Pub Date : 2025-12-14DOI: 10.1016/j.tbs.2025.101168
Yantao Huang, Natalia Zuniga-Garcia, Kara M. Kockelman
This study assesses long-distance (LD) travel demand in near-future scenarios where automated vehicles (AVs) are easily available. Stated and revealed preference data were obtained from 1,004 American adults. The survey includes questions about general LD trip-making behavior with AVs, after investigating the possibility of using AVs to substitute for respondents’ recent LD trips (over 75-miles one-way) prior to the COVID-19 pandemic. After cleaning and weighting the responses, respondents’ willingness to use AVs for a past LD trip are shared, and their future travel behaviors with AVs are explored via statistical models. Ordered logit regression model results suggest AVs would increase the trip-making frequency of high-income households, households with more children, and young people who are part-time employed. The multinomial logit model for overnight stopping suggests that high-income travelers prefer staying overnight in hotels, while young and solo-drivers are expected to more often stay overnight in moving AVs. Mornings departures are preferred for LD travel - both with and without AVs, but some travelers shift to later departures when AVs become available, particularly those who are employed full-time and/or have more children in their household. Results of the mode choice model for mid-range LD travel (200 to 500 miles) suggest those who are unmarried and/or employed full time prefer AVs, while those over age 65 do not. Car and AV cost are the most practically significant variables impacting people’s mode choices, and aircraft and AVs are more appealing than human-driven vehicles for trips over 500 miles long.
{"title":"Long-distance travel impacts of automated vehicles: A survey of American households","authors":"Yantao Huang, Natalia Zuniga-Garcia, Kara M. Kockelman","doi":"10.1016/j.tbs.2025.101168","DOIUrl":"https://doi.org/10.1016/j.tbs.2025.101168","url":null,"abstract":"This study assesses long-distance (LD) travel demand in near-future scenarios where automated vehicles (AVs) are easily available. Stated and revealed preference data were obtained from 1,004 American adults. The survey includes questions about general LD trip-making behavior with AVs, after investigating the possibility of using AVs to substitute for respondents’ recent LD trips (over 75-miles one-way) prior to the COVID-19 pandemic. After cleaning and weighting the responses, respondents’ willingness to use AVs for a past LD trip are shared, and their future travel behaviors with AVs are explored via statistical models. Ordered logit regression model results suggest AVs would increase the trip-making frequency of high-income households, households with more children, and young people who are part-time employed. The multinomial logit model for overnight stopping suggests that high-income travelers prefer staying overnight in hotels, while young and solo-drivers are expected to more often stay overnight in moving AVs. Mornings departures are preferred for LD travel - both with and without AVs, but some travelers shift to later departures when AVs become available, particularly those who are employed full-time and/or have more children in their household. Results of the mode choice model for mid-range LD travel (200 to 500 miles) suggest those who are unmarried and/or employed full time prefer AVs, while those over age 65 do not. Car and AV cost are the most practically significant variables impacting people’s mode choices, and aircraft and AVs are more appealing than human-driven vehicles for trips over 500 miles long.","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"93 1","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145759417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-13DOI: 10.1016/j.tbs.2025.101212
Anastasios Skoufas, Erik Jenelius
Public transportation (PT) plays a crucial role in catering to the mobility needs of school students. However, the disparities of PT travel characteristics among different socioeconomic groups have been underexplored. In this study, we explore disparities in PT usage, after-school activity participation, journey length, and on-board crowding among different socioeconomic groups as well as between different educational stages (primary, secondary). We specifically focus on home-to-school and school-to-activity PT journeys utilizing automated data sources (smart card data). Results from the case study of Region Stockholm show that travel time and crowding exposure vary across the case study area. Specifically, school students coming from areas with higher income levels, higher shares of cooperative housing, or lower vehicle ownership tend to need less time to travel to school. In terms of student categorization, secondary students with diverse socioeconomic backgrounds tend to travel longer to school compared to primary students. Concerning journeys to after-school activities using PT, results reveal that school students from areas with high vehicle ownership and education or lower employment levels, as well as students from suburban/rural areas, have lower odds of using PT. The findings can assist policy makers and PT agencies in designing more equitable and youth-friendly PT systems, improving access to schools and to after-school activity locations.
{"title":"Youths on the move: Social disparities in public transportation use among school students","authors":"Anastasios Skoufas, Erik Jenelius","doi":"10.1016/j.tbs.2025.101212","DOIUrl":"10.1016/j.tbs.2025.101212","url":null,"abstract":"<div><div>Public transportation (PT) plays a crucial role in catering to the mobility needs of school students. However, the disparities of PT travel characteristics among different socioeconomic groups have been underexplored. In this study, we explore disparities in PT usage, after-school activity participation, journey length, and on-board crowding among different socioeconomic groups as well as between different educational stages (primary, secondary). We specifically focus on <em>home-to-school</em> and <em>school-to-activity</em> PT journeys utilizing automated data sources (smart card data). Results from the case study of Region Stockholm show that travel time and crowding exposure vary across the case study area. Specifically, school students coming from areas with higher income levels, higher shares of cooperative housing, or lower vehicle ownership tend to need less time to travel to school. In terms of student categorization, secondary students with diverse socioeconomic backgrounds tend to travel longer to school compared to primary students. Concerning journeys to after-school activities using PT, results reveal that school students from areas with high vehicle ownership and education or lower employment levels, as well as students from suburban/rural areas, have lower odds of using PT. The findings can assist policy makers and PT agencies in designing more equitable and youth-friendly PT systems, improving access to schools and to after-school activity locations.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101212"},"PeriodicalIF":5.7,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145732696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-11DOI: 10.1016/j.tbs.2025.101201
Zijian Yang , Guocong Zhai , N.N. Sze , Hongliang Ding , Nikolai Bobylev , Hongtai Yang
Numerous studies have examined the effectiveness of urban transportation planning policies such as park-and-ride, transit-oriented development, and multimodal transportation hubs in promoting public transit use. In the past decades, bike sharing, both dockless and docking systems, has been increasingly popular as a green transport mode, connecting to public transit. However, the influence of socioeconomic conditions, land-use factors, transport infrastructure, and station characteristics on bike-and-ride remains underexplored, particularly across different patterns of bike-and-ride. In this study, an integrated random forest (RF) and geographically weighted regression (GWR) model is applied to capture nonlinear relationships and spatial heterogeneity between bike-and-ride usage and explanatory variables, including socioeconomic variables, land-use factors, transportation infrastructure, and metro characteristics, based on the integrated bike sharing and metro ridership data in Chengdu, China. Additionally, a novel similarity metric, Dynamic Time Warping (DTW), is applied to classify the metro stations based on the temporal pattern of bike-and-ride trips at all stations. Hence, four clusters of metro stations with a varying pattern of bike-and-ride trips are established. The results show that the importance of determinants and their association with bike-and-ride vary significantly among different clusters of metro stations. This study proposes a fine-grained analytical framework for bike-and-ride, providing theoretical and empirical support for station function classification.
许多研究已经检验了城市交通规划政策的有效性，如停车换乘、交通导向发展和多式联运枢纽，以促进公共交通的使用。在过去的几十年里，共享单车作为一种连接公共交通的绿色交通方式，无论是无桩还是有坞系统，都越来越受欢迎。然而，社会经济条件、土地利用因素、交通基础设施和车站特征对自行车骑行的影响仍未得到充分探讨，特别是在不同的自行车骑行模式中。本文基于成都市共享单车和地铁出行数据，采用随机森林（RF）和地理加权回归（GWR）模型，分析了共享单车使用与社会经济变量、土地利用因子、交通基础设施和地铁特征等解释变量之间的非线性关系和空间异质性。在此基础上，提出了一种新的相似性度量——动态时间扭曲（Dynamic Time Warping， DTW），基于各车站的骑车出行时间模式对地铁站进行分类。因此，建立了四个具有不同模式的自行车和骑行的地铁站群。结果表明，在不同的地铁车站群中，决定因素的重要性及其与骑车出行的关系存在显著差异。本研究提出了自行车骑行的细粒度分析框架，为车站功能分类提供理论和实证支持。
{"title":"Exploring different patterns of bike-and-ride trips and influencing factors using geographically weighted random forest","authors":"Zijian Yang , Guocong Zhai , N.N. Sze , Hongliang Ding , Nikolai Bobylev , Hongtai Yang","doi":"10.1016/j.tbs.2025.101201","DOIUrl":"10.1016/j.tbs.2025.101201","url":null,"abstract":"<div><div>Numerous studies have examined the effectiveness of urban transportation planning policies such as park-and-ride, transit-oriented development, and multimodal transportation hubs in promoting public transit use. In the past decades, bike sharing, both dockless and docking systems, has been increasingly popular as a green transport mode, connecting to public transit. However, the influence of socioeconomic conditions, land-use factors, transport infrastructure, and station characteristics on bike-and-ride remains underexplored, particularly across different patterns of bike-and-ride. In this study, an integrated random forest (RF) and geographically weighted regression (GWR) model is applied to capture nonlinear relationships and spatial heterogeneity between bike-and-ride usage and explanatory variables, including socioeconomic variables, land-use factors, transportation infrastructure, and metro characteristics, based on the integrated bike sharing and metro ridership data in Chengdu, China. Additionally, a novel similarity metric, Dynamic Time Warping (DTW), is applied to classify the metro stations based on the temporal pattern of bike-and-ride trips at all stations. Hence, four clusters of metro stations with a varying pattern of bike-and-ride trips are established. The results show that the importance of determinants and their association with bike-and-ride vary significantly among different clusters of metro stations. This study proposes a fine-grained analytical framework for bike-and-ride, providing theoretical and empirical support for station function classification.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101201"},"PeriodicalIF":5.7,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-10DOI: 10.1016/j.tbs.2025.101210
Vladimir Maksimenko , Liting Yuan , Prateek Bansal
Due to limited historical data on interactions of pedestrians with autonomous vehicles (AVs), researchers commonly use stated preference experiments to study pedestrians’ perceived ease of interactions with AVs. Virtual reality implemented via head-mounted displays (HMDs) provides a three-dimensional representation of pedestrian–AV encounters that may enhance realism and elicit responses similar to those in real life. However, the mechanisms by which HMDs confer this advantage remain unclear. To this end, we systematically compare HMD-based and monitor-based experimental formats in their ability to capture behavioral, physiological (i.e., stress biomarkers), psychological (i.e., brain data), and self-reported measures of pedestrian-AV interaction. In a controlled within-subject design, we find that in the HMD condition, pedestrians’ initial trust in AVs translates into statistically detectable differences across these measures while pedestrians interact with AVs and human-driven vehicles; by contrast, the monitor-based condition, tested with the same participants and identical stimuli, fails to detect such effects. The greater immersion in the HMD condition is further supported by a higher propensity to look around (behavioral measure) and by increased cognitive load derived from neurophysiological signals, both of which indicate enhanced perceptual realism. These results underscore the value of immersive 3D experiments for studying pedestrian-AV interaction over 2D picture/video-based experiments.
{"title":"Do Pedestrians Respond Differently to Perceived Vehicle Automation in Monitor-based and Head-Mounted immersive Experiments?","authors":"Vladimir Maksimenko , Liting Yuan , Prateek Bansal","doi":"10.1016/j.tbs.2025.101210","DOIUrl":"10.1016/j.tbs.2025.101210","url":null,"abstract":"<div><div>Due to limited historical data on interactions of pedestrians with autonomous vehicles (AVs), researchers commonly use stated preference experiments to study pedestrians’ perceived ease of interactions with AVs. Virtual reality implemented via head-mounted displays (HMDs) provides a three-dimensional representation of pedestrian–AV encounters that may enhance realism and elicit responses similar to those in real life. However, the mechanisms by which HMDs confer this advantage remain unclear. To this end, we systematically compare HMD-based and monitor-based experimental formats in their ability to capture behavioral, physiological (i.e., stress biomarkers), psychological (i.e., brain data), and self-reported measures of pedestrian-AV interaction. In a controlled within-subject design, we find that in the HMD condition, pedestrians’ initial trust in AVs translates into statistically detectable differences across these measures while pedestrians interact with AVs and human-driven vehicles; by contrast, the monitor-based condition, tested with the same participants and identical stimuli, fails to detect such effects. The greater immersion in the HMD condition is further supported by a higher propensity to look around (behavioral measure) and by increased cognitive load derived from neurophysiological signals, both of which indicate enhanced perceptual realism. These results underscore the value of immersive 3D experiments for studying pedestrian-AV interaction over 2D picture/video-based experiments.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101210"},"PeriodicalIF":5.7,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145730668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-10DOI: 10.1016/j.tbs.2025.101202
Hongxia Yuan , Zhongquan Qiu , Han Xu , Renbin Pan , Yusong Yan
Uneven crowding across metro networks, where some lines are severely congested while others remain underutilized, undermines passenger satisfaction and network efficiency. This study examines the potential of coordinated feeder bus services to divert passengers from overcrowded to less crowded lines, using Chengdu, China, as a case study. To assess passenger willingness to switch and capture preference heterogeneity, a stated preference experiment and latent class model were applied under scenarios where the current travel mode was either metro-walking or metro-bus. Two passenger classes were identified. Class A comprised mainly frequent commuters who used the metro at least three days per week. They were highly responsive to service attributes, willing to accept substantially longer metro travel to avoid crowding and transfers, moderate extensions to reduce cost, but only minimal increases in walking or bus access time. Class B, comprising low-frequency, off-peak, and non-commuting passengers, displayed strong inertia and switched only with clear improvements in comfort or walking access. Across scenarios, Class A, particularly metro-bus commuters facing severe crowding and multiple transfers, emerged as the group most likely to switch. Elasticity and sensitivity analyses for Class A further revealed that more severe crowding or transfers on the current route produce stronger switching effects: as crowding intensifies, larger discounts are required to divert passengers to worse alternatives, whereas only modest or no incentives suffice to attract them to better ones. Overall, the findings provide robust evidence that improving feeder bus accessibility can encourage commuters to shift to less crowded metro lines, particularly when combined with service enhancements and targeted incentives.
{"title":"Who is willing to switch to a less-crowded metro route via feeder bus connections? A case study in Chengdu, China","authors":"Hongxia Yuan , Zhongquan Qiu , Han Xu , Renbin Pan , Yusong Yan","doi":"10.1016/j.tbs.2025.101202","DOIUrl":"10.1016/j.tbs.2025.101202","url":null,"abstract":"<div><div>Uneven crowding across metro networks, where some lines are severely congested while others remain underutilized, undermines passenger satisfaction and network efficiency. This study examines the potential of coordinated feeder bus services to divert passengers from overcrowded to less crowded lines, using Chengdu, China, as a case study. To assess passenger willingness to switch and capture preference heterogeneity, a stated preference experiment and latent class model were applied under scenarios where the current travel mode was either metro-walking or metro-bus. Two passenger classes were identified. Class A comprised mainly frequent commuters who used the metro at least three days per week. They were highly responsive to service attributes, willing to accept substantially longer metro travel to avoid crowding and transfers, moderate extensions to reduce cost, but only minimal increases in walking or bus access time. Class B, comprising low-frequency, off-peak, and non-commuting passengers, displayed strong inertia and switched only with clear improvements in comfort or walking access. Across scenarios, Class A, particularly metro-bus commuters facing severe crowding and multiple transfers, emerged as the group most likely to switch. Elasticity and sensitivity analyses for Class A further revealed that more severe crowding or transfers on the current route produce stronger switching effects: as crowding intensifies, larger discounts are required to divert passengers to worse alternatives, whereas only modest or no incentives suffice to attract them to better ones. Overall, the findings provide robust evidence that improving feeder bus accessibility can encourage commuters to shift to less crowded metro lines, particularly when combined with service enhancements and targeted incentives.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101202"},"PeriodicalIF":5.7,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-08DOI: 10.1016/j.tbs.2025.101197
Yanyan Xu, Panchamy Krishnakumari, Neil Yorke-Smith, Serge Hoogendoorn
This article proposes an evidence-based policy recommendation framework integrating social media data and natural language processing methods, to support inclusive and efficient transport policy-making. Given that current research underscores the crucial role of both external and psychological variables in individual travel decisions, psychological features – such as beliefs, attitudes or values – are frequently used as latent variables for travel behaviour interpretation and travel choice modelling. However, user-centric policy recommendations based on dynamic psychological variables are still limited. Most studies rely on survey data, which neglects the urgent dynamic trend of user perception change and its underlying relationship with travel behaviour. Hence there is a lack of illustration on how these psychological variables can be further used at specific temporal and spatial levels for travel behaviour interpretation. This would be valuable to identify priorities for more targeted (sustainability and other) policies and interventions. In this article, we utilize sentiment analysis and dynamic topic modelling to represent the spatial–temporal variance of psychological features. Integrating with corresponding travel behaviour, we illustrate how these dynamic psychological features can distinguish travel dissonance, identify key motivations, and reflect urgent social demands at precise spatial–temporal levels. We demonstrate these advances in a case study in New York City from 2019 to 2022 using Twitter (X) data. A comparison with existing travel-related policies in the case study validates the feasibility of our framework to support evidence-based policy recommendations. We conclude by discussing the potential of this framework to support sustainable transport promotion.
{"title":"Extracting socio-psychological perceptions for analysis of travel behaviours","authors":"Yanyan Xu, Panchamy Krishnakumari, Neil Yorke-Smith, Serge Hoogendoorn","doi":"10.1016/j.tbs.2025.101197","DOIUrl":"10.1016/j.tbs.2025.101197","url":null,"abstract":"<div><div>This article proposes an evidence-based policy recommendation framework integrating social media data and natural language processing methods, to support inclusive and efficient transport policy-making. Given that current research underscores the crucial role of both external and psychological variables in individual travel decisions, psychological features – such as beliefs, attitudes or values – are frequently used as latent variables for travel behaviour interpretation and travel choice modelling. However, user-centric policy recommendations based on dynamic psychological variables are still limited. Most studies rely on survey data, which neglects the urgent dynamic trend of user perception change and its underlying relationship with travel behaviour. Hence there is a lack of illustration on how these psychological variables can be further used at specific temporal and spatial levels for travel behaviour interpretation. This would be valuable to identify priorities for more targeted (sustainability and other) policies and interventions. In this article, we utilize sentiment analysis and dynamic topic modelling to represent the spatial–temporal variance of psychological features. Integrating with corresponding travel behaviour, we illustrate how these dynamic psychological features can distinguish travel dissonance, identify key motivations, and reflect urgent social demands at precise spatial–temporal levels. We demonstrate these advances in a case study in New York City from 2019 to 2022 using Twitter (X) data. A comparison with existing travel-related policies in the case study validates the feasibility of our framework to support evidence-based policy recommendations. We conclude by discussing the potential of this framework to support sustainable transport promotion.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101197"},"PeriodicalIF":5.7,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145732698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-08DOI: 10.1016/j.tbs.2025.101209
Yongtao Liu , Jing Feng , Dongdong Song , Yitao Yang , Danyue Zhi , Huan Pang , Deyin Jiang , Shifeng Niu
Hazard-based duration models have gained popularity in predicting traffic incident durations. However, most studies analyze congestion duration as a whole, overlooking the varying levels of congestion (minor, moderate, and severe), which may be interrelated and influenced by different factors. This study proposes multivariate joint survival analysis models to examine the relationships across these congestion levels using traffic incident data from New York State (2017–2019), treating minor and moderate congestion as recurrent events, with severe congestion as a terminal event. By incorporating a frailty term, unobserved heterogeneity among road segments is accounted for. The results show that real-time weather factors, such as temperature, wind speed, visibility, and precipitation (rain/snowfall), exhibit varying effects on the duration of different congestion levels, with these effects fluctuating over time. For example, in 2017–2019, low temperatures increase the duration of minor congestion by 40.88 %, 26.66 %, and 52.69 %, respectively. Conversely, for severe congestion, low temperatures also show stable temporal effects but reduce congestion duration by 70.81 %, 60.07 %, and 70.81 %, respectively. Rainy weather increases the duration of moderate congestion by 54.10 %, 31.94 %, and 54.10 %, respectively, while snowy weather reduces it by 41.38 %, 37.19 %, and 27.48 %. More importantly, a significant correlation is found between minor or moderate congestion, which are recurrent events, and severe congestion, the terminal event. Furthermore, a positive correlation between minor and moderate congestion suggests that unobserved factors jointly influence the duration of both. The study confirms the superiority of the proposed joint model for analyzing traffic incident duration and provides practical insights for transportation policymakers to massively ease congestion more effectively.
{"title":"Exploring weather-related factors affecting the duration of multiple congestion levels caused by traffic incidents using a multivariate joint frailty survival model","authors":"Yongtao Liu , Jing Feng , Dongdong Song , Yitao Yang , Danyue Zhi , Huan Pang , Deyin Jiang , Shifeng Niu","doi":"10.1016/j.tbs.2025.101209","DOIUrl":"10.1016/j.tbs.2025.101209","url":null,"abstract":"<div><div>Hazard-based duration models have gained popularity in predicting traffic incident durations. However, most studies analyze congestion duration as a whole, overlooking the varying levels of congestion (minor, moderate, and severe), which may be interrelated and influenced by different factors. This study proposes multivariate joint survival analysis models to examine the relationships across these congestion levels using traffic incident data from New York State (2017–2019), treating minor and moderate congestion as recurrent events, with severe congestion as a terminal event. By incorporating a frailty term, unobserved heterogeneity among road segments is accounted for. The results show that real-time weather factors, such as temperature, wind speed, visibility, and precipitation (rain/snowfall), exhibit varying effects on the duration of different congestion levels, with these effects fluctuating over time. For example, in 2017–2019, low temperatures increase the duration of minor congestion by 40.88 %, 26.66 %, and 52.69 %, respectively. Conversely, for severe congestion, low temperatures also show stable temporal effects but reduce congestion duration by 70.81 %, 60.07 %, and 70.81 %, respectively. Rainy weather increases the duration of moderate congestion by 54.10 %, 31.94 %, and 54.10 %, respectively, while snowy weather reduces it by 41.38 %, 37.19 %, and 27.48 %. More importantly, a significant correlation is found between minor or moderate congestion, which are recurrent events, and severe congestion, the terminal event. Furthermore, a positive correlation between minor and moderate congestion suggests that unobserved factors jointly influence the duration of both. The study confirms the superiority of the proposed joint model for analyzing traffic incident duration and provides practical insights for transportation policymakers to massively ease congestion more effectively.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101209"},"PeriodicalIF":5.7,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145732697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-03DOI: 10.1016/j.tbs.2025.101208
Meng Guo , Jianing Liu , Sisi Jian , Zheng Li , Gang Ren , Chenyang Wu
As a noteworthy example of subscription-based service in transportation, Mobility-as-a-Service (MaaS) provides seamless and integrated multimodal travel solutions through bundles, encouraging travelers to transition from private modes to sustainable travel options. While previous studies have primarily focused on the impact of MaaS bundles on mode preferences, the complicated and extensive MaaS-induced behavioral changes and their evolving impact have been overlooked. This study addresses this gap by investigating changes in users’ subscriptions and travel choices with accumulated virtual experience of MaaS bundle usage. Combining stated choice experiments and experimental economics, we conduct a four-part multimodal travel experiment targeting commuters, offering an engaging environment where participants make sequential decisions comprising MaaS bundle subscriptions and travel mode choices. Dynamic discrete choice models are formulated to calibrate participants’ dynamic decision-making processes under MaaS bundle subscriptions and behavioral changes over multiple virtual periods. The results indicate that the virtual experience of subscribing to a particular bundle would motivate them to subscribe to the same bundle again in subsequent periods. When MaaS subscribers make mode choices, their behavior is not simply making trade-offs between travel time and cost. Rather, they tend to consider the future use of their bundles fully, and they are more inclined to make travel decisions based on available bundle discounts. The impact of subscriptions is most pronounced in promoting ride-sourcing trips, followed by multimodal and single-mode public transportation options. These findings offer initial insights into the impact of MaaS subscriptions in reshaping traveler’ subscription and travel choices over a relatively longer period.
{"title":"How virtual experience reshapes commuters’ MaaS subscription and mode choice: Insights from an economic experiment","authors":"Meng Guo , Jianing Liu , Sisi Jian , Zheng Li , Gang Ren , Chenyang Wu","doi":"10.1016/j.tbs.2025.101208","DOIUrl":"10.1016/j.tbs.2025.101208","url":null,"abstract":"<div><div>As a noteworthy example of subscription-based service in transportation, Mobility-as-a-Service (MaaS) provides seamless and integrated multimodal travel solutions through bundles, encouraging travelers to transition from private modes to sustainable travel options. While previous studies have primarily focused on the impact of MaaS bundles on mode preferences, the complicated and extensive MaaS-induced behavioral changes and their evolving impact have been overlooked. This study addresses this gap by investigating changes in users’ subscriptions and travel choices with accumulated virtual experience of MaaS bundle usage. Combining stated choice experiments and experimental economics, we conduct a four-part multimodal travel experiment targeting commuters, offering an engaging environment where participants make sequential decisions comprising MaaS bundle subscriptions and travel mode choices. Dynamic discrete choice models are formulated to calibrate participants’ dynamic decision-making processes under MaaS bundle subscriptions and behavioral changes over multiple virtual periods. The results indicate that the virtual experience of subscribing to a particular bundle would motivate them to subscribe to the same bundle again in subsequent periods. When MaaS subscribers make mode choices, their behavior is not simply making trade-offs between travel time and cost. Rather, they tend to consider the future use of their bundles fully, and they are more inclined to make travel decisions based on available bundle discounts. The impact of subscriptions is most pronounced in promoting ride-sourcing trips, followed by multimodal and single-mode public transportation options. These findings offer initial insights into the impact of MaaS subscriptions in reshaping traveler’ subscription and travel choices over a relatively longer period.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101208"},"PeriodicalIF":5.7,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-02DOI: 10.1016/j.tbs.2025.101204
Luqi Dong , M.Baran Ulak , Luiza Gagno Azolin , Anna B. Grigolon , Mohamed Abouelela , Karst T. Geurs
Shared micromobility services (SMMS) can provide alternative travel options during disruptive conditions (e.g., public transport disruptions). This is defined as “option use”, indicating that people who don’t normally use shared micromobility can consider using it when their main mode is unavailable. However, not everyone can benefit from it due to barriers that limit access to these shared modes. Therefore, this study aims to examine and explain the use and option use of shared micromobility services. A combined revealed preference and stated choice survey was conducted in the Netherlands, and binary logit models were estimated. Our results indicate that option users are more likely to be Dutch, own private e-bikes, cars, and have advanced digital skills. Moreover, we found that respondents lacking advanced digital skills are unlikely to consider app-based shared modes (e.g., shared mopeds) as a backup option in disruptions, but do consider shared modes which do not require a smartphone.
{"title":"Factors affecting the use and option use of shared mopeds and bicycles: Evidence from Dutch metropolitan cities","authors":"Luqi Dong , M.Baran Ulak , Luiza Gagno Azolin , Anna B. Grigolon , Mohamed Abouelela , Karst T. Geurs","doi":"10.1016/j.tbs.2025.101204","DOIUrl":"10.1016/j.tbs.2025.101204","url":null,"abstract":"<div><div>Shared micromobility services (SMMS) can provide alternative travel options during disruptive conditions (e.g., public transport disruptions). This is defined as “option use”, indicating that people who don’t normally use shared micromobility can consider using it when their main mode is unavailable. However, not everyone can benefit from it due to barriers that limit access to these shared modes. Therefore, this study aims to examine and explain the use and option use of shared micromobility services. A combined revealed preference and stated choice survey was conducted in the Netherlands, and binary logit models were estimated. Our results indicate that option users are more likely to be Dutch, own private e-bikes, cars, and have advanced digital skills. Moreover, we found that respondents lacking advanced digital skills are unlikely to consider app-based shared modes (e.g., shared mopeds) as a backup option in disruptions, but do consider shared modes which do not require a smartphone.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101204"},"PeriodicalIF":5.7,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Traffic restrictions and the construction of cycling infrastructure are effective strategies to reduce private car use and promote active travel in urban areas. However, implementing these measures often involves reallocating existing street space, which can lead to public resistance. This study employed a Best-Worst-Scaling (BWS) profile case approach to examine preferences for different types of street space reallocation to encourage cycling and to explore how these preferences are influenced by psychological factors such as driver and cyclist identities, perceived infringement on freedom, and place attachment. A Britain-based sample of participants (N = 509) evaluated images depicting various configurations of bike lanes, traffic restrictions, and cycle parking, where road or pedestrian space was reallocated to accommodate cycling infrastructure. Participants identified the most and least preferred features of these designs. The findings indicate broad public support for cycling infrastructure and traffic restrictions, although preferences varied significantly across street layouts. Participants particularly opposed the removal of car parking and showed a strong preference for reallocating road space rather than pedestrian space. Both cyclists and drivers favoured segregated cycling infrastructure over painted bike lanes on roads. While place attachment had limited impact on preferences, perceptions of cycling infrastructure as infringing on individual freedom emerged as a significant factor shaping space reallocation preferences. These findings offer insights for policymakers and urban planners, highlighting design strategies that may be more publicly acceptable and identifying areas where resistance to urban redesigns is likely to emerge.
{"title":"Preferences for urban street space reallocation to encourage cycling: A Best-Worst Scaling profile case approach","authors":"Isabella Malet Lambert , Wouter Poortinga , Dimitris Potoglou , Dimitrios Xenias","doi":"10.1016/j.tbs.2025.101205","DOIUrl":"10.1016/j.tbs.2025.101205","url":null,"abstract":"<div><div>Traffic restrictions and the construction of cycling infrastructure are effective strategies to reduce private car use and promote active travel in urban areas. However, implementing these measures often involves reallocating existing street space, which can lead to public resistance. This study employed a Best-Worst-Scaling (BWS) profile case approach to examine preferences for different types of street space reallocation to encourage cycling and to explore how these preferences are influenced by psychological factors such as driver and cyclist identities, perceived infringement on freedom, and place attachment. A Britain-based sample of participants (N = 509) evaluated images depicting various configurations of bike lanes, traffic restrictions, and cycle parking, where road or pedestrian space was reallocated to accommodate cycling infrastructure. Participants identified the most and least preferred features of these designs. The findings indicate broad public support for cycling infrastructure and traffic restrictions, although preferences varied significantly across street layouts. Participants particularly opposed the removal of car parking and showed a strong preference for reallocating road space rather than pedestrian space. Both cyclists and drivers favoured segregated cycling infrastructure over painted bike lanes on roads. While place attachment had limited impact on preferences, perceptions of cycling infrastructure as infringing on individual freedom emerged as a significant factor shaping space reallocation preferences. These findings offer insights for policymakers and urban planners, highlighting design strategies that may be more publicly acceptable and identifying areas where resistance to urban redesigns is likely to emerge.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"43 ","pages":"Article 101205"},"PeriodicalIF":5.7,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：