ABSTRACT Concerns over traffic congestion and environmental pollution have prompted more studies into the impacts of built environment on commuters’ mode choice behavior. This paper aims to make a comprehensive analysis of commuters’ mode choice behavior with the 5th Household Travel Survey in Beijing. A mixed nested logit model was employed to jointly explore the impacts of mode attributes and built

(2021). Special issue on understanding the relationships between COVID-19 and transportation. Transportation Letters: Vol. 13, Understanding the Relationships Between COVID-19 and Transportation, pp. 327-330.

ABSTRACT The COVID-19 outbreak significantly disrupted urban mobility across the world and affected people’s travel behaviors. This paper aims to explore the relationship between socio-demographic and health factors and changes in travel behavior during the second phase of this outbreak. We proposed two measures to assess these changes: (i) whether an individual reduced the number of trips to stores

ABSTRACT The fear of infection of COVID-19 among people has greatly reduced their intention to travel, which needs a deeper understanding to aid the policy-makers in framing robust guidelines to ensure safe travel. This paper aims to present a critical understanding of the traveler’s willingness to reduce their trip frequency, using psycho attitudinal analysis of the variables impacting the travel

ABSTRACT This paper explores the impact of COVID-19 on shopping behavior in two neighboring developing economies: Bangladesh and India. While the previous studies investigating the impact of COVID-19 on shopping behavior have relied on Revealed Preference (RP) data, this paper combines RP and Stated Preference (SP) data to develop joint RP-SP discrete choice models. This makes it possible to quantify

ABSTRACT COVID-19, a respiratory virus violently spread worldwide, has deeply affected people’s daily life and travel behaviors. We adopted an autoregressive distributed lag model to analyze changes in travel patterns in Houston, Texas during COVID-19. The results indicated that visit patterns and changes in COVID-19 cases a week prior heavily influence the following week’s behaviors. Additionally

ABSTRACT This research proposes a novel single-level approach to traffic counts-based OD estimation using observed turning proportions and partial OD flows. The key idea is to relax the need for explicit assignment-based bi-level models and exploit the observations from big traffic data. The observed turning proportions are used to estimate traffic counts; and the structural knowledge of partial OD

ABSTRACT This study examines the causal relationship between road transportation and economic growth in 31 provinces and municipalities in China by using province-level panel data covering the period from 1980 to 2015. This study adopts the Granger causality analysis based on meta-analysis in heterogeneous mixed panels. The empirical model also considers the heterogeneity of the coefficients and the

ABSTRACT This paper presents the joint analysis of departure time choice for non-work activities and latent preferences toward the active and non-active mode. Utilizing the concept of smart growth design of neighborhoods, scheduling the travel activities considering active transport through smart phone applications is one of the efficient ways to promote active mode usage. The hypothesis of the current

ABSTRACT The environmental traffic assignment problem in the bimodal network with electric vehicles (EVs) and gasoline vehicles (GVs) has become a hot topic recently. However, few previous works consider the psychological difference between EV users and GV users in terms of environmental awareness , in order to fill in this research gap, we formulate an environment-oriented mixed-behavior user equilibrium

ABSTRACT Despite the well-known benefits that autonomous technologies bring to supply chain and logistics, the adoption of such technologies remains a challenging task. This study seeks to investigate how firms that are associated with the generation of freight movements in Niagara Region (Canada) will respond to new autonomous technologies. Structural Equation Modeling was used to extract meaningful

ABSTRACT It is crucial for policymakers to satisfy the expectation of network users in practice. It is a so-called responsive transport network design problem. It is curious that this important problem is rarely explored. This paper aims to propose a method to solve this problem. A novel bi-level programming model is formulated where the upper level is to minimize investment cost with desired travel

ABSTRACT The work zones greatly change the traffic wave characteristics on the urban road and further significantly influence the signal timing schemes. However, studies on the traffic wave under the influence of work zones are limited. This paper attempts to investigate how a work zone changes the traffic wave propagation characteristics. The traffic wave profiles for different scenarios are analyzed

ABSTRACT This study explores the spatial mode of electric vehicle (EV) adoption in the early market of 41 key cities in China among which there is a high spatial heterogeneity . A spatial econometric model is established to illustrate the relative importance of regional variables on EV adoption. Most independent variables have significant direct positive effects on EV adoption. Specifically, the number

ABSTRACT The discretionary lane-changing process consists of two phases. The first phase is decision making on lane-changing, and the second phase is the execution of this decision. The first phase has a complex structure that is affected by many parameters. In this phase, some parameters are present that affect lane-changing directly, while some other indirect parameters motivate drivers to perform

ABSTRACT The present study focuses on modeling roundabout in heterogeneous condition and understanding the effect of change in two-wheeler composition on the entry capacity using microscopic simulation technique. A four-legged roundabout of 25m diameter, located in the city of Chandigarh, India was considered as the study area. As Indian traffic flow is highly heterogeneous due to the presence of vehicles

ABSTRACT Predicting the traffic conditions in urban networks is a priority for traffic management centres. This becomes very challenging, especially when the network is affected by traffic incidents that vary in both time and space. Although data-driven modelling can be considered an ideal tool for short-term traffic predictions, its performance is severely degraded if little historical traffic information

ABSTRACT This paper explores the emotions of self-drive rental car users in India on social-media platform using sentiment analysis and estimates the relationship between socio-demographic factors and factors influencing the decision of renting a car. An ordered logit model is used to determine the factors which are affecting individuals’ demographic characteristics to rent from a self-drive rental

ABSTRACT The state-of-the-art of mobility services among large-scale agent-based travel demand models has focused predominantly on the demand side, whereas complexities of the supply side have been given much less attention. Conventional definitions must be revisited to establish solid foundations for model implementations. First, several mobility services are characterized from abstract attributes

ABSTRACT This paper addresses the problem of traffic variable estimation and traffic state classification of highway traffic, from video. To solve this problem, we propose to use the Interactive Multiple Model (IMM) filter with a multi-class macroscopic model. This filter runs two Extended Kalman Filters (EKF) to smooth the measured traffic parameters. In addition, the models’ probabilities that it

ABSTRACT Dynamic prediction of queues and delays at signalized intersections utilize data obtained from automated traffic sensors as inputs for Intelligent Transportation Systems (ITS) applications. Errors are inevitable during automated data handling, especially when the traffic involved is heterogeneous and lacking in lane discipline. This paper presents a model-based estimation scheme that can handle

ABSTRACT Real-time traffic speed information is essential for effective traffic management. Due to the high costs of conventional data collection methods, transportation agencies have sought alternative data sources, such as Waze. To thoroughly evaluate and explore Waze, or similar probe-based traffic data, This study used a 10.8 mile stretch of I-40 in Knoxville, Tennessee to compare the speed measurements

ABSTRACT The p-center problem is the problem of finding p best places on a network to locate facilities for providing customers' demands such that the maximum distance between the demand points and facilities is minimized. If these facilities are located on the edges and vertices of the network, the problem is called the absolute p-center problem. Whereas, if the facilities can just be located on the

ABSTRACT The present work introduced a framework of developing comprehensive extended vehicular trajectory data under heterogeneous non-lane-based traffic conditions like the NGSIM datasets in the United States. Due to the absence of automation and instrumentation, and even the lack of sensor deployment on roads in developing economies like India, it is even more challenging to study driver behavior

ABSTRACT Limited priority conditions are observed in developing countries which cause the approaching through vehicles (higher priority movement) to compromise their movement in terms of speed reduction or lane changing or may be a combination of the both. This compels the vehicles to (i) experience undesirable delay, (ii) perform forced lane changes, and (iii) experience an overall flow reduction

ABSTRACT Recently, carsharing has emerged as an alternative to vehicle ownership in many countries worldwide. This study examines the system parameters of one-way carsharing systems to determine a trade-off between the lost sales rate and system parameters. Four system parameters are considered in this study, namely average number of vehicles per station, rate of one-way trip, average number of staffs

ABSTRACT This paper introduces the Fleet Size and Mix Vehicle Routing Problem with Synchronized Visits (FSM-VRPS), an extension of the Vehicle Routing Problem with Synchronization (VRPS), where a mixed fleet composed of electric and conventional bikes, and passenger cars having different acquisition costs are considered. The problem consists of planning a set of different vehicle routes to serve a

ABSTRACT The COVID-19 outbreak led to significant changes in daily commuting. As lockdowns were imposed to metropolitan areas throughout the globe, travelers refrained heavily from using public transport, to maintain social distancing. Based on data from Athens, Greece, this paper investigates the anticipated, post-pandemic behavior of travelers with respect to public transport use. Focus is given

ABSTRACT Free-floating car sharing (FFCS) service draws attention and has the potential to improve transportation system efficiency and achieve sustainability. This study proposes a self-efficacy-based value adoption model (SVAM) to investigate consumer adoption intention of FFCS by decomposing the perceived value and the self-efficacy. Specifically, the model examines the functional, economical, emotional

(2021). Joint distribution modelling of vehicle dynamic parameters using copula. Transportation Letters. Ahead of Print.

ABSTRACT Continuous Approximation (CA) models have been used to solve transportation problems due to their ability to efficiently model complex transportation systems and offer flexibility in testing alternative policies. The current study develops a CA model for optimizing transportation planning for ferry services. The model is tested in a case study for a ferry network in the Aegean Sea, Greece

ABSTRACT The present study examines the impact of lockdown measures taken to control the spread of COVID-19 on road fatalities. The study is based on the data collected over the duration of six months for fifteen countries based on severity of COVID-19. Lockdown stringency and six daily mobility measures were selected to study the change in road mobility patterns due to lockdown measures. The fifteen

ABSTRACT The present study focuses on the relationship between the Covid-19 pandemic and mobility patterns. By using data from an international survey, transport users’ socio-demographic features and travel characteristics during the pre-pandemic and pandemic time are analyzed.Afterward, the pandemic commuting travel behavior is modeled. The multinomial model shows that public transport users are 31

(2021). Modeling, simulation and evaluation of transport scenarios in the presence of innovative solutions. Transportation Letters: Vol. 13, Modeling, simulation and evaluation of transport, pp. 149-150.

ABSTRACT The success of machine-learning methods is spreading their use to many different fields. This paper analyses one of these methods, the Kernel Logistic Regression (KLR), from the point of view of Random Utility Model (RUM) and proposes the use of the KLR to specify the utilities in RUM, freeing the modeler from the need to postulate a functional relation between the features. A Monte Carlo

ABSTRACT Modelling and simulation of mixed-traffic zones is an essential tool for transportation planners to assess safety, efficiency, and human-friendliness of future urban areas. This paper addresses the calibration and transferability of existing shared space models for pedestrians and cars. Specifically, our first contribution is enhancing the Game-Theoretic Social Force Model (GSFM) by a generic

ABSTRACT Freight vehicle origin-destination (O-D) matrices play a key role within the assessment procedures of city logistics scenarios, and simulation of delivery tours allows such O-D flows to be obtained. Therefore, the paper revisits a modeling framework for simulating delivery tours using an aggregate approach proposed by the authors and presents the preliminary results of its implementation to

ABSTRACT After the COVID-19 pandemic, a decrease in travel demand due to the mass transport characteristics of public transit was inevitable, and the impact of the pandemic has increased the need for new transport policies. This study aims to propose transport policies for public transit through comparison by quantitatively measuring passengers’ crowding impedance before and after the COVID-19 pandemic

ABSTRACT In the absence of pharmaceutical interventions for the Novel Coronavirus (COVID-19), countries have taken drastic steps like quarantine, prohibit large-scale gatherings, limited transport, social distancing, curfews, and lockdowns to curtail the spread of the virus. In light of these events, the current study attempts to understand the short-term changes in road traffic patterns, using data

ABSTRACT The COVID-19 outbreak created a context that was not previously considered by most urban transportation planners and modellers. This paper presents a study design to comprehensively measure the effects of COVID-19 induced Lockdown on changes in travel behaviour and its dynamics. The study is designed for the Greater Toronto Area. The paper presents results from the common portion of four specialized

ABSTRACT The transportation sector has been severely crippled by the COVID-19 crisis in India. Due to the strict enforcement of a nation-wide lockdown, the operators of long-distance transport in India by road, rail, and air have suffered leading to loss of jobs and pay cuts. As the year 2020 reaches an end, the severity of the pandemic began to subside and the common modes of long-distance travel

ABSTRACT We investigate the evolution of the Chinese Spring Festival travel network during COVID-19 early outbreak (Jan 17 to Feb 23, 2020) in China and explore the impacts of COVID-19 on the evolution of the intercity travel network. We find that the connections of a China city with other 27.9 cities were cut off after the Wuhan lockdown (Jan 23). Correlating the degree centrality of each city and

ABSTRACT The COVID-19 pandemic lockdown undeniably impacted travel behavior. It is assumed that directed (commute and non-work) trips reduced following reduced out-of-home activities. This study analyzing 764 respondents in Flanders, Belgium, explores whether undirected trips, or travel for the purpose of travel itself, increase as compensation or to ‘get out and about’. Additionally, change in commute

ABSTRACT In this Fuzzy Inference System based study, a model is developed which can present a real-time risk assessment model to the drivers. The model includes parameters car speed, accident frequency, weather conditions, tire tread depth and fatigue. In order to evaluate the performance of the model, the road between Zonguldak and Düzce is chosen, which has a high accident incidence and can cause

ABSTRACT The novel Coronavirus (COVID-19) significantly impacts all sectors and brings the whole population to stuck at home due to a countrywide lockdown in India. Due to the lockdown, the major influence is on students and education systems all over the world. The present study attempts to study the effect of COVID-19 on traffic patterns and choice of mode for the students to reach their host institute

ABSTRACT This paper aims to emphasize the impacts of the COVID-19 pandemic at the healthcare logistics and supply chain networks and to transport polymerase chain reaction testing samples between hospitals and laboratories by using unmanned aerial vehicles (UAVs). To achieve the mission, range and payload capacitated UAV routing problem is defined and a mixed-integer linear programming model (MILP)

ABSTRACT The COVID-19 pandemic has altered day-to-day life worldwide, including the perceived risks associated with travel. Ride-sourcing can augment the mobility of those without access to private vehicles and who are reluctant to use public transit. Using data from a web-based survey, this study investigates the influence of the first wave of the pandemic on ride-sourcing use in the Greater Toronto

ABSTRACT The paper discusses the major limitations of the existing speed–area occupancy curve for multi-class traffic. Any driver will react not to the actual area occupancy, but to a perceived area occupancy based on the spatial arrangement and percentage composition of vehicles. To address multi-class traffic peculiarities, this paper proposes a formulation for perceived area occupancy. Traffic flow

ABSTRACT Although several studies have attempted to determine the mileage and time inefficiency of ridesourcing services due to concerns about traffic and environmental impacts of these services, all of them provide a point estimate, which does not reflect the uncertainties in the calculation of these estimates. As such this study aims to present the efficiencies as ranges, based on lower and upper

ABSTRACT At metro junction stations located in transportation hubs, a great number of passengers need to transfer to the metro system from other transportation modes during peak hours. This paper proposes a new train operation strategy—reserving carriages dynamically on each service train at the departure station for the metro junction station, which aims to relieve the serious passenger accumulation

ABSTRACT Interchange provides more flexibility in route choice, a key travel behaviour in urban rail transit, but its influence is usually simplified. This paper investigates how interchange affects route choice with passenger perception considered. At single-interchange level, perceived interchange time was proposed and modelled under three resolutions to capture passenger perception and its sensitivity

ABSTRACT The imputation of time series traffic flow data is of great significance to the intelligent transportation, urban planning, and road emergency handling. This paper proposes a filling missing time series traffic data with Generative Adversarial Network (ST-FVGAN), which not only considers the spatio-temporal correlation and utilizes the idea of data generating of the Generative Adversarial

ABSTRACT This paper presents an analysis of people’s time use patterns, incorporating the mediating role of ICT and personal networks on their daily activity-travel patterns, explicitly addressing the issue of activity fragmentation for social-based episodes. Implementing a seven-day time use survey, which includes temporal, spatial, and social characteristics for each activity, and using a theoretical

ABSTRACT Modelling and simulation of mixed-traffic zones is an essential tool for transportation planners to assess safety, efficiency, and human-friendliness of future urban areas. This paper addresses the calibration and transferability of existing shared space models for pedestrians and cars. Specifically, our first contribution is enhancing the Game-Theoretic Social Force Model (GSFM) by a generic

ABSTRACT The imputation of time series traffic flow data is of great significance to the intelligent transportation, urban planning, and road emergency handling. This paper proposes a filling missing time series traffic data with Generative Adversarial Network (ST-FVGAN), which not only considers the spatio-temporal correlation and utilizes the idea of data generating of the Generative Adversarial

ABSTRACT In this paper, we apply the minimum information theory to the uncapacitated p-median facility location problem to determine the most probable allocation solution. Indeed, we investigate the bi-level p-median model introduced by [TRANSPORT RES B-METH. 123 (2019) 1–20] in the case that facilities have unlimited capacities. At the upper level, minimizing the cost of establishing facilities and

ABSTRACT Until now various surrogate safety measures (SSM) have been developed and research in this area is ongoing. However, it is unclear which indicators are able to reflect danger more accurately. This paper proposes a novel method of performance comparison by taking the advantage of statistical analyses of SSMs data. This analytical approach is inspired by the dominant behavior of drivers in car-following

ABSTRACT Crashes take place at intersections even when signalized due to the presence of dilemma zone, where the driver feels uncertain whether to cross or stop at the trigger of yellow signal. Erroneous decisions taken by the driver leads to rear-end or right-angle crashes, causing safety implications. Accurate position of the dilemma zone can help in implementing various safety measures and enhance

ABSTRACT Short-term travel time prediction on freeways is the most valuable information for drivers when selecting their routes and departure times. Furthermore, this information is also essential at traffic management centers in order to monitor the network performance and anticipate the activation of traffic management strategies. The importance of reliable short-term travel time predictions will

ABSTRACT The focus of this study is to examine the service quality of unsignalized intersections based on the perception of automobile drivers. This was achieved by developing Automobile Level of Service (ALOS) models using two computational intelligence methods – Functional Linked Artificial Neural Network (FLANN) and Differential Evolution (DE). The required data were collected at 47 unsignalized