Transit operators need vulnerability measures to understand the level of service degradation under disruptions. This paper contributes to the literature with a novel causal inference approach for estimating station-level vulnerability in metro systems. The empirical analysis is based on large-scale data on historical incidents and population-level passenger demand. This analysis thus obviates the need

This paper aims to evaluate the impacts of the economic context on traffic congestion and its consequential effects on private vehicle accessibility. We conduct a long-term analysis of spatiotemporal traffic congestion patterns in Madrid (Spain), comparing two urban realms: the 2008 economic crisis and the following post-crisis situation. We apply TomTom Speed Profiles data to assess daily variations

Travel demand estimation, as represented by an origin–destination (OD) matrix, is essential for urban planning and management. Compared to data typically used in travel demand estimation, the key strengths of social media data are that they are low-cost, abundant, available in real-time, and free of geographical partition. However, the data also have significant limitations: population and behavioural

The combined use of the bicycle and the train in the Netherlands has risen steadily over the past decade. However, little is yet known about the underlying processes driving the growth of bike–train use in the Netherlands. Are new bike–train trips replacing car trips, or are they primarily an extension of existing train travel and cycling practices? The present study investigates this question by exploring

During the era of COVID-19 (COronaVIrus Disease of 2019), telework has been adopted extensively in developing countries for the first time. This study analyzes data of 355 teleworkers in Hanoi (Vietnam) during April 2020, the period of social distancing, to examine various factors associated with (1) complete home-based telework (HBT), (2) the perception of HBT, and (3) the attitude toward the combination

In this paper, we propose a method for estimating the timings at which trains arrive and depart from stations using passenger farecard data and knowledge of the network topology. The problem we consider is essential for understanding commuter movement patterns across metro systems at high granular detail in settings where one does not have access to train logs (comprising records of train arrival and

A robust and scientific selection of appropriate Travel Demand Management (TDM) measures is likely to ensure that the purpose of their implementation is met. The existing methods of TDM measure selection do not often adopt a multi-dimensional approach in their decision-making process. Besides, there is minimal scholarly work on the selection of a ‘push plus pull’ integrated TDM package, even though

The studies on escalators have mainly reported the walking speeds of passengers or their passenger handling capacity. Theoretical capacity is reported as a constant value for a given escalator speed, but is never achieved in the field. This creates practitioners’ dilemma regarding augmentation of the facility as some capacity will always remain available even under high passenger flows. This paper

Developing economies are still in the stage of e-commerce deployment, unlike in developed countries, where online shopping is already a common purchase channel. This research aims to assess the purchasing behaviors of end-consumers in regard to two alternative shopping channels: in-store and online, within a developing economy. A revealed-preference survey was conducted to collect the in-store and

City events are getting popular and are attracting a large number of people. This increase needs for methods and tools to provide stakeholders with crowd size information for crowd management purposes. Previous works proposed a large number of methods to count the crowd using different data in various contexts, but no methods proposed using social media images in city events and no datasets exist to

Weather events often force motorists to drive in unsafe conditions or alter travel plans. Both decisions are imbued with costs that drivers may minimize by developing adaptation behaviors that facilitate safe travel. This study examines motorist behavior in Tucson, where urban flash floods are potentially avoided by strategies such as changing the route or trip timing. A sample of 108 residents completed

Successful and sustained interventions to obtain travel behavior change would be achieved based on a thorough understanding of individual’s decision-making process on travel. To narrow the gap between the theory of planned behavior (TPB) and green travel behavior, this study extends classical TPB by accommodating the moderating effect of affective-cognitive congruence of attitudes. Based on a cluster

How should public transit agencies deliver mobility services in the era of shared mobility? Previous literature recommends that transit agencies actively build partnerships with mobility service companies from the private sector, yet public transit agencies are still in search of a solid empirical basis to help envision the consequences of doing so. This paper presents an effort to fill this gap by

To estimate impacts, support cost–benefit analyses, and enable project prioritization, it is necessary to identify the area of influence of a transportation infrastructure project. For freight related projects, like ports, state-of-the-practice methods to estimate such areas ignore complex interactions among multimodal supply chains and can be improved by examining the multimodal trips made to and

Rural areas in low-income countries often face severe poverty typically caused by insufficient accessibility to basic facilities. Improvements in rural roads are expected to reduce poverty although the mechanism has not been investigated sufficiently. This study empirically analyzes the impacts of rural road improvements implemented from 2012 to 2014 in Cambodia, highlighting local residents’ accessibility

The ubiquity of personal cellular phones in society has led to a surging interest in using Big Data generated by mobile phones in transport research. Studies have suggested that the vast amount of data could be used to estimate origin–destination (OD) matrices, thereby potentially replacing traditional data sources such as travel surveys. However, constructing OD matrices from mobile phone data (MPD)

In upcoming years, the introduction of autonomous vehicles (AVs) will reshape the transport system. The transition from a regular to an autonomous transport system, however, will take place over many years and lead to a long period with a mixed driving environment where AVs and regular vehicles (RVs) operate side by side. The purpose of this study is to investigate how the utilisation of the road capacity

This paper studies the impact of removing the level crossing, which constitutes traffic hazard to the society, on house prices by conducting a quasi-natural experiment using the Level Crossing Removal Project (LXRP) implemented by the Victoria state government in Australia since 2015. Using a difference-in-differences method, we analyzed the changes in housing prices due to the improvement of transportation

Previous choice studies have proposed a way to condition the utility of each alternative in a choice set on experience with the alternatives accumulated over previous periods, defined either as a mode used or not in a most recent trip, or the mode chosen in their most recent trip and the number of similar one-way trips made during the last week. The paper found that the overall statistical performance

This study aims to suggest a three-phased methodological framework based on the operational approach of quality function deployment (QFD) to improve the service quality and passenger satisfaction with China’s high-speed rail (HSR) by identifying the key passenger needs with regard the HSR seats. For the first phase, the collection of the voice of the customers/passengers (VOC), the processing of the

Like many cities across North America, Montréal has experienced shrinking bus ridership over recent years. Most literature has focused on the broader causes for ridership decline at the metropolitan or city level; few have considered ridership at the route level, particularly while accounting for various operational attributes and accessibility-to-jobs issues. Because service adjustments take place—and

The emerging technology of autonomous vehicles has been widely recognized as a promising urban mobility solution in the future. This paper considers the integration of autonomous vehicles into bus transit systems and proposes a modeling framework to determine the optimal bus fleet size and its assignment onto multiple bus lines in a bus service network considering uncertain demand. The mixed-integer

One of the reasons to subsidise public transport is to improve the mobility of low-income groups by providing affordable public transport; however, the literature describes a situation whereby those with a low income are unable to afford the cheapest tickets per trip, i.e. travelcards, as they usually require a considerable up-front cost. In this study, we use a large dataset from the Swedish National

This study attempts to develop a comprehensive framework by integrating the theory of planned behavior (TPB) and latent class choice model, with aim to understanding how mode-use habits moderate the process underlying commute mode choice. By designating habit as the covariate in the class membership model, three segments with unique mode-use habit style are obtained. First, heterogeneity in the effects

Self-driving cars are expected to be integrated into the traffic system in the near future. It is crucial to understand how the public accepts self-driving cars and how adoption rates are influenced. The main purpose of this study was to investigate how trait anxiety and the Big Five personality traits affect acceptance and to provide a personality profile of early adopters of self-driving cars. A

A considerable number of empirical studies have explored the effects of information & communication technologies (ICT) on travel in recent years. In particular, the most attention has been paid to whether the use of ICT increases or decreases trip frequency (i.e., substitution or complementarity effects). However, the subject of whether or how travel distance and mode choice are altered by ICT (i.e

In this paper, a method to study travel behaviour dynamics by constructing detailed synthetic pseudo panels from repeated cross-sectional data is presented. The method is based on the modelling of a high-dimensional joint distribution of travel preferences conditional on detailed socio-economic profiles by using a conditional variational autoencoder (CVAE). The CVAE is a neural-network-based generative

The mediation of work practices by information and communication technologies enables knowledge workers to telework from remote non-office locations such as their homes, or to work nomadically from multiple locations in a day. This paper uses data from the American Time Use Survey to explore the relationship between daily work locations and travel in the United States from 2003 to 2017. Outcome variables

A sharing logistics platform for less-than-truckloads could increase efficiency in city pickup and last-mile deliveries under time window constraints by pairing (matching) truck bidders and last-mile logistics requesters. The platform will propose new tours based on localization data, travel time and time-window constraints; it operates a matching algorithm to search for stable truck-sharing deals

Given the limitations of traditional methods of data collection and the increased use of smartphones, there is growing attention given to using smartphone apps for activity-travel surveys. Smartphones, through their location-logging capability, allow for the collection of high-quality data on the travel patterns of individuals over multiple days while minimizing the burden on those being monitored

Everyday commuting as a mobility phenomenon is well-investigated and has been the topic of many contributions. Nevertheless, the distinct determinants of the commuting professional’s motivation to regularly travel comparably long distances have not been in the focus of research yet. Thus, this contribution analyses the sociodemographic variables that underpin the well-educated group’s decision to commute

Transportation vulnerability, defined as lack of access to transportation resulting in financial, social, or health consequences, reduces quality of life. While research has focused on the relationship between transportation vulnerability and the built environment among adults, youth have received less attention. This study examined the association between transportation vulnerability and school attendance

In-vehicle crowding on public transportation is a serious problem that transportation planners must address. Recent studies have emphasized that in-vehicle crowding impacts travelers’ stress and health, while other studies have investigated how daily travel affects subjective well-being (SWB). Based on the findings of these studies, we provide useful insights into the value of a reduction in crowding

This paper formulates a spatial autoregressive zero-inflated negative binomial model for freight trip productions and attractions. The model captures the following freight trip characteristics: count data type, positive trip rates, overdispersion, zero-inflation, and spatial autocorrelation. The spatial autoregressive structure is applied in the negative binomial part of the models to obtain unbiased

In this paper, two public information campaigns were analysed. These were related to capacity reductions, caused by maintenance work, in two main road tunnels—at Smestad and Bryn in Oslo. The paper analyses the campaigns’ characteristics and their goal fulfilment. The usage of social media to inform and communicate with travelers and inhabitants is highlighted. We find a high level of outreach of the

Traditional approaches to travel behaviour modelling primarily rely on household travel survey data, which is expensive to collect, resulting in small sample sizes and infrequent updates. Furthermore, such data is prone to reporting errors which can lead to biased parameter estimates and subsequently incorrect predictions. On the other hand, mobile phone call detail records (CDRs), which report the

This study examines changes in activity-travel patterns of employed people during a recession by using a tour-based representation of the activity-based approach. The term tour is defined as a sequence of trips and activities that begins and ends at home and contains at least one non-home activity. Tours are classified based on the presence of work and/or non-work activities. We are interested in investigating

Studies have applied single-reference-point or safety margin hypotheses to examine how advanced traveler information affects travel behaviors. However, these theories may fail to fully capture the trade-offs among origin departure time, airport access time, and terminal processing time in terms of airport ground access behaviors. In this study, we developed a tri-reference-point hypothesis and assumed

Ride-hailing (ridesourcing) companies such as Uber, Lyft, and Didi Chuxing have been a disruptive force in the urban mobility landscape around the world during the past decade. In this paper, we analyse the working conditions, earnings, and job satisfaction of ride-hailing drivers. We begin by discussing the regulatory, labour, financial, and urban mobility effects of ride-hailing companies. Then,

Inferring trip destination in smart card data with only tap-in control is an important application. Most existing methods estimate trip destinations based on the continuity of trip chains, while the destinations of isolated/unlinked trips cannot be properly handled. We address this problem with a probabilistic topic model. A three-dimensional latent dirichlet allocation model is developed to extract

Local and regional governments in the U.S. rely increasingly on voter-approved local option sales taxes (LOSTs) to fund transportation capital investments, maintenance, and operations. LOSTs typically present voters with lists of local transportation projects and programs to be funded by a ¼ to 1 percent sales tax increase. Most research on LOSTs are case studies, which make generalizations about LOSTs

Transport systems in China face extreme capacity shortages during the Spring Festival travel season. This study therefore explores traveler’s decision making behavior when booking tickets during this season for a specific origin destination relation. Data are obtained from a mixed RP/SP survey that reflects the ticketing policy in China. Loop questions are programmed inside the questionnaire to investigate

Numerous studies have found that travel attitudes might not only affect travel behavior, but also the residential location choice as people might choose a residential location based on their travel preferences and needs (i.e. transport-related residential self-selection). However, it might also be possible that the residential location and travel behavior influence attitudes towards travel. In this

Endogeneity is a potential anomaly in econometric models, which may cause inconsistent parameter estimates. Transport models are prone to this problem and applications that properly correct for it are scarce. This paper focuses on how to address this issue in the case of strategic urban mode choice models (i.e., the third stage of classic strategic transport models), possibly the main tool for the

Exploiting the full potential of pedestrian infrastructure is becoming critical in many environments which cannot be easily expanded to cope with the increasing pedestrian demand. This is particularly true for train stations as in many dense cities space is limited and expansion is difficult and very costly. In this paper, we investigate how to improve the level-of-service experienced by pedestrians

Simulation studies suggest that pooled on-demand services (also referred to as Demand Responsive Transport, ridesharing, shared ride-hailing or shared ridesourcing services) have the potential to bring large benefits to urban areas while inducing limited time losses for their users. However, in reality, the large majority of users request individual rides (and not pooled rides) in existing on-demand

The limited endurance mileage of battery electric vehicles (BEVs) affects mode choice of commuters inevitably. To help facilitate BEV charging and improve accessibility of transit stations, the park-charge-ride (PCR) services have been implemented in some cities. This study develops a deterministic continuum equilibrium model for a monocentric city to analyze the modal choice behavior of commuters

Ridesharing is the sharing of trip segments from one place to another among multiple travelers, obviating others’ needs to drive themselves. By having more than one occupant sharing a vehicle, ridesharing aims to reduce personal resources and costs, such as fuel and trip-related costs, and driver stress. The objective of this paper is to model the social preferences of rideshare passengers. We identify

Mobility as a service (MaaS) promises a bold new future where bundled public transport and shared mobility options (carsharing, ridesharing, bikesharing and microtransit) will provide consumers with seamless mobility on par with and exceeding that of private vehicle ownership. Whilst there is a growing body of work examining the market and end user demand for MaaS, there remains a limited understanding

This paper exploits some latest advances in structural equation modelling and latent class analysis for identification and mapping of the spatial variations in travel choices. The approach controls for a wide range of socioeconomic and demographic variables and changes in car fuel prices. The research is focused on employed and self-employed adults, and the method can be readily extended to cover other

Disruptions in public transport can have major implications for passengers and service providers. Our study objective is to develop a generic approach to predict how often different disruption types occur at different stations of a public transport network, and to predict the impact related to these disruptions as measured in terms of passenger delays. We propose a supervised learning approach to perform

Autonomous vehicle (AV) technologies are under constant improvement with pilot programs now underway in several urban areas worldwide. Modeling and field-testing efforts are demonstrating that shared mobility coupled with AV technology for automated mobility on-demand (AMoD) service may significantly impact levels of service and environmental outcomes in future cities. Given these rapidly emerging

Spatiotemporal data, and more specifically origin–destination matrices, are critical inputs to mobility studies for transportation planning and urban management purposes. Traditionally, high-cost and hard-to-update household travel surveys are used to produce large-scale origin–destination flow information of individuals’ whereabouts. In this paper, we propose a methodology to estimate origin–destination

Travel time reliability has been recognized as an important factor in cost–benefit analysis in a transportation network. To estimate the benefit and cost of travel time reliability, several network models have been proposed to estimate the monetary values both of travel time and of travel time reliability based on the driver’s route choice behavior. In this study, we propose a network model that addresses

This paper examines the opportunities for addressing evacuations by leveraging the sharing economy. To support this research, we use a mixed-method approach employing archival research of sharing economy actions, 24 high-ranking expert interviews, and a survey of individuals impacted by Hurricane Irma in 2017 (n = 645). Using these data, we contribute to the literature in four key ways. First, we summarize

China’s low-cost carriers (LCCs) are poised for fast growth, thanks to the changing competition dynamics and aviation policies in the domestic market. This new trend calls for an in-depth investigation of the characteristics and behavioral intentions of LCC passengers. In particular, passenger demographics must be carefully considered given the likely demographic diversity in China’s emerging LCC market

Activity sequencing is a crucial component of disaggregate modeling approaches. This paper presents a methodology to analyse and predict activity sequence patterns for persons based on their socio-demographic attributes. The model is developed using household travel survey data from Germany. The presented method proposes an efficient approach to replace complex activity-scheduling modules in activity-based

This study advances understanding of the role of residential location in joint household travel and activities for non-work purposes in an Asian city context. This has been done by investigating the relationship between job accessibility, and the undertaking and duration of joint travel and activities of multi-person households in Hong Kong. Particular attention was given to the difference between

Bike-sharing systems have been popular in addressing the “last mile” problem in public transit. However, service providers have found challenges when soliciting travellers to shift from their private vehicles: more stations do not always mean higher switching by private vehicle users. Considering the possible non-linear relationship between service provision and intention to use, this study utilises

Going beyond the traditional business to consumer air transport passenger perspective, this paper examines what we can learn from combining transaction marketing (TM) and relationship marketing (RM) orientations in respect to customer loyalty in the context of business to business (B2B) freight transportation markets. We model and examine post-transactional air freight express (integrator) customer