Despite the huge progress toward fully autonomous vehicles, current models are limited to Level 3 autonomy due to technological constraints, making driver readiness necessary for manual intervention. Head-up displays (HUDs) enhanced with augmented reality (AR) technologies are being developed to improve safety and convenience by projecting essential information onto windshields, thereby minimizing

Road accidents globally have an 18 % fatality rate per 100,000 population, with significant regional variations, particularly affecting Africa. The increasing frequency of oil and gas tanker accidents in Nigeria exemplifies this trend, highlighting the need to explore the relationship between risk perception, driving task perception, and road safety attitudes among Nigerian oil and gas tanker drivers

Value of travel time (VOT) serves as a crucial metric for understanding the benefits of transport investments and policy initiatives. Despite numerous studies estimating the VOT for Autonomous Vehicles (AVs), consensus remains elusive, and the variability of the factors influencing AV VOT estimates has yet to be thoroughly explored. This study addresses these gaps through a meta-regression analysis

This paper focuses on the tour-based mode choice pattern of the post-secondary students of the Greater Toronto and Hamilton Area (GTHA). The data for this study was collected from a detailed online-based survey in the GTHA. Based on the survey data, the mode choice model for two-trip tours and three-trip tours is estimated using a dynamic discrete choice modeling approach. The model results capture

Multimodal integration is an important issue in public transport systems due to its influence on both passenger experience and overall network efficiency. In most countries in the global South, achieving integration is particularly problematic because of the informal nature of most public transport. Decentralised service planning and demand responsiveness lead to often uncoordinated, highly variable

Given the dynamic nature of human behavioral decisions over time, a life course approach is adopted to understand the interdependencies among key events in different life domains including residence, occupation, and car ownership. Based on a combination of binomial logit and decision tree, intertwined relationships for all three domains have been confirmed with respect to a quasi-longitudinal dataset

Recently, Mobility as a Service (MaaS) has garnered increasing attention by integrating various modes of transportation to provide users with a unified travel solution. However, In multimodal transportation planning, we primarily face three challenges: Firstly, a multimodal travel network is constructed that covers multiple travel modes and is highly scalable. Secondly, the routing algorithm fully

Recent years have seen a rapid deployment of shared electric scooters (e-scooters), across hundreds of cities worldwide. Despite the global diffusion, most urban residents are still not using e-scooters, and they often bear the negative consequences of e- scooter deployment. This comparative study investigates the attitudes and characteristics of the e-scooter non-users in Helsinki, Finland and Tokyo

Emotion is an important factor that affects driving behavior, and thus, drivers’ emotions are closely related to overall traffic safety. We investigated the emotional expressions of online car-hailing drivers under two driving conditions: with passenger(s) and without passenger(s). We recruited 16 male car-hailing drivers and collected a total of 91.5 h of data using non-contact equipment. We employed

While the pursuit of sustainable measures to arrest private vehicle usage and externalities continues, poor last-mile connectivity remains a major deterrent for choice riders (car owners) considering the use of public transport. The present study proposes an integrated Bike Taxi-Bus Service (BTBS) system as a solution to last-mile connectivity concerns and investigates the perception of choice riders

Superior safety is the main banner value of promoting autonomous vehicle (AV) technology, but it is difficult to responsibly claim it. The potential for AVs to reduce crash and injury risks would be overshadowed by technological limitations, regardless of their ability to mitigate or eliminate human error. This study aims to identify the key factors affecting crash severity by analyzing real-world

The transport network is a complex system that benefits from detailed data on user mobility. Analyzing user trajectories through clustering or classification methods can provide valuable insights into mobility patterns. Extracting transport modes from these trajectories using classification methods enhances the understanding of user mobility. The complexity of classification methods varies, with some

Leisure activities are closely associated with individuals’ quality of life. In this paper, we are interested in how many leisure trips the individuals have realized and how many trips they schedule but fail to realize due to the inability to accomplish the activity. The realized and unrealized leisure trips are correlated and together constitute leisure needs. To investigate it, a survey was conducted

Given the destructive nature of hurricanes in tropical regions, pre-disaster evacuation has emerged as a critical approach for hurricane preparedness. Nevertheless, the compounding effects of natural hazards and the outbreak of infectious diseases, such as Covid-19, significantly challenge hurricane evacuation management. To investigate emergency responses under compound hazards, this study develops

In the United States (US) and Canada, paratransit refers to transportation services that supplement scheduled, fixed route, mass transit to eligible passengers, namely people with disabilities and a growing number of older adults. This paper presents a critical systematic review of the literature on paratransit in the US and Canada since 2010 (n = 57), investigating what is known about paratransit

Micromobility and public transport integration is an area of urban mobility that has been increasingly gaining attention and importance. The necessity to provide improvements to public transport services and their spatial reach in order to reduce the number and volume of car trips in cities is irrefutable. The integration of micromobility and public transport is often presented as a valuable strategy

A comprehensive understanding of charging behaviors among electric vehicle users is crucial for advancing green transportation and deploying effective charging infrastructure. This study conducted large-scale empirical research using data from electric taxi fleets in Shenzhen to explore the heterogeneity of charging behaviors among taxi drivers. The study hypothesized that distinct charging patterns

A two-step model framework is proposed and applied to analyze empirically the impact of a travel time reduction on labor supply in two-worker two-gender households, using a nationwide data set for time use collected in 2015 in Chile. First, a system of structural equations (SSE) is estimated to reveal which activities can be considered as committed, and to unveil the hierarchy of activities by gender

Traffic congestion has imposed considerable economic expenses and environmental challenges on metropolitan areas. Consequently, cities have implemented Travel Demand Management (TDM) strategies to mitigate this issue during peak hours. Although studies have investigated how individuals make decisions during commuting in response to TDM incentives, there is limited research on differences in route choices

Time-use surveys provide useful data for travel analyses. However, the survey on time use and leisure activities (TULA) Questionnaire A, a representative time-use survey in Japan, does not include questions related to the locations of activities, thus making it difficult to use for travel analyses. This study proposes machine-learning methods to determine the in-home/out-of-home situations of TULA

Bike-sharing systems play a crucial role in encouraging sustainable transportation, and understanding their usage characteristics is essential for enhancing their contribution to urban mobility. This research seeks to investigate how weather conditions impact the utilization of a small-scale docked bike-sharing system. The study employed Generalized Linear Mixed Effects (GLME) models to analyze interactive

Bike-riding GPS data offers detailed insights and individual-level mobility information which are critical for understanding bike-riding travel behaviour, enhancing transportation safety and equity, and developing models to estimate bike route choice and volumes at high spatio-temporal resolution. Yet, large-scale bicycling-specific GPS data collection studies are infrequent, with many existing studies

Increasing the share of travelers using public transport is one way to address environmental problems such as carbon dioxide emissions. Senior citizens represent an increasingly important group in this transition, as they are increasingly mobile and make up a large share of the population. In this paper, we investigate senior citizen’s mobility decision-making, focusing on public transport. Through

Active Mobility Devices (AMDs) such as electric scooters (e-scooters) and electric bikes (e-bikes) are increasingly used on shared paths and Park Connector Networks (PCNs) in Singapore, leading to frequent interactions between AMD riders, pedestrians, and cyclists. To ensure safety, it is crucial to understand the factors associated with collision risk related to these AMDs. To gain insights into the

As a representative mode of shared mobility, bike-sharing serves not only as a convenient way to conduct short-distance trips in urban areas, but also as a feeder mode to public transit, forming the Bike and Ride (BnR) system. Conducting management for such a hybrid multi-modal system faces various challenges, including the complex interactions between bike-sharing and other modes, highly dynamic passenger

To help automated bus services to be competitive in the market, understanding what factors influence the public’s acceptance and adoption of an automated bus service and how these factors change over time is critical. Various factors affect users’ acceptance of this new bus mode, with the quality of service standing out as a significant consideration. Based on pilot demonstrations, some prior studies

The mobility of persons is changing due to technological innovation linked to autonomous and electric vehicles or to connectivity and data communication technologies. Furthermore, it is being conditioned by social behaviours. Qualitative research based on in-depth interviews with experts in mobility from three European countries is used to analyse the main trends that characterize the current transformation

This study examines the links between neighborhood walkability, household income, and older adults’ walking trips. This study mainly utilizes the detailed individual-level data from the 2017 National Household Travel Survey-California Add-on (2017 NHTS-CA). To understand neighborhood walkability and its effects on older adults’ walking trips, we first classify neighborhoods using K-means clustering

Based on the analysis of one-week GPS-based travel diary data from the four largest metropolitan areas in California, this study performs a latent-class cluster analysis and identifies four distinctive traveler groups with varying levels of multimodality. These groups are characterized by their distinctive use of five travel modes (i.e., single-occupant vehicles, carpooling, public transit, biking

Resilience is a characteristic of a system to adapt, resist and recover from disruptions as defined by the U.S. Federal Highway Administration. The concept has been adopted across several fields of research. Existing literature on roadway network resilience typically frames resilience in terms of performance metrics based on the attributes of the network (travel time or travel distance, for example)

In this paper, a probabilistic topic modeling algorithm called Latent Dirichlet Allocation (LDA) is implemented to infer trip purposes from activity attributes revealed from smart card transit data in an unsupervised manner. While most literature focused on finding patterns for home and work activities, we further investigated non-home and non-work-related activities to detect patterns associated with

While living in city centers is usually linked to higher accessibility levels, shorter travel times, and higher levels of public transit (PT) utilization, the opposite is true for residents of suburban areas. This assumption holds in metropolitan contexts, where central areas offer better accessibility and are associated with higher levels of PT use. In metropolitan peripheries, a large part of commuting

All over the world, cities are becoming “smarter.” The improved use of data generated by the transport system (e.g. smart cards data), combined with GPS trackers and citizens’ mobile data enabled the development of a new generation of smarter mobile apps (e.g., Waze) and several local real-time public transport services and trip planners. These technologies have the potential to reduce transport inequalities

This study aims to extend and investigate how external factors (socioeconomic and demographic characteristics, EV-related policy mechanisms, transportation, and climate conditions) influence the actual adoption of battery electric vehicles (BEVs). Using panel data from 49 U.S. states from 2011 to 2020, we estimate a dynamic spatial Durbin model under the space fixed effect to examine the effects of

This review explores the potential of digital twin systems to provide a more holistic representation of travel behavior and support transportation planning and policymaking. The paper introduces the concept of digital twins, their key characteristics, and their applications in various domains, including transportation. It discusses the traditional methods used in travel behavior analysis and their

Promoting the use of sustainable transport alternatives is critical for reducing carbon emissions. In this paper, we propose a cognitive mechanism that explains the extent to which individuals use different sustainable travel modes (e.g., the bus, train, bicycle, and car-sharing). Specifically, we hypothesise negative emotions related to cars as an antecedent of sustainable travel mode use where emotions

Concerned by the increasing environmental impact of urban areas and the mobility sector, the study examines mobility in Reykjavík, Iceland. Reykjavík residents have been found to have high emissions in both local and leisure travel. The study aims to explore the connections between urban mobility and leisure travel behaviour using a novel method – activity spaces. The relationship between activity

While a substantial body of literature exists on the factors associated with walking behavior, little is known about the long-term effects of childhood experiences. This study utilizes micro-longitudinal data from the Indonesian Family Life Survey (IFLS) to track the lives of 1,343 Indonesians from childhood to adulthood. Findings from a series of regression analyses provide suggestive evidence of

Travel preferences in public transport (PT) have been substantially affected by the COVID-19 crisis, with rising emphasis on on-board safety and comfort aspects. Hence, real-time crowding information (RTCI) might have become even more instrumental in supporting travel decisions in congested urban PT systems. This study investigates the willingness to wait (WTW) to reduce (or avoid) overcrowding with

Mixed-traffic crosswalks are a prevalent scene in urban traffic. Understanding the movement characteristics of bidirectional e-bike-pedestrian mixed flow is helpful to enhance traffic efficiency at an intersection. In this research, a controlled experiment on bidirectional e-bike-pedestrian mixed flow was conducted. There are three variables, namely the proportion of e-bike riders (i.e., 0.5 and 0

Wheelchair accessibility of transportation service hailed using Uber and Lyft is fraught with contention. In this research, I interview 12 drivers on the apps who work in Washington, DC to understand their experience and perception about issues surrounding service to wheelchair users. Some drivers experience transporting wheelchair users as markedly different from service to non-wheelchair users due

Hand foot mouth disease (HFMD) is one of the widespread transmissible diseases that target preschool children, especially in urban regions in East Asia. Based on the mobile app data, a GIS automated regionalization method is used to define regions of various urbanicity levels. The variability of HFMD patients’ travel behaviors across these regions are examined by the complementary cumulative distribution

In psychology, choices are influenced by either goal-directed or habitual systems, which are represented by model-based (MB) and model-free (MF) reinforcement learning algorithms. This paper introduces these concepts into the transportation literature and shows that individuals with habitual tendencies often fail to consider new, potentially superior, alternatives. Across two experiments, participants

In order to investigate the role that Mobility as a Service (MaaS) could play in university communities to reduce car dependency and moderate car-oriented travel behavior, this paper examines individuals’ stated interest in adopting MaaS bundles in academic environments, where its potential is still largely underexplored. The study involves a large-scale survey campaign carried out within a university

A poor diet has crucial impacts on individuals and society as a whole. In addition to individual preferences, there is evidence that people’s diet is related to their social, economic, and geographical environment, including their mobility context. However, few studies have an empirical, integrated perspective of these previous dimensions. This paper presents an empirical effort to understand people’s

Increasing urbanization is causing many challenges for mobility today, such as traffic jams and high carbon dioxide emissions. Hyperloop is a radical mobility innovation that could offer a potential solution for these issues. Since hyperloop is currently under development, overcoming technical and economic challenges and increasing its acceptance in society will decide the success of this innovative

The impact of ride-hailing (RH) as an emerging mode of travel service on public transit (PT) systems has been confirmed. However, the current research only views the relationship between PT and RH as competition or complementation based on macro statistics and travel time differences. In fact, the relationship is beyond binary, and it is partial to take the travel time difference as the only classification

Car-sharing mobility is an emerging sustainable transportation mode, but it poses great challenges to operators and urban traffic management due to the imbalance between supply and demand across time and space. To address the problem, this research proposes a spatio-temporal rebalancing optimization framework for the urban car-sharing system (CSS) based on geospatial big data and machine learning.

A rise in reporting and media coverage of negative social interactions and experiences of racism in transit and other public environments suggests that perceived discrimination may have affected the travel behavior and health of people of color during the COVID-19 pandemic. In this study, to examine relationships between race, perceived discrimination, transit use, and walking behavior, we draw on

Air-rail intermodal services (ARISs) represent a highly promising multimodal solution within the transportation sector. Nonetheless, various uncertainties and challenges persist across multiple dimensions of air-rail interline travel, with discrepancies in passenger perceptions being a notable aspect. In an effort to pinpoint the pivotal factors contributing to these disparities among distinct passenger

Bikeshare is increasingly recognized as a healthy travel behaviour worldwide. However, issues of inequity in bike-sharing usage exist and hinder the social benefits of bike-sharing system. This paper aims to unveil the spatiotemporal evolution of inequalities in bike-sharing usage and their social-built environment correlates, using Chicago’s Divvy system as a case study. Specifically, Gini coefficients

With the advent of new mobility modes and technologies, we have seen meaningful changes in travel behavior. One such new mobility mode is on-demand transit. The Metropolitan Atlanta Rapid Transit Authority deployed its own on-demand transit system, dubbed MARTA Reach, in March of 2022. This paper provides an evaluation of the characteristics of two groups of people related to MARTA Reach: those who

Encouraging residents’ green travel behaviour can reduce carbon emissions. However, existing research focuses more on the individual level than on green travel in the context of group interactions. This study aims to connect individual- and group-level insights by integrating the theory of planned behaviour (TPB) and the norm activation model (NAM). Based on empirical data from a questionnaire survey

One major challenge of a public transit system is first- and last-mile (FLM) connectivity. With the advent of smart technology and on-demand transportation services, shared micromobility is believed to provide a low-cost solution for bridging the first- and last-mile gap. However, several studies have arrived at mixed conclusions about the FLM achieved by shared mircomobility. This study explores the

In this paper we assess whether shared e-scooters are being used in hurried situations to avoid arriving late, making trips we define as last-minute trips. We identify trip characteristics for last-minute trips using data from shared e-scooters in Stockholm. Trip arrival time patterns, distances, durations, and speeds are analyzed in relation to desired arrival times. We observe a peak in the number

The concept of Mobility on Demand (MOD) aims to create a safe and convenient ecosystem for transportation and goods delivery. Despite offering various services, the integration and seamless data exchange among different modes of transportation remain challenging. To address this, research was conducted to examine the current state of integration in the MOD ecosystem, identify gaps in data exchange

Many American cities are testing autonomous shuttles (AS), or self-driving minibuses, as a new mode of public transportation. Existing AS studies often rely on stated preference (SP) surveys that require participants to imagine AS scenarios, or they evaluate short-term pilot programs, thus lacking long-term user insights – particularly in car-dependent suburban contexts. To address these limitations

The COVID-19 pandemic resulted in drastic changes in people’s living habits. The lockdown, social distancing measures, and the fear of contagion severely impacted the demand for public transportation services. Due to the decline in demand during the pandemic, the financial crisis of the Bus Rapid Transit (BRT) systems in Colombia, similar to other Latin American countries, worsened. This article aims

E-scooters, a burgeoning form of micromobility, are revolutionizing urban transportation systems globally, particularly in the post-pandemic world. The surge in e-scooter adoption introduces novel regulatory challenges for local authorities. Numerous recent studies cater to these policy needs by exploring e-scooter use. However, scant attention has been paid to non-users’ perspectives, which is crucial