a major role in predicting the future travel demand for the development of a robust and reliable urban transportation system. It is not possible for the traditional surveys to sample a large majority of daily commuter trips that serve as input to full sample agent-based simulation. In this paper, we use the household travel survey data of Singapore to generate synthetic mobility patterns for the complete population of private vehicle users by using a multi-headed gated recurrent unit (GRU) based generative model. We define and utilize two accuracy evaluation metrics that quantify the quality of the generated synthetic mobility trips. Our experimental results have shown that we are able to capture 90\% of the correctness of the original mobility dataset of private vehicle users.

ABSTRACT. Households are more and more buying online and using various delivery solutions, between home deliveries and out-of-home collecting points (pick-up point or food drive). Based on a questionnaire survey of 593 households in France, our article aims to better understand the determinants of online shopping practices, considering the nature of the goods purchased (food or non-food) as well as the collection methods chosen. Our paper aims at refine the innovation and efficiency hypothesis of the geographical distribution of online shopping uses and mobilities. Beyond the usual socio-demographic determinants, it appears that geographical location doesn’t impact the intensity of online purchases but the choice of a particular delivery method. In fact, the choice of home delivery is more likely to be made by households that live or consider living in less densely populated areas with fewer shops. Conversely, the choice of a relay point is more likely to be made by households living in towns and cities or in areas they consider to be well equipped. Thus, in dense areas, the online purchase of material goods would generate logistical trips for households, whereas in less dense areas, households would more easily delegate these same trips to a logistics provider.

ABSTRACT. COVID-19 mitigation measures triggered a sharp increase in adoption of teleshopping and telecommuting activities. However, there is a need to understand extent to which past frequencies and experiences will affect post-pandemic teleactivity behaviour. Moreover, teleshopping and telecommuting are interconnected and inter-relationship may exist among them in post-pandemic world. This study aims to investigate future preferences toward online grocery shopping, online food ordering, and working from home by utilizing a multivariate ordered probit (MVOP) model. The data comes from a web-based survey conducted for the Central Okanagan region of Canada. Model results confirm the presence of unobserved factors influencing telecommuting and teleshopping choices. Interestingly, endogenous variable “future work from home” revealed a positive effect on future online grocery shopping. Model results also confirm the significant impact of past teleactivity frequencies and experiences on post-pandemic preferences. Overall, findings provide important insights into post-pandemic activity-travel patterns which can be utilized for robust policymaking.

ABSTRACT. Teleworking has been disseminated throughout the world with the spread of the coronavirus, which has brought about changes in our workstyle. To better understand teleworking, a web-based questionnaire survey was conducted at the end of March 2020. The survey registered 3,500 respondents who worked and lived in three metropolitan areas in Japan. In this study, the choice and intention to telework were analyzed, while considering the trade-off between commuting and teleworking, as well as incorporating the cost and benefit of both commuting and teleworking. The commuting cost includes travel time, travel-related risks (contracting COVID-19), and satisfaction with travel scale. For the cost of teleworking, risks of ICT use were incorporated. The work satisfaction with teleworking compared to office-based work was measured by incorporating social presence as a predictor. Further, socioeconomic attributes such as age, family composition, type of work, and type of industries were considered. The binary probit and ordered probit model were applied to the analysis. The estimation results showed that risk perceptions, travel satisfaction, and work quality of teleworking considerably affected the individual’s preference to telework. The findings are expected to provide valuable insight into urban planning and transportation system designs resistant to the risk of infectious diseases.

ABSTRACT. The rise of telework is likely to impact work and non-work mobility patterns. Therefore, understanding the nature of telework arrangements will be crucial. This research explores teleworked days (Monday, Tuesday, etc.) and teleworking frequency (as the number of full or half days weekly teleworked). Using data from an online survey conducted in the Paris Metropolitan Area in 2022 over 841 teleworkers, two mixed models are developed to understand current but also future or ideal declared telecommuting days. Findings suggest that full-day home-based telework is and should remain the rule in the near future. Moreover, the main actual and also ideal teleworking days are Friday, followed by Monday and Wednesday. Then, people are likely to telework to better manage the transition between weekdays and weekends or organize their children’s activities. Finally, teleworking frequency should not decrease, or even increase for some categories of workers in the next years. Current telework frequency, distance to the workplace, commuting modes, seniority in teleworking, education level and the ability to reallocate commuting time on other activities are among the main factors explaining changes in teleworking frequency in the future. The conclusion discusses implications regarding the influence of telework on mobility patterns and future research needs.

ABSTRACT. This research examines employees’ preferences toward post-pandemic flexible work arrangements (FWA) using logit modelling techniques. First, it conducts an online questionnaire survey among working professionals in the Halifax Regional Municipality (HRM), Canada, to gather information on their socio-demographics, travel characteristics and work arrangements before and during the pandemic, and their preferences towards post-pandemic work from home (WFH) and flexible work hours (FWH). Using the collected 337 complete responses, then it develops a binary logit model (BLM) to examine factors affecting employees’ WFH choice, a multinomial logit model (MLM) to examine the choice of WFH frequency, and an ordered logit model (OLM) to investigate preference for FWH. Results show that approximately 55% of the employees prefer WFH, while almost half of the respondents prefer WFH a few days/week. Logit model results indicate that increasing WFH preference also increases FWH preference, while employees who perceive higher importance of FWH tend to choose higher WFH frequency. Employees with higher commute frequency during the pandemic are less likely to prefer FWA post-pandemic. Increasing commute time increases the willingness to have FWH. The results will assist transport policymakers in better understanding the factors influencing employees’ FWA choices which will aid in developing effective TDM policies.

ABSTRACT. Understanding the households’ residential relocation dynamics is of great importance in urban land-use modeling. The duration of home residence and its dependence on accessibility is one of the less studied areas of residential relocation. Residential relocation duration is usually modeled using classical survival analysis approaches. The last few years of progress in machine learning have provided a fruitful opportunity for improving such models and making the most out of the heterogenous and high-dimensional residential data. This study benchmarks the performance of ten machine learning approaches combined with six feature selection methods capable of handling survival data. The models are compared with classical survival approaches. The 30-minute accessibility to job opportunities and accessibility of workplace and education locations are estimated and included. A life-course dataset of 1,024 residential relocations from Sydney, Australia, is utilized. A model on the households' tendency to increase/decrease their accessibility after relocation reveals important policy implications, including reemphasizing public transport equity and scattering job opportunities for a more sustainable environment. Residential self-selection issue is addressed by incorporating the direct questioning approach. Using a concordance index measurement, the results indicate that classical approaches could reach 52% accuracy without any feature selection and 76% with feature selection approaches.

ABSTRACT. When a household decides to move from the current location, it takes bundle of decisions such as when to move, where to search, and others. We hypothise that these decisions are interlinked and may result in different decision-making trajectories. This heterogeneity in decision-making may exist due to the influence of different triggers, urgency, and situational setup on the search duration, spatial decisions (search criteria and search type: tenure or typology), and choice of information source which may result in varied relocation time and the choice set for different households. The paper aims to establish a need to determine these decision trajectories by quantitatively exploring the variation across decisions. A retrospective revealed preference survey was conducted in Rajarhat Newtown and Rajarhat Gopalpur in India resulting in 272 households’ samples. The findings support the hypothesis and also suggests that variation in trigger and urgency results in the variation of search duration from 1 day to 2 years whereas variation in situational setup reveals the selection of different search criteria and search type. The study bears an important implication on LUTI models by providing an approach to consider dependency across decision stages to model the relocation time, choice set formation, and location choice.

ABSTRACT. This study aims at determining the impact of travel-related residential self-selection on residential relocation, potentially influencing travel behavior, by analyzing a sample of 2,651 German respondents planning to move. This allows us to examine the relationship between the motivation to relocate, residential satisfaction and residential dissonance as a mismatch between travel attitudes and the neighborhood structure. We develop an indicator of residential dissonance that classifies 36% of respondents as dissonant. Two logistic regression analyses model the probability of indicating the neighborhood as a reason for the move among urban and nonurban residents. Residential dissonance is found to have an impact on the satisfaction with the neighborhood, but there are other travel-related characteristics that make residents want to leave their current neighborhood. In non-urban areas, the satisfaction with the quality of transit motivates relocations, while dissatisfaction with the accessibility of the workplace, shopping facilities and leisure activities for young people are important reasons for urban residents. The results suggest that dissatisfaction toward specific travel-related characteristics of a neighborhood has a significant, though small influence on the desire to leave the current neighborhood but the more general ‘dissonance’ does not. We draw conclusions for transport policies in urban and non-urban areas.

ABSTRACT. Given the wide scope of integrated urban models (IUMs) to simulate households/individuals’ location and travel-related choices, and their interactions, IUM presents a fitting platform to test the impacts of COVID-19 since the pandemic has also impacted many domains of our life including travel and housing market. This study implements and tests the applicability of the residential relocation module of an agent-based IUM during the COVID-19 pandemic. The proposed IUM is an event-based model adopting a hybrid of continuous time and discrete time microsimulation technique. The behavioral models of this IUM are also consistent with the hybrid technique – e.g., hazard-based duration and logit models have been implemented to simulate residential mobility and location choice decisions respectively. The IUM has been deployed for the entire population of the Central Okanagan region of British Columbia, Canada for the years of 2011-2021. A multi-year validation exercise has been performed and results suggest a reasonably satisfactory representation of the observed behavior in the simulation environment. Results further indicate a growing increase in housing prices for single-detached dwelling units in suburban neighborhoods during the pandemic. This study adds the capacity to IUMs to test for unprecedented socio-economic shocks such as the COVID-19 pandemic.

ABSTRACT. For decades, the phenomenon of urban sprawl has been increasing. In conjunction to focusing on car dependency to reduce the footprint of increasing daily travel distances, it would be more sustainable for cities to propose strategies that affect the spatiotemporal structure of travel, for example by addressing residential location. Understanding how households choose where to live is therefore essential to help planners encourage people to select their place of residence more wisely. This research aims to define the characteristics of households willing to move, and to examine the reasons given for this choice, using data from two Montreal CMA-wide surveys on changes in habits caused by the Covid-19 pandemic. Results show that the household typology has a strong influence on relocation reflection, with young couple households having a lower probability of wanting to stay in their housing than other household types. Proximity to services in the area of residence is also found to have a strong impact on willingness to relocate, good proximity to secondary education and employment fostering the desire to relocate, and good proximity to groceries supporting staying in current housing. Results show that getting closer to nature is the most common reason why households want to relocate.

ABSTRACT. A system transition from a fossil driven mobility sector to one that is carbon neutral will have substantial impacts on the energy efficiency. A widespread concept to look at energy in an industrialized economy is the EROI concept (Hall, 2017). This concept looks at the energy that needs to be invested to gain access to a certain amount or form of energy. Historically especially oil and oil-based fuels had very high EROI values. For the mobility sector one also has to address that the energy in the fuel source is not the relevant service the system provides. Against this background the presented paper introduces a variation of the EROI concept and looks at mobility return on energy investment (MoROI). Build on this concept, a model to simulate a change from a fossil-based mobility system to an electric-based mobility system is introduced, which, in turn, allows for a calculation of the MoROI value for each step of the transition process. From these results the energy investment needs for both systems can be calculated as well as a break-even energy need for a theoretical CCS based carbon removal from fossil vehicles still in in use at each step of the transition.

ABSTRACT. This bibliometric review presents cumulative knowledge of the research on electric vehicles systematically. Based on bibliometrics through content analysis and keyword analysis, this study quantitatively analyses and evaluates the prior research on electric vehicles in the last five years. The research looks at 2393 peer-reviewed journal articles for five years ranging between 2017 and 2021. The study uses co-citation analysis, page-rank analysis, content analysis, and publishing trends to determine the influential works and structure of the ever-emerging area, consequently identifying research gaps. A clustered analysis was performed after identifying the most prominent journals, authors, nations, articles, and themes. Electric vehicles, related infrastructures, barriers and motivators of adoption, and the respective impact of interventions, are the key subjects discussed. Finally, quantitative research provides the most recent evolving trends in electric vehicles to improve electric vehicle performance. Following the suggested prospective research areas, a conceptual framework has been created that depicts the entire picture. This is the first research to look at electric vehicles in depth from an interdisciplinary approach. This research will aid policymakers, regulators, and academic academics in understanding the intricacies of electric vehicles and identifying necessary resources.

ABSTRACT. Discontinuing low-carbon technology ownership impacts sustainable development goal to combat climate change. This paper investigates the proportion of U.S. plug-in electric vehicle (PEV) owners who discontinued PEV ownership by disposing their PEV and buying a non-PEV on their next purchase, termed PEV discontinuance. Using a survey of 190,000 new car buyers, we find a 37% discontinuance among PEV owners (N=1077) who disposed their PEVs, indicating the PEV transition may take longer than anticipated. PEV discontinuance is more likely among younger men with slightly lower income and education. Brand loyalty and leasing reduces this likelihood, implying automakers could design targeted brand loyalty and leasing programs to lower discontinuance. Driving range, charging, and cost are barriers to adoption, but the PEV discontinuance group is more concerned about charging than cost. The trade-off between subsidizing PEV price and charging infrastructure needs reconsideration; the former might accelerate adoption, whilst the later could sustain it.

ABSTRACT. Surging electric vehicle (EV) adoption concerns the energy sector due to challenges in balancing the supply with electricity demand. In this context, electricity demand management strategies can be used to reduce potential grid strains posed by EV charging. This study investigates consumer preferences for smart charging technology and control (user-managed or supplier-managed) and responses to progressive ToU tariff discounts in guiding change of EV charging time to late-night and around midday when there is peak solar energy generation. The results show that activity-travel behaviour plays an important role in the responses to electricity demand management. Consumers willing to change EV charging time are likely to have more flexible schedules, while time-constrained individuals seek the practical benefits of smart charging. Current EV owners have a higher propensity than potential EV adopters to choose supplier-managed charging and charge around midday in response to ToU tariffs, indicating that trials with current EV owners may potentially overestimate the acceptance of such strategies. While monetary incentives can successfully shift an important share of consumers to night charging, these incentives are not very effective in shifting demand to midday. Synergy in the formulation of transport and energy demand strategies may be necessary to facilitate such shift.

ABSTRACT. Fast charging stations (FCSs) can facilitate the uptake of Electric Vehicles (EV), but their installation requires significant investments affecting their profitability. An optimal determination of charging locations and capacities based on associated costs can help to provide infrastructure efficiently. As initial FCSs affect installations and costs in later years, a strategic infrastructure development plan over multiple years is required to expand the infrastructure to satisfy the charging demand of a growing EV fleet, while pursuing the goal of minimal costs. Based on former work, a model for the investment-optimal allocation and sizing of FCSs over multiple years (including costs for grid connection) is developed. For the first time, a multi-periodic capacitated Arc-Cover Path-Cover formulation with an investmentoptimal objective is proposed and applied to New Zealand. The results are analyzed with respect to the locations and sizes of FCSs, the impact on the coverage of traffic flows, and the related trends over time. They indicate that FCSs are to be located along highly trafficked corridors in densely populated regions for being applied profitably. The chosen station locations have below-average installation costs and are capable of covering high shares of EV traffic on inter-regional and highly frequented routes.

ABSTRACT. The driving cycle is one of the main inputs of vehicle emission modeling to estimate emitted GHG. The variability of driving cycles coming from fluctuations in weather parameters is one of the primary resources of uncertainty in vehicle emission estimation. This study aims to identify and determine an optimal number of driving cycles representing driving patterns in various weather conditions. A multivariate multiple regression model is developed to determine the essential weather factors that affect critical patterns to achieve the desired objective. Then, similar weather conditions are identified according to these factors and using unsupervised machine learning. Then, two driving cycles were constructed for all weather types, one for weekdays and one for weekends. Afterward, descriptive analysis and similarity matrix are employed to determine how similar the generated driving cycles are in different weather types. Finally, 15 driving cycles are identified to represent appropriate driving patterns in all driving conditions.

ABSTRACT. Estimation of energy consumption and GHGs emissions is critical for assessing the effectiveness of traffic management strategies. Significant correlation between energy consumption and CO2 emission has been detected in gasoline vehicles. It has also been considered in MOVES and CMEM using temperature-related correction factor. Such impact differs across engine operating conditions, which corresponds to different air inflow rate. In this study, a fuel consumption model and a temperature adjustment factor model were proposed to quantify these interactions based on OBD data from 252 gasoline light-duty vehicles in Beijing and Shanghai collected on summer (July), fall (October) and winter (December). Strong variation of energy consumption impact from temperature were observed over driving conditions. At the same level of speed, the fuel consumption first decreases then increases with the raising of temperature. With the increase of speed, the influence of temperature on fuel consumption becomes more severe, especially when speed is over 90 Km/h, energy consumption rate increases exponentially when the temperature becomes extremely low. Ignoring the influence of temperature can cause an error of 8% in fuel consumption estimation. The study can help better understand and quantify temperature impact on fuel consumption of gasoline vehicles under various operation conditions.

ABSTRACT. Remote sensing (RS) is an ideal mechanism by which to identify the ‘high-polluting’ in-use vehicles on urban roads as it allows for the recording of thousands of unique vehicles emissions, and these can be used to identify the vehicles with high emissions. This paper presents two models - top 5% high emitters and support vector machines (SVMs) - to determine the vehicles within the fleet which are high emitters in key pollutants. These models account for the vehicle specific power (VSP) of the vehicle and its speed in order to compare distance-based emissions factors. These emission factors are then compared to the relevant Euro standards to understand the effectiveness of said standards. The models are found to be effective in determining both the highest overall emitters within the dataset but also those which produce ‘relative’ high emissions, these are the vehicles which produce a high volume of emissions for vehicles within their given Euro class. The performance of the models is then compared so as to identify which model is most suitable for ‘high-polluter’ detection. The findings from this research could form the basis for the introduction of low-emission zones in air pollution hotspots in urban areas.

ABSTRACT. The study investigates the impact of vehicle characteristics and predicts the emission of CO and NOx. Direct emission measurements were collected from the exhaust pipe of 88 vehicles through gas analyzers. The vehicle mix comprises motorcycles, tricycles, personal cars, minibuses, large buses and trucks. The emission levels of CO and NOx were analysed statistically to establish an emission model equation based on vehicle type, engine type, age of vehicle and vehicle purchase status. The findings revealed that personal cars and minibuses are prevalent in petrol engine emission of CO, while large buses and trucks are major contributors to the emission of NOx in the diesel engine. Further analysis shows 66 percent of the total vehicles are older than 10 years, and consequently increased, the emission levels by 65%. The regression model showed a statistically significant relationship between the CO, NOx emissions, vehicle type, engine type and age of vehicles (P <0.05). About 60% of petrol and 75% of diesel vehicles exceeded the emission permissible limit. The study shed light on the hazard of age and old vehicles, engine types and the need for a gradual overhaul and adoption of low-carbon or electric vehicles in developing African cities.

ABSTRACT. Autonomous IWT will become reality only if the technology implementation will make a viable business case, which means the revenue will surpass the costs. However, in an ecosystem with multiple actors, benefits and costs can be distributed and shifted to different actors. In the case of split advantages brought by autonomy, the solution is to establish a different allocation of benefits, to allow every actor to gain a positive outcome. The distribution is achieved through contracts. For this reason, understanding how costs and benefits are allocated under charter parties for conventional barges helps in proposing solutions to commercially introduce autonomous barges.

ABSTRACT. Public transport is an important contributor to sustainable and smart cities. It is important for the general population to fulfill daily needs. Especially young and elderly people depend on the public transport system. Sustainability has different aspects however; a good utilization of public transport is usually considered a sign of sustainability. Achieving good utilization is especially challenging in rural areas. Low population density and a large area of operation are making it expensive to provide public transport with sufficiently attractive level of service. It is very important to avoid low utilization, because empty rides are both costly and not sustainable. A common approach to achieve both cost-effectiveness is demand-oriented public transport. Trips are requested in advance and vehicle only operate in areas where they are needed and when they are needed. Empty rides are therefore avoided. This impose new challenge for usability, once again especially for elderly people. In "Autonomous public driving" (emoin), a subproject of the project RealLabHH, such a system was implemented and tested in the region Hamburg-Bergedorf. Hamburg-Bergedorf is a suburb of Hamburg. This paper is going to describe and explain some of the technical challenges and the steps involved of this project.

ABSTRACT. The following paper presents a methodology we developed for addressing the case of a multi-modal network to be implemented in the future. The methodology is based on a simulation approach and presents some characteristics that make a challenge to be verified and validated. To overcome this limitation, we proposed a novel methodology that implies interaction with subject-matter experts, revision of current data, collection and assessment of future performance and educated assumptions. With that methodology we could construct the complete passenger trajectory Door to door in Europe. The results indicate that the approach allows to approach infrastructure analysis at an early stage to have an initial estimation of the upper boundary of performance indicators. To exemplify this, we present the results for a case study in Europe.

ABSTRACT. Currently, traffic and mobility engineering research focus mainly on the analysis of road use based on network flows as well as the dimensions or the available space for circulation of existing means of transportation. (HCM, 2017). In other words, levels of service are evaluated based on road characteristics and their interaction with vehicles.

This kind of evaluation used in road impact research (and based on road capacity, travel times and vehicle speeds in the area) points out to the variables that are susceptible of improvement (number of lanes, pavement condition, control elements such as traffic lights or access feathers). Such variables are the foundations for projects aiming to mitigate the impacts generated by new projects.

Nowadays, however, the search for evaluation means that consider gender relationships in public spaces are starting to tear down paradigms in the engineering field while seeking to have a more global and integrating perspective that offers results (not only of vehicle dynamics but of the human relations that are generated in said space).

Mobility will be sustainable only if in urban and regional planning, gender equity, affordability and accessibility are taken as principles.

ABSTRACT. We analyze the relationship between various elements of walkability and real estate transaction price with a hedonic approach to understand which factor influences the real estate transaction price. We use much detailed and directly measurable data of real-estate transaction price and walkability based on City of Vienna government open data, which became recently available. With this large dataset, we analyze the relationship with several subsets of the samples, e.g., stratified by approved building height (low or high) and or with certain land use types e.g., residential or industrial/commercial, to understand context-dependent importance of different walkability elements reflected in the real-estate transaction price. The valuation of walkability is potentially different in different urban contexts. The pedestrian-friendliness in a near proximity, such as the ration of walkable pavement, greened pavement, and beautified pavement, are more nuanced in low-rise and residential areas than high-rise and industrial or commercial areas when it comes to land transaction prices. A similar conclusion can be drawn for the trees, too. This may open up a potential for financing publicly funded walkability improvements if such additional value can be monetized as e.g., property taxation or property transaction taxation is introduced.

ABSTRACT. This study utilizes Halifax Sustainable Transport Survey to determine the EV adoption in the next five years. The methods used in this study include: 1) Binary Logistic Regression (BLR) model identifies the potential parameters which are related to adopting EV, 2) Ordered Logistic Regression (OLR) model captures the importance level of installing Electric Vehicle Charging Station (EVCS) based on individuals’ socio-demographic characteristics, and vehicular information. Both age groups, 25 to 34 (1.108) and 35 to 44 (1.265), portray a positive relationship with EV adoption. For shorter travel distances, the likelihood of adopting an EV is higher than for longer travel distances. Inadequate charging stations for EVs, may be a plausible reason for not being interested in longer travel distances. Similarly, individuals between 35 to 44 are more highly interested (0.068*100% = 6.8%) in the installment of EV charging stations. Those who work daily (1.054) and 3-4 times per week (0.915) show positive interest in charging station. Furthermore, using the interventions obtained from the model results, policymakers can ensure an equitable and robust sustainable transportation infrastructure, better accounting for a healthier environment for the Halifax residents.

ABSTRACT. Active transport, which was side-lined as an option due to the intense rate of motorization over the years, again came to the forefront as a focus area with the National Urban Transport Policy 2006. The disruption created by COVID-19, however, has significantly changed people’s perception of walking and biking, leading many decision makers to rethink the role of active transport. However the current city level transportation studies are more based on motorized oriented approach which is also one of the main reasons to declining the share of active transport usage in the urban areas. It is very unfortunate that city officials have set maximization of vehicle-km as their target, thereby ignoring the mobility of the majority of the city dwellers. The existing practice of active transport infrastructure planning is bias towards motorized infrastructure and do not comprehensively take into account the behavior aspects of active transport users while planning for them. In this context the present paper highlights the need to revisit the present approach for preparation of City Mobility Plans (CMPs) with focus on scientifically derived demand assessment of active transport users and its related infrastructure to achieve a sustainable mobility environment in cities.

ABSTRACT. Among Montreal pedestrian streets summer projects in 2021, two locations (Mont-Royal Avenue and Wellington Street) have set up a pilot project considering the cohabitation between pedestrians and cyclists by authorizing cyclists to stay on their bike at a slow pace while it’s forbidden on other pedestrian streets. This paper aims to document this cohabitation at three specific sites (two where cyclists are permitted and one where they are not) based on observations of cyclist's behaviours and their interactions with pedestrians. Direct observations of cyclists (n=1371) were conducted through a grid regrouping items about cyclist characteristics, actions and interactions with a pedestrian. The results show that cyclists' behaviours are fairly predictable and one third of them were involved in an interaction with a pedestrian. For the small number of cyclists who engaged in unsafe behaviours, young males and other vehicle types (i.e., Segways, rollerblades, cargo bikes, etc ) are overrepresented.

ABSTRACT. Facing the challenges of motorised traffic, many cities around the globe started implementing measures to transform their urban transport systems. One of the major challenges for the success of adequate policies is not only their effectiveness but also whether they are accepted by city residents. With a quantitative case study in four neighbourhoods in Frankfurt am Main (N=821), this article investigates the acceptability of three measures: (i) parking management, (ii) the conversion of car lanes into cycle lanes and (iii) the closure of an inner city arterial road to car traffic. The results show a surprisingly high acceptability for all measures if the benefits for local residents are tangible. Thus, successful policy packages may combine push measures with either pull measures, as suggested frequently in the literature, or with improvements for non-car travel options (e.g. re-using former car-parking spaces for non-transport purposes, such as greenery or seating areas). Furthermore, the perceived effectiveness, daily travel practices and intentions to reduce car use, the built environment and, to a lesser degree, socio-demographics explain differences in acceptability by population group.

ABSTRACT. Electrification of vehicles is expected to substantially reduce greenhouse gas emissions and contribute to achieving climate targets. The Irish government have introduced several policy incentives to encourage purchasing and using private electric vehicles (EVs). This study aims to inform policymakers about the equity impacts of measures supporting EV uptake by estimating how many Irish households can avail of policy incentives for EVs. To receive the benefits, households must be able to afford an EV. The four scenarios are designed, and the spatial distribution of numbers is analysed across the country at the electoral division level. The results show that incentivising the purchase of even a small EV presents a regressive redistribution of resources to the wealthier segments of society. It is found that at least 38% of Irish households would not be able to afford an EV if taken a loan for a typical repayment period offered by lenders. The governmental support for EVs prioritises higher income segments of society and, because of this, contradicts a sufficientarian approach to social justice in which all individuals are provided with a threshold level of basic capabilities. Investment in sustainable mobility seems a more inclusive alternative for transitioning to low-emission transport.

ABSTRACT. The research focus of this paper is on the inclusion of disabled persons in the public transport system with an emphasis on their full autonomy. Several models in operational research treat this problem, such as transport on-demand with its varieties, the shortest path problem, even though they are often understood to focus on public transport rather than accessibility to the public network itself. Providing a full service to persons with disabilities in a public transport system is a very long process, which involves many participants. The diversity of the needs of disabled persons and the various interactions between these needs raises the level of complexity behind this process. To explore this problem, we used a decision-aiding approach. First, we use a multidisciplinary approach to develop a matrix of the different fields of decision. Second, the decision-aiding process proposes a comprehensive analysis, which gives the ability to choose at any time the suitable model for the inclusion of disabled persons. Third, we put forth a scheme of the relationship among existing optimization models, depending on the public network information.

ABSTRACT. COVID-19 brought public health challenges to the public transport system throughout the world. As a result, a range of response measures were implemented to ensure the safety of passengers while maintaining a functioning system. This paper explored the responses of public transport agencies in New Zealand’s metropolitan cities (Auckland, Christchurch and Wellington) to the COVID-19 pandemic by understanding the physical and communication measures that have been implemented in the last three years. We analysed public transport agencies' websites to understand the response measures implemented, including the accessibility of COVID-19-related information, and the communication of information via the website and social media platforms. The results show that 13 service responses were implemented across the three public transport agencies, with Auckland implementing the most measures. Seven infrastructural responses were implemented, with Christchurch implementing all seven. Wellington was found to be the public transport agency that utilised social media the most during the pandemic. The website accessibility findings suggest that the more accessible a public transport agency’s website was, the less information was present. The research concludes that all three public transport agencies in New Zealand performed reasonably well and were able to maintain a safe and responsive public transport system.

ABSTRACT. As, in most countries, electricity cannot be efficiently and practically stored at a systemic level, charging EVs during peak hours implies that additional energy has to be generated (relying almost exclusively on fossil sources) to cover the additional demand during that time window. This paper reports the results of an SP-study, in which EV-owners were confronted with the option of charging their EVs at home (for a fixed known price) or at a publicly accessible charging station with charging price variability (as well as other features of EV charging). The results of the behavioral experiment show that EV-users exhibit a high willingness to accept alternative compensations for not charging EVs during peak-hours and that small monetary incentives as well as shorter access times, a guaranteed charging place, or fast charging could all efficiently promote a shift in the charging patterns towards a more sustainable behavior.

ABSTRACT. In Japan, the mobility functions of principal arterial roads are hindered by lined-up roadside facilities and densely located signalized intersections. Therefore, it is necessary to consider a functional hierarchy of road networks, based on the structure and traffic operations of each road. This study focused on evaluating the utilization rate of road hierarchy according to trip length as an index to express the hierarchical utilization status of the road network. To accomplish this, we proposed a four-level method for the evaluation of the functional hierarchy of road networks based on the derived index values. As a case study, we calculated the degree of hierarchy for the road networks in northern Mie and western Shizuoka. The results showed that the current evaluations of the functional hierarchy in these regions were low, and that introducing mid-level roads was necessary to improve the current situation.

ABSTRACT. Current European transport models following the classical four-step approach are not suitable for analysing the traffic volumes on concrete inter-regional road infrastructure, as they consider only about 10% of the trip demand with passenger cars. Due to runtime problems, these models are limited to operation at the NUTS-3 level. This level comprises 1,500 regions for Europe with an average diameter of about 50km. Application of these models at a higher spatial resolution, such as the LAU-2 level, is not possible, as the runtime increases significantly with the number of travel zones. In the HIPAT model, this obstacle is overcome by an innovative concept operating at different hierarchical levels. Hence, the HIPAT model can be applied at large scale for 150,000 travel zones without runtime problems. This is demonstrated by a prototype implementation for a case study that handles 33,000 travel zones in two minutes. In addition, the limitations of NUTS-3-based travel zones for transport modelling are shown: 94.6% of the trips are shorter than the average diameter of the travel zones (50km) and are therefore not correctly represented by the model. Smaller travel zones decrease this number and provide a better basis for analysing infrastructure policies and, ultimately, for decision-making.

ABSTRACT. Effective tourism crises and disaster management can help mitigate both human and financial damages. However, due to the lack of proper preparation and management foreign tourists remain highly vulnerable. Foreign tourists differ from residents and local tourists in their language abilities, knowledge of possible dangers, and familiarity with the geographical layout of tourist regions. In this study, an agent-based evacuation model was developed to model the evacuation behavior of foreign tourists, residents, and local tourists during a tsunami. Furthermore, the influence of information provision and soft and hard countermeasures on the evacuation rate and time of various groups was investigated. The tourist area of Minato Bay in Osaka was used for conducting the case study. Based on the results of the simulation model and scenario analysis, we can infer that there are disparities in the evacuation behavior of foreign tourists and residents, particularly regarding arrival time at shelters. While most residents can reach shelters without difficulty, tourists, especially foreign tourists, confront more obstacles that delay their arrival. As a policy implication, a comprehensive plan which considers information provision in multiple languages in addition to the increasing shelter capacity is necessary to support the foreign tourist evacuation.

ABSTRACT. This study empirically analyzes the impact of COVID-19 on inter-urban business trips (IBT) using data collected from an online questionnaire survey. A total of 4,700 participants, who were employed in Japan from February 25–27, 2022, participated in the survey. The questions included IBT frequency before and during the pandemic, changes in organizational decision-making rules regarding employees’ IBT during the pandemic, expected IBT frequency after the end of the pandemic, their personal attributes, and which organizations they belong. The survey results show that many respondents reduced IBT significantly during the pandemic, and the post-pandemic IBT frequency is not expected to return to the pre-pandemic level. Binary logit models regarding the firm’s choice to approve employees’ IBT are estimated with the data, revealing that large-scale firms are more likely to prohibit their employees’ IBT than small- and medium-scale firms during the pandemic. Regression models regarding the changes in IBT frequency found that the experience of using video conferences negatively affected the IBT frequency during the pandemic, while its effect was inconclusive in the post-pandemic period. This may be because businesspersons familiar with video conferences are likely to prefer new styles of IBT combined with leisure and tourism rather than traditional IBT.

ABSTRACT. In this historical context, the public transport sector faces various challenges: urbanization, automation process, diffusion of "sharing mobility" and the affirmation of new mobility paradigms (e.g. Mobility as a Service). Technological innovation, guided by the reference regulation, is the solution to many of these issues: this paper intends to analyze the Italian case study in order to understand the state of the art of technological innovation introduced by public transport authorities and how regulations and political measures affect it. To this end, the top 10 PTAs for passengers in 2019 were investigated and, through web research and analysis of the financial statements, 15 different innovations were identified. The results show that, in order to increase the level of technological innovation in public transport and pursue objectives of economic and environmental sustainability, a market open to competition and a favorable and stimulating regulatory framework are a necessary condition.

ABSTRACT. Cycling-related grassroots movements are recognized as key to turn cycling initiatives into reality. However, little is known about how grassroots movements contribute to structural changes for the promotion of cycling. This paper bridges this gap by answering the question if local cycling-related grassroots movements are an essential driving force for implementing cycling policy. Based on four German cities, the development of cycling policies over the last two decades is analysed, paying special attention to the role of the “Radentscheid”, a cycling-related citizens' initiative. A three-step mixed methodological approach is used. Containing an exploratory document analysis, expert interviews with public authorities and “Radentscheid” members and data around the development of cycling use and satisfaction. The results show that the process might be structured in three stages: (i) Commitment, cycling promotion is put in political agendas. (ii) Imbalanced growth, characterised by little progress in cycling policies, a sharp increase in cycling use and decreasing satisfaction with cycling. (iii) Institutional adaptation, cycling becomes a central issue for local governments due to pressure from the grassroots movements "Radentscheid". In Germany, the “Radentscheid” movement is proving to be the decisive factor for significant progress in local cycling policy. The paper closes by discussing policy implications.

ABSTRACT. Transit-oriented development (TOD), characterized by a high and mix development around public transport stations, is gaining traction as a sustainable way to support the use of public transport for regional trips and active transport for local trips. To support integrated land use and transport planning, several TOD typologies have been developed, with a focus on land use and transport characteristics, and more recently walkability. While TOD aims to support active modes, including cycling, bikeability has been left out of TOD typologies. To fill this gap, this study seeks to enhance actual TOD typologies by combining indicators related to the cycling environment with traditional land use and transport indicators. Using Montreal as a case study, fourteen indicators are generated to develop a TOD typology oriented on bikeability and the 114 public station areas are grouped into seven distinct clusters. The results demonstrate that the addition of a bikeability criteria to the TOD typology helps discriminate the different types of station based on their current bikeability and bikeability potential. The proposed framework enables recommending and prioritizing targeted interventions to station development. This study is of relevance to planners and researchers aiming to integrate cycling in the development of TOD.

ABSTRACT. Cities across the world want more sustainable urban environments and transport systems. Within these aspirations, improving the walking and cycling environments and reducing accident injuries would serve to support more sustainable cities. Pedestrians and cyclists are disproportionally often the victims of road accidents. Understanding the factors that influence the severity of injury, can greatly contribute to several societal commitments. Research in islands are particularly important due to the increase in car dependence across a number of island states and the increasing risk exposure for pedestrians and cyclists. This study examines the pedestrian and cycling accident injuries in Malta using a database of injuries between 2005 and 2021 and analyse, using a Poisson panel random effects model, the relationship between local population, urban land use and driving behaviour, and how they affect injury severity at local level. Furthermore, the study presents the case study and describes injury trends over time. Results show a link between slight and grievous injuries and commercial, health and industrial activities. Links are also found with population. Speeding is only linked to grievous injuries. Fatal accidents are related to the location of industrial activity and population. The paper concludes with some recommendations to improve road safety conditions.

ABSTRACT. Biking to school reduces congestion and air pollution compared to school drop-off by car, improves the overall health of children. However, most streets are considered too dangerous by the parents to let their children ride on them. This paper uses the Level of Traffic Stress classification defined by Mekuria [2012] that ranks each street based on the stress felt by the cyclists due to motorized vehicles. This classification allows to identify a low-stress network, suitable for children. Using a Geographic Information System, an Accessibility Index is calculated for each school, based on its low-stress bicycle service area. The analysis applied to the Island of Montreal shows that 76% of the schools have an Accessibility Index below 1%, meaning that children living in less than 1% of the street network around the school can reach it safely by bike while using a low stress route. Improving the school’s accessibility requires both local improvements to connect schools to the existing low stress network, and a general connectivity improvement of the highly fragmented low stress network. Transportation planners can use this methodology to evaluate the current accessibility around schools and to select network improvement projects that increase the most children’s access to schools.

ABSTRACT. This research investigates general public preferences towards travel modes during the COVID-19 post-vaccination times. First, a questionnaire survey is conducted in Dhaka, Bangladesh, to gather information on people's socio-demographic characteristics, travel choices before and during the pandemic, and attitudes towards public transit, active transport, and personal cars. Next, three ordinal logistic regression models are developed to explore how mode preferences vary across socio-demographics, travel characteristics, and risk perceptions. This research identifies factors that contribute to commuters' travel mode preference and factors that act as deterrents. Analysis reveals that there will be noticeable shift from public transport to private car and active transport. People may consider relocating closer to their workplaces to walk or bike there. Individuals who used a private car before vaccination may continue to do so after vaccination. Results also suggest that use of food delivery services, ridesharing, and working from home significantly affects travel mode preference. Individuals who never used ridesharing services are more likely to prefer walking and bicycling after vaccination. The outcomes of this study are expected to assist transport policymakers in the Global South in understanding COVID-19's long-term influence on mode choice behavior and help in developing pragmatic policies to promote sustainable travel habits.

ABSTRACT. This article aims to analyse the pandemic's impact on Colombia's seven existing BRT systems. From a sample taken in the seven cities (N=1486), through online surveys conducted in mid-2021, we estimated multinomial and ordinal logit models to explain the use of BRT systems before and during the pandemic. Subsequently, we estimated a hybrid discrete choice model, incorporating several individual perceptions about the service to analyse the intention of BRT use after the pandemic. Modelling results confirmed that the pandemic had a profound impact on mobility behaviour, with a shift away from mass public transport such as BRT or bus and a substantial increase in the use of single transport modes, which include cars, cycling, and walking. As we show in this work, the intention to continue using the BRT service after the pandemic depends on not only people's occupation, socioeconomic situation, spending on transport before the pandemic, and access to private vehicles, but also the perception of contagion risk and service quality perception before and during the pandemic. The BRT demand is not expected to reach pre-pandemic levels when the virus takes a back seat, which will exacerbate the financial unsustainability of this transport system in the country.

ABSTRACT. Indian cities have varied densities, incomes, land-use patterns and trip distances. They are now experiencing rapid urbanization, thus amplifying the demand for efficient transportation systems. The transportation system in developing countries is often shabby. A rapid mass transit system is a dynamic solution for efficient, inclusive and environmentally sustainable transportation. However, the wide disparity between metro cost and its ridership has prompted doubts about the efficacy of metros. The allure of metros has led them to be replicated in cities without a thorough feasibility study, thus resulting in a mistaken investment which only adds a superfluous gloss to the efforts to improve public transportation. This paper expresses the need to invest in metro projects for sustainable mobility. It describes how a cohesive system can be created for financing, planning and management of a capital-intensive project that poses several challenges. It also explains the need for metro rails in cities with high travel demand, gaps between policies and stakeholders, differences in policy and actual practices and other challenges in the progress of such projects. The measures suggested herewith are aimed at increasing metro rail ridership and thereby improving the quality of life in Indian cities.

ABSTRACT. Regions with urgent rail infrastructure demands have difficulties in developing reasonable railroad network construction plans when the megalopolitan spatial structure is ever-changing. Previous studies seldom investigated the factors influencing the railway passenger flow from the perspective of ‘multi-flow space’, which can be reflected by economy, industry, corporation, mobility, patent, and railway passenger flow data. In this study, a social network analysis method is utilized to evaluate the spatial distribution and correlation among the multi-flow elements, taking Yangtze River Delta megalopolis in China as the study area. Results show that, economic, industry, and corporation flows are highly correlated to the railway passenger flow, implying their importance in railway network planning. For different industry segments, these three industries, namely commerce, technical services, and financials, contribute most trips to the railway passenger flow. Besides, regional railways need to be supplemented to meet the travel demand between adjacent counties. In the aspect of connection priority, the lower-level nodes should be connected to the adjacent higher-level nodes, rather than directly to the central city of the network. Our findings provide implications for policymakers in developing countries to plan railroad networks reasonably and effectively.

ABSTRACT. There is a long tradition of accessibility research in Latin American cities, with an increasing interest of frameworks from distributional perspectives. However, most accessibility metrics deployed in research and practice do not consider the dimension of (dis)utility, which resonates more clearly with mainstream transport decision-making and planning. This paper contributes to debates about the use of utility-based measures as inputs for accessibility assessment of transport investments in the Global South, using choice modeling and its potential as a bridging language between socially nuanced and economics-driven planning. This paper uses mixed revealed and stated preferences data from Bogotá, Colombia. Then, it uses a logsum accessibility metric to estimate the differentiated impact of a set of infrastructure interventions on the accessibility of residents with different socioeconomic conditions. The logsum accessibility metric analyses future innovations and structural additions to Bogotá's public transport, reflecting their effect on accessibility and consumer surplus in the next 20 years. The proposed approach captures the benefits derived from the opportunity locations and transport infrastructure improvements, which has relevance for debates about transport policy and practice in similar urban contexts in the Global South. These accessibility gains could be assigned a monetary value to include in project cost-benefit assessments.

ABSTRACT. Due to the high complexity of freight transport on goods distribution activity, information about preferences and perceptions for each stakeholder involved has become essential, especially because their interests are often divergent and conflicting. The main problems related to road freight transport are congestion, poor road networks and inadequate loading/unloading operations/. These raises concern to conduct a study on assessment of project stakeholders’ management on sustainable freight transport logistics in Lagos State. Population of the study comprise 5000 truck owners registered COMTUA. Convenient and Purposive sampling technique were used to select 265 respondents. Out of 265 questionnaires distributed 160 usable questionnaires were returned, representing 60% response rate. Descriptive statistics was used to analysed the data collected, which was presented using charts. The findings of the study shows that proper identification of stakeholders in freight transport logistics will undoubtedly help in the formulation and implementation of policies and measures that will effectively, efficiently enhanced freight movement and promotes special attention needed for freight traffic planning and management in ensuring efficient distribution of freight and promotes profitability of freight transport logistics in Lagos state. The study therefore recommended that stakeholder’s involvement should be given priority in freight transport logistic planning.

ABSTRACT. Assessing the service quality of transit systems has gained a huge importance in recent years. However, commuters’ satisfaction plays a significant role in determining the service quality of a transit system. This study attempts to examine the relationship of different attributes on the overall satisfaction of commuters using existing regional transit systems operated between Delhi, Gurugram, Rewari and Alwar districts of the National Capital Region (NCR), India. A questionnaire-based survey is used to capture the satisfaction of 781 respondents over 27 attributes using five-point Likert-type scale. The factor analysis is performed to determine the latent factors explaining the overall satisfaction of regional transit systems and are further used to determine relationship using Structural Equation Modelling (SEM). The result showcases the relationship of the attributes to the overall satisfaction of commuters and the relationship between different latent factors. Information at station is the most satisfactory attribute while clean toilets at station is least satisfactory. Three latent factors developed in the model have a positive effect on the overall satisfaction of the commuters. Vehicle Factors have a direct while the other two latent variables have an indirect effect on the overall satisfaction.

ABSTRACT. Transportation agencies in developing countries lack means for monitoring real-time traffic conditions. Application of Intelligent Transportation Systems (ITS) in data collection is accompanied with financial and technical constraints. The increased use of crowdsource data shows the potential of improving traffic data collection in developing countries. This study aims to test the suitability of crowdsourcing in collecting comprehensive traffic data and to display performance measures of roadway facilities. The study was done in one of the major arterials in the City of Dar Es Salaam located in Tanzania. Crowdsource data was obtained by introducing virtual sensors on the roadway segment. The virtual sensors collected data using the customized Google API. The virtual sensor output provided the travel times and speeds in the segments. The travel time and speeds represented the traffic conditions at every 5-minute interval. Crowdsourcing is expected to benefit developing countries due to its low installation and maintenance cost.

ABSTRACT. As sea levels rise, there has been an increase in research focused on the protection of shoreline infrastructure and transportation systems that may increasingly suffer from permanent capacity and accessibility reduction. This paper focuses on Abu Dhabi, UAE, a city vulnerable to inundation due to its insular geography, aiming to identify protection strategies that will minimize transportation network delays. The model considers hydrodynamic interactions and traffic assignment. The results show some shoreline portions are critical, and their protection leads to less congestion, while there are combinations of shoreline protection that worsen the congestion levels. The results also show that in some cases, the marginal effects of protecting one precinct may yield a better reduction of congestion than multiple other precincts. This research can provide a general framework for the protection of transportation infrastructure against sea level rise.

ABSTRACT. This article proposes modelling the service quality offered by signalized intersections, nodal focuses in a transportation network, from motorized two-wheeler users’ perspective in the urban Indian context. All conceivable geometrical, traffic, and built-environmental data were gathered from a variety of signalized intersections situated in large cities across various Indian states. In addition to this, responses from almost 2500 on-street motorized two-wheeler users were obtained in order to get sociodemographic data and overall satisfaction scores. With the aid of various statistical modelling approaches, namely multiple linear as well as non-linear regression, ordered logit and, probit models, accurate but less erratic motorized two-wheeler level of service (MLOS) models were developed taking into account these six explanatory variables. In the current study, the ordered logit model showed astounding likelihood efficiency with (R2) value of 0.861. The exhibited characteristics of the model revealed that the impact of peak hour traffic volume, average control delay, and pavement quality index had a significant impact on the MLOS of signalized intersections. The outcomes of this work would, to a large extent, assist transportation planners and architects in analyzing the operational efficacy of signalized intersections and in formulating effective remedies for the better management of motorized two-wheeler traffic.

ABSTRACT. In order to transform cities into more liveable, safe, and sustainable places, we must shift our mobility paradigms. As one auspicious concept amongst urban transportation facilities, para transit modes facilitate urban transportation into small, efficient, and affordable vehicles that are flexibly operated on any infrastructure i.e. specifically motorized three-wheelers being the most prominent subject vehicle of para-transit mode in India, yielding the potential to make public transit more convenient, affordable, and sustainable all at once. Considering this, service quality prediction for motorised three-wheelers at urban roadways is analysed involving the data collected from 50 road segments from 5 cities. Adaptive Neuro Fuzzy Interface System (ANFIS) is used for the development of Three-Wheeler Level of Service (3W-LOS) prediction model, which simplifies the complex and wide input space. The steps involved for 3W-LOS modelling are; defining input-output variables (influencing parameters (Vi) with two- tailed significance (p)<0.001), defining fuzzy sets for input values (f(Vi)), defining fuzzy rules (Weights towards rules and input functions (Wi)), create and train the neural network using Gaussian membership function. The coefficient of determination for training and testing is found to be 0.8809 and 0.8239 respectively by using the ANFIS output for 3W-LOS prediction over Indian roadway segments.

ABSTRACT. Passing manoeuvres are inevitable on two lane highways with heterogeneous traffic because of the speed differential prevailing in the traffic flow. Among the various parameters which influence safe overtaking, lateral placement and lateral separation of vehicles plays a major role. Lateral interactions of vehicles during passing manoeuvres are influenced by various traffic and geometric characteristics and have significant influence on traffic performance and safety. This paper examines the lateral spacing of vehicles during passing manoeuvring in terms of lateral placement of overtaken vehicle and lateral clearance between overtaken and overtaking vehicle. Models were developed using field data for lateral placement and lateral clearance during passing manoeuvres. The results reveal that the type and composition of vehicles have an influence on passing characteristics. A traffic simulation model is also developed using VISSIM software to assess the impact of truck traffic on passing manoeuvre. When the truck composition changes, there is a significant change in the number of passing manoeuvres and speed of passing manoeuvres.

ABSTRACT. With rising congestion, increased pollution, and decreasing available space per person in urban areas made us to think about the adopting new methods to improve the infrastructure conditions. City administrations so far overlooked one of the basic and most essential elements of the transportation eco-system i.e., the availability of respectable and walkable pedestrian infrastructure. In addition, accessibility for all the pedestrian groups to such facilities is also a major concern. This research paper aims to study and develop the concept of Universal Accessibility Index which is essentially evaluate the suitability of pedestrian facilities available in city for all types of pedestrian groups including disable. Based on the extensive literature study and observations, a robust, reliable and repetitive universal accessibility index is proposed. From the results it is inferred that low level of accessibility is associated with less participation of people especially, elderly, women and differently abled people. Finally, recommendations were suggested for the study location based on the concept of universal design. It is believed that the proposed methodology and finding from this study will be useful for transportation planners and practitioners to evaluate the level of accessibility and ways to improve pedestrian facilities for all user groups.

ABSTRACT. The provision of dedicated bicycling infrastructure in transit catchments ensures safe and convenient access to metro stations. Its provision is challenging in congested urban areas and can be constructed around stations to a certain extent. This research identifies the four parametric logistic (4PL) curve as the appropriate distance decay (DD) function to capture the cycle ridership variation with distance from the station. The trip length range corresponding to the maximum rate of increase in ridership governed by the curve's upper and lower bend points rationally delineates the region where infrastructure provision can yield maximum patronage. We also test and prove the hypothesis that rail alignment and station spacing, station type, and location characteristics affect the bicycling service area. This is achieved by dividing the catchment area into six radial sectors based on its adjacency to the metro line and estimating the bend points on the curve for each sector.

ABSTRACT. Proper development within the station catchment area is a key factor in encouraging transit use and alleviating severe urban traffic congestion. While the railway development has been in progress in Bangkok for over decades, the area development around the station was not in such a way that enhance people to shift away from private cars to the railway. This study examined the patterns of relationships among the characteristics of the catchment area around the 122 urban railway stations based on 5d’s measures of transit-oriented development (TOD): density, diversity, design, destination accessibility, and distance to transit. Multiple correspondence analysis revealed the associations between the TOD factor levels and characterized the station catchment areas based on TOD measures, for example, high density employment and commercial land were found associated with a high degree of diversity, while low density residential areas were associated with low destination accessibility and poor transit access, etc. The findings shade light to enhance the station catchment area development to encourage the railway use.

ABSTRACT. The last mile is movement of people from the various transit stations to their destinations. The last mile transportation system provides on-demand shared transportation. The constraint in selecting the shared mode of transport arises while looking for the better transportation services in terms of availability, flexibility and reasonability from various transit stations to the user destinations. The intermediate public transportation present at the various transit stations was challenging the private transit in providing the more flexible and reasonable cost of the transportation to the users. The literature based on the relative user characteristics of both private transportation and intermediate public transportation and their mode choice travel behaviour is less available. The paper shows the various socio-economic and travel characteristics affecting the last mile trips and examines various issues encountered by users during the last-mile travel. ). It was observed that variables such as gender, occupation, reason of mode choice, Total time have a significant influence on users while choosing their modes.

ABSTRACT. Accessibility of transit is an essential aspect of the success of public transport. Measuring the ease of access to the opportunities by transit is important in evaluating existing services, predicting travel demands, allocating transportation investments, and making decisions on land development. A substantial amount of research on transit accessibility demonstrates the significance of methods for simulating the real-world travel process. Previously available studies have considered the performance parameters aspects of the operator, user, and society independently in the form of indices. However, for a holistic approach, present study proposed a comprehensive framework of indices for evaluating transit accessibility based on coverage, cumulative opportunity, and gravity model-based attraction aspects to develop a composite index. The transit system of Surat, India, is considered a case study for applying the proposed framework. The results indicate that the public transport system effectively serves the city; however, the transit system is not uniformly accessible to all parts of the city. Enhanced accessibility will further boost the performance of the transit system. The developed framework aims to provide a robust applicable measure that can be interpreted easily by policymakers, government bodies, planners, and engineers to identify deficiencies in service coverage and encourage equity in transit accessibility.

ABSTRACT. The present study measures the impact of built environment on access mode choice and gauges the differences between walk and feeder modes. A total of 600 samples were collected within catchment areas of 15 Metro stations in Delhi, India. 5-point Likert scale was used to collect the users’ perception about the walk access environment and service quality of the feeder modes. Firstly, structural equation modelling was used to assess the walking related latent constructs. Subsequently, the study examined two mode choice models; one was a basic model, and other was an extended. ‘Comfort’ and ‘safety-security’ were found to be negatively associated with walking, as people were feeling more comfortable and safer while travelling in feeder modes than walking. Mesoscale built-environment factors observed to be having positive impact on walk-access to metro station. In addition, factors like path distance, gender, education levels, and monthly income were discovered to have a detrimental impact on walking as a mode of access to metro stations. The findings of the study are beneficial in developing policies for the improvement of walking within the catchment areas around metro stations and creating seamless and user-friendly built environment that facilitates the walking towards the metro.

ABSTRACT. In recent years, the demand for glass beads for road marking is increasing, but the problem of low detection accuracy of heavy metal content in glass bead is prominent. Based on this background，this paper proposes an accurate and sensitive two-factor analysis of variance (Two-factor ANOVA) method to determine the content of Sb in glass beads by high-resolution continuous light source atomic absorption spectrometry (HG-HRCS-AAS).Firstly, the sample pretreatment conditions are optimized through orthogonal test design to determine the best digestion ratio of glass bead samples, and the combination of the best digestion temperature, holding time and heating time is obtained by combining range analysis and variance analysis methods. The best acid removal temperature and holding time are determined by the test results. Secondly, we use the two-factor ANOVA to optimize the instrument conditions and reaction conditions. The former includes sensitivity conditions, atomization conditions, and injection conditions. Another includes pre-reduction conditions and hydride generation conditions. Finally,using this method to analyze Sb standard material and get the following results: the relative standard deviation (RSD) of Sb in the glass bead sample was 1.33% and the Limit of detection(LOD) was 0.147μg/L, limit of quantit-ation(LOQ) is 0.490μg/L, the recovery rate of blank spiking is 96%-104%.

ABSTRACT. This study focuses on advancements in road construction technology that reduce aggregate usage, leading to cost savings and energy conservation. It proposes a new method for determining cement and fly ash percentages in stabilizing the base course. The use of Full Depth Reclamation (FDR) with chemical stabilizers enhances strength, reduces water permeability, and increases flexibility. The study examines compaction, durability, and unconfined compressive strength (UCS) with different cement percentages and stabilizers in FDR. UCS increases with varying cement percentages in CTB but decreases with higher fly ash content and stabilizers in FDR. Durability tests show 5.80% mass loss in wetting-drying cycles of CTB. Utilizing CTB as a base layer in flexible pavement construction improves cost-effectiveness, durability, and pavement strength. However, a thicker wearing course is required to prevent rutting and cracking. CTB implementation results in cost reductions of 24.48% for high-volume roads and 34.20% for low-volume roads, while incorporating FDR further reduces costs by 30.06% for low-volume roads as compared to conventional method. In summary, this study explores advancements in road construction technology and highlights the benefits of CTB in flexible pavement construction. The findings emphasize the importance of thickness and demonstrate cost savings through CTB implementation and FDR application.

ABSTRACT. In order to prolong the service life of pavement and guarantee the Construction Quality of Pavement, asphalt mixture must have good construction and good workability. At present, road workers have carried out a lot of research on the viscosity of asphalt, and achieved satisfactory results, but workability are not only related to the viscosity of asphalt, but also need to consider other factors. Based on some research and experimental data, this paper studies the influence of gradation type on mixing and flow characteristics of asphalt mixture. AC-13, AC-20, SMA-13, OGFC-13 and ATB-25 five gradation types and 70# base asphalt were selected in the experiment . The variable speed mixing power testing device developed by the research group was used to change the speed of the mixture.Mixing tests were used to analyze the effect of grading types on the mixing characteristics of asphalt mixtures by different asphalt dosage and different gradation types at different mixing temperatures. The effects of gradation types on mixing characteristics of asphalt mixtures were analyzed.

ABSTRACT. Moisture-induced damage to the asphalt mixtures can occur due to loss of adhesion between asphalt aggregates. This study focused on improving the moisture resistance of hot mix asphalt (HMA) using chemical treatments to inferior quality aggregates(IQA). Hydrated lime (HL), nano-organosilane additive (NOS), and two silane coupling agents (SCA) with different functional groups were used to treat IQA. The HMA specimens were made with treated and untreated aggregates and subjected to moisture susceptibility tests like Marshall stability, retained Marshall stability, indirect tensile strength (ITS), and fracture energy. SEM analysis was conducted to identify surface modifications and understand the treatment mechanisms of different chemicals used. The results showed that chemical treatments improved the adhesion properties of aggregates and also the moisture susceptibility of HMA. Coating retention after the boil test was quantified with image processing, and it was increased to greater than 95 percent compared to control mixes (40-45%). The tensile strength ratio of HMA with treated aggregates was increased by 20-25% above the control mixes. HL and SCA-1 showed better tensile strength ratio (TSR) and fracture energy ratio (FER), it can be concluded that chemically treated aggregates improved fatigue resistance of the HMA even in the presence of water.