Travel Behaviour and Society最新文献

{"title":"Neural integrated choice model with ParetoTail and Gaussian copula for travel behavior analysis","authors":"Yue Liu,&nbsp;Guohua Liang,&nbsp;Ziyu Chen,&nbsp;Zhixiang Gao","doi":"10.1016/j.tbs.2026.101252","DOIUrl":"10.1016/j.tbs.2026.101252","url":null,"abstract":"<div><div>Travel behavior modeling is essential for transportation demand analysis and policy-making, yet traditional discrete choice models often struggle with real-world data complexities, such as heavy-tailed distributions and strong feature correlations. This study proposes a novel neural network framework integrated with advanced statistical techniques to effectively address these issues. Specifically, a ParetoTail transformation is employed to normalize heavy-tailed travel attributes, such as travel time and cost, reducing the undue influence of extreme values. To explicitly capture complex dependencies among features, a Gaussian copula approach is integrated, improving the robustness of the model against traditional independence assumptions. Furthermore, a gating mechanism is introduced to dynamically balance the contributions of continuous and discrete features, incorporating random noise to account for preference heterogeneity across individual travelers. Extensive empirical analyses, initially on the Swissmetro dataset and validated in three additional diverse public datasets, demonstrate that the proposed model consistently and significantly outperforms the baseline models (MNL, MXL, L-MNL, E-MNL, EL-MNL) in terms of prediction accuracy, F1 score, and AUC values. Crucially, the interpretability of the model reveals nuanced behavioral insights, such as the heterogeneity of decision-making styles across the population and non-linear responses to cost in long-distance travel. Additional ablation studies underscore the essential roles of the ParetoTail, Gaussian copula, and gating components. In general, this integrated framework provides a flexible, robust, and generalizable approach to modeling travel behavior, offering transport planners a more accurate tool for policy evaluation in complex real-world scenarios.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"44 ","pages":"Article 101252"},"PeriodicalIF":5.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146072166","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}

{"title":"Valuing time in silicon: Can large language models replicate human value of travel time","authors":"Yingnan Yan,&nbsp;Tianming Liu,&nbsp;Yafeng Yin","doi":"10.1016/j.tbs.2026.101245","DOIUrl":"10.1016/j.tbs.2026.101245","url":null,"abstract":"<div><div>As a key advancement in artificial intelligence, large language models (LLMs) are set to transform transportation systems. While LLMs offer the potential to simulate human travelers in future mixed-autonomy transportation systems, their behavioral fidelity in complex scenarios remains largely unconfirmed by existing research. This study addresses this gap by conducting a comprehensive analysis of the value of travel time (VOT) of three popular LLMs. We employ a full factorial experimental design to systematically examine LLMs’ sensitivities to various transportation contexts, including the choice setting, travel purpose, and socio-demographic factors. Our results reveal a high degree of behavioral similarity between LLMs and humans. Some LLMs exhibit an aggregate VOT similar to that of humans, and all tested models demonstrate human-like sensitivity to travel purpose, income, and the time-cost trade-off ratios of the alternatives. Furthermore, the behavioral patterns of LLMs are highly consistent across varied contexts. However, while the behavior of every single model is highly robust, we also find some heterogeneity across models regarding the magnitude and direction of sensitivity to travel contexts and income elasticity. Overall, this study provides a foundational benchmark for the future development of LLMs as proxies for human travelers, demonstrating their robust decision-making capabilities while cautioning that misaligned magnitudes of economic trade-offs between humans and LLMs necessitate rigorous validation and additional conditioning of LLMs before their application.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"44 ","pages":"Article 101245"},"PeriodicalIF":5.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146109861","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}

{"title":"Extending the workplace tether: impact of work flexibility on commute duration acceptance","authors":"Maximilian Kuchenbauer,&nbsp;Almina Bešić","doi":"10.1016/j.tbs.2026.101246","DOIUrl":"10.1016/j.tbs.2026.101246","url":null,"abstract":"<div><div>Understanding what drives employees’ willingness to accept longer commutes is key to designing effective hybrid working policies. This study explores how commute frequency, salary, employer reputation, and travel mode influence tolerance for commute duration, based on a factorial survey experiment involving 302 participants and over 1,700 vignette evaluations conducted across Germany, Austria, and Switzerland. The results indicate that less frequent office attendance, higher salaries, a strong organizational reputation, and more convenient travel modes (e.g., train vs. bicycle) significantly increase commute tolerance. These effects, however, vary depending on individuals’ preferences for working from home or anywhere (WFH/A). Participants with strong WFH/A preferences were notably more sensitive to frequent commuting requirements and less responsive to modest salary increases. The findings challenge traditional assumptions, such as Marchetti’s constant, by demonstrating that individuals adjust their tolerance based on hybrid working patterns and mode-specific expectations. For example, commute acceptance was substantially higher when the mode was air travel, reflecting associations with long-distance or infrequent travel. These framing effects suggest that commuting decisions are shaped as much by context and mental reference points as by time alone. The study offers practical insights for HR professionals, urban planners, and policymakers. Adjusting attendance expectations or reframing commuting time (e.g., treating it as paid work) may help expand recruitment reach, enhance retention, and align job design with the preferences of a more mobile workforce.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"44 ","pages":"Article 101246"},"PeriodicalIF":5.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146109860","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}

{"title":"Unveiling gender dynamics in perception of commuters towards regional transit","authors":"Aditya Manish Pitale ,&nbsp;Shubhajit Sadhukhan ,&nbsp;Manoranjan Parida","doi":"10.1016/j.tbs.2026.101255","DOIUrl":"10.1016/j.tbs.2026.101255","url":null,"abstract":"<div><div>Developing gender sensitive transit infrastructure is essential as there exists difference in how commuters of different gender experience the transit system. This research highlights the differences in commuter experience based on socio-demographic and travel characteristics of commuters across gender, while using regional transit system of the National Capital Region (NCR), India. The perception of 1419 male and 792 female commuters of regional transit system was analysed by integrating Relative to an Identified Distribution Integral Transformation (RIDIT) analysis with Importance-Satisfaction Analysis (ISA) to reveal significant differences in their perception. Male commuters prioritized time, whereas cost was most critical for females. Last-mile connectivity along with the need to improve toilet facilities and cleanliness inside vehicle was crucial for both the commuters.</div><div>The findings of Spearman’s rank correlation analyses showcased heterogeneity among commuters of specific gender with different socio-demographic and travel characteristics, suggesting the need for targeted interventions. The approach can be used to formulate gender-based strategies for improving the service quality of regional transit systems. Developing a gender responsive transit system can assist planners and decision-making authorities in addressing the existing gaps and ensure an inclusive and efficient transit experience for all commuters.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"44 ","pages":"Article 101255"},"PeriodicalIF":5.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146111043","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}

{"title":"Left behind: forgone medical care due to transportation barriers among adults with physical impairments and disabilities that prevent physical activity in small and rural communities","authors":"Jiahe Bian ,&nbsp;Wei Li ,&nbsp;Xiao Li ,&nbsp;Sun Quan ,&nbsp;Andong Chen ,&nbsp;Sinan Zhong ,&nbsp;Muhammad Usman ,&nbsp;Samuel Dominic Castiglione Towne Jr. ,&nbsp;Muyang Li ,&nbsp;Bahar Dadashova ,&nbsp;Xinyue Ye ,&nbsp;Marcia G. Ory","doi":"10.1016/j.tbs.2026.101242","DOIUrl":"10.1016/j.tbs.2026.101242","url":null,"abstract":"<div><div>Adults with physical impairments or disabilities that prevent physical activity (PID-PA) face significant transportation barriers to essential healthcare, often forgoing care despite higher healthcare needs. While on-demand ride-sourcing services (e.g., Uber and Lyft) may improve mobility, concerns remain about the current level of inclusivity and equity, especially for individuals with more complex needs. Whether on-demand ride-sourcing will facilitate mobility or further isolate certain people with PID-PA is largely unknown. This study examined the transportation barriers to healthcare among people with temporary and chronic PID-PA and assessed the role of alternative access strategies, with particular attention to small and rural communities where residences are dispersed and transit options are limited. A cross-sectional online survey was conducted in nine such communities in Texas, yielding 416 valid responses for analysis. Fisher’s exact tests, logistic regression models, and mediation analysis were used to assess associations between adults with PID-PA and variables such as forgone necessary healthcare due to lack of transportation, use of on-demand ride-sourcing, and alternative transportation options.</div><div>Among participants, people with PID-PA were more likely to use rides provided by others and telemedicine. However, logistic regression models showed that having chronic PID-PA and using on-demand ride-sourcing for healthcare were positively associated with forgone necessary medical care due to transportation barriers. Moreover, on-demand ride-sourcing use did not mediate the relationship between chronic PID-PA and forgone necessary healthcare. This result indicates that ride-sourcing services do not effectively reduce transportation barriers for individuals with chronic PID-PA. Instead, dependence on such services may be associated with forgoing necessary medical care. The study highlights substantial challenges to using on-demand ride-sourcing in small and rural communities, including limited physical/digital accessibility, affordability concerns, and unreliable service. To improve transportation equity for people with PID-PA, interventions must address broader systemic issues affecting the accessibility of ride-sourcing.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"44 ","pages":"Article 101242"},"PeriodicalIF":5.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080725","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}

{"title":"Investigating e-scooters idle time patterns: A survival analysis approach to understand availability","authors":"Sajjad Karimi ,&nbsp;Robert Kluger ,&nbsp;Abolfazl Karimpour","doi":"10.1016/j.tbs.2026.101240","DOIUrl":"10.1016/j.tbs.2026.101240","url":null,"abstract":"<div><div>E-scooters have emerged as a popular means of commuting, specifically for short trips, within urban environments. Ensuring the availability of e-scooters within a shared fleet system is crucial for providing convenient services. However, increasing demand and service areas make it challenging to keep e-scooters available based on when and where users want to use them. This study aims to investigate the factors affecting e-scooter availability by specifically studying their idle patterns. Idle time refers to the duration between a vehicle becoming available for pick-up and being rented. Survival analysis was employed to analyze and visualize the probability of e-scooters remaining idle in a shared network in Louisville, Kentucky. Idle time was found to be influenced by several factors, including time of day, season, pick-up location, and operator. Fall and winter drop-offs have longer idle times despite fewer e-scooters indicating a large drop-off in demand. Morning drop-offs have longer idle times than other times of day. The survival analysis identifies optimal pick-up windows that operators can use to guide rebalancing, stage replacements, plan maintenance and charging, and offer incentives, customizing operations and policies to improve service reliability and efficiency.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"44 ","pages":"Article 101240"},"PeriodicalIF":5.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146109863","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}

{"title":"Preferences for on-demand transportation as a last-mile mode considering weather and time urgency: A stated choice approach","authors":"Motohiko Shiraiwa ,&nbsp;Ryosuke Abe","doi":"10.1016/j.tbs.2026.101250","DOIUrl":"10.1016/j.tbs.2026.101250","url":null,"abstract":"<div><div>On-demand transportation (ODT) has been increasingly adopted to address first- and last-mile challenges, with the aim of integration into public transportation systems. However, previous studies have not sufficiently examined how contextual factors influence preferences for this service as a last-mile mode. This study analyzes preferences for ODT as an activity-end last-mile mode, focusing on weather and time urgency. Data were collected through a stated choice experiment conducted among railway commuters traveling to Yokohama National University from five nearby stations. Respondents evaluated hypothetical scenarios comparing ODT with buses or walking under four contextual scenarios (sunny/rainy × low/high time urgency). A panel mixed logit model was estimated to analyze last-mile mode choices and quantify the effects of cost, wait time, and travel time, including interactions with weather and time urgency. The results show that travel time has a greater negative impact under time urgency than under ordinary rainy conditions. Demand for ODT is more elastic than for buses concerning cost, wait time, and travel time in most contextual scenarios, and cost elasticity varies considerably depending on the scenario. The value of travel time for ODT is the highest in “rainy and high time urgency” scenarios, reaching up to 5.6 times the baseline value. Simulations reveal that weather strongly influences demand levels for ODT when costs are low, while time urgency becomes more influential when costs are high. The findings provide quantitative insights into context-sensitive preferences, supporting the design and evaluation of last-mile mobility services.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"44 ","pages":"Article 101250"},"PeriodicalIF":5.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135479","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}

{"title":"Street environments and recovery experience: a cycling perspective analysis using machine learning and natural language processing","authors":"Yiwen Zhang ,&nbsp;Scarlett T. Jin ,&nbsp;Haizhi Luo ,&nbsp;Yang Yu ,&nbsp;Hui Kong","doi":"10.1016/j.tbs.2026.101238","DOIUrl":"10.1016/j.tbs.2026.101238","url":null,"abstract":"<div><div>Recovery experience refers to the process through which individuals achieve stress recovery via emotional responses and engagement in restorative activities. Although urban streets are known to support stress recovery, their specific effects on recovery experience, particularly in cycling-friendly environments amid growing bike-sharing adoption, remain underexplored. This study integrates multi-source data to examine how street environmental features and cycling density influence recovery experience. Using a Bidirectional Encoder Representations from Transformers (BERT) model and machine learning techniques, we systematically assess the impact of various street environmental features on recovery experience. Results indicate that traffic accessibility (e.g., metro and bus station density, intersection density), urban vitality (e.g., social vitality and commercial facility density), and aesthetic qualities (vegetation) significantly enhance recovery experience. Different dimensions of recovery experience exhibit distinct sensitivities: detachment and mastery are more responsive to traffic accessibility, while relaxation is more strongly influenced by street vitality. Specifically, shared-bike facility density exerts a positive effect on recovery experience, and moderate slope likewise contributes positively to mastery. Furthermore, high cycling density amplifies the beneficial influence of the street environments on recovery experience, particularly in terms of traffic accessibility and vitality. These findings highlight the critical role of cycling-friendly street environmental features and active cycling participation in promoting recovery experience. Based on the findings, this research provides evidence-based insights for designing urban streets that enhance sustainable mobility while fostering stress recovery.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"44 ","pages":"Article 101238"},"PeriodicalIF":5.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015815","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}

{"title":"Environmental and social influences on cycling adoption: A socio-ecological mode choice analysis in Greater Melbourne","authors":"Sapan Tiwari ,&nbsp;Afshin Jafari ,&nbsp;Nikhil Chand ,&nbsp;Billie Giles-Corti","doi":"10.1016/j.tbs.2026.101257","DOIUrl":"10.1016/j.tbs.2026.101257","url":null,"abstract":"<div><div>Cycling is widely recognised as a sustainable and health-enhancing mode of transport; however, its adoption remains low in many urban areas due to safety concerns and infrastructure limitations. This study considers the multiple levels of influence on individual behaviour. Adopting a social ecological framework, it examines how traffic stress, social norms, and family influences shape cycling uptake in Greater Melbourne. It focuses on the impact of lowering residential speed limits to 30 km/h and expanding low-stress cycling networks. The study uses the Victorian Integrated Survey of Travel and Activity, a household travel survey data and a multinomial logit model to evaluate how reducing the Level of Traffic Stress (LTS), combined with social and family reinforcement, influences mode choice behaviour.</div><div>The results indicate that speed reductions significantly lower the proportion of high-LTS road segments from 45% to 30%, leading to a 49.6% increase in cycling adoption in the model with LTS alone and from 27.85% to 88.37% in models incorporating social and family influences. The findings highlight that infrastructure improvements alone are insufficient; family and social support are crucial in reinforcing cycling behaviour and mitigating infrastructure constraints. These insights highlight the need for an integrated ecological approach combining infrastructure, behavioural strategies, and policy interventions to promote cycling.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"44 ","pages":"Article 101257"},"PeriodicalIF":5.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146153279","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}

{"title":"Predicting managed lane choice by integrating real world data and behavioral science","authors":"Musfira Rahman,&nbsp;Mark Burris","doi":"10.1016/j.tbs.2026.101254","DOIUrl":"10.1016/j.tbs.2026.101254","url":null,"abstract":"<div><div>Managed lanes (MLs) are a congestion management strategy that provides travelers with an option to either pay for uncongested travel on MLs or travel toll-free on adjacent general-purpose lanes (GPLs). Traditional travel demand models assume all travelers choose between these options for every trip based on utility maximization. However, recent research shows many travelers do not make such decisions trip by trip but instead rely on a habitual set of lanes. This study integrates real-world travel data with behavioral science to predict ML usage. A multi-task learning (MTL) model was developed to capture lane choice at two levels. At the upper level, the MTL model classified participants as choosers (who actively switch between MLs and GPLs) or non-choosers (who consistently use one type of lane). At the second level, the model predicted lane choice (MLs vs. GPLs), with each trip weighted by the participant’s probability of being a chooser. Data included detailed trip records from GPS logs and traveler information.</div><div>The MTL model was compared with two models: an Integrated Choice and Latent Variable (ICLV) model and a two stage Random Forest classification model. The study analyzed data from 106 participants tracked over three months in Dallas-Fort Worth, Texas, and Northern Virginia. Results show that travel time variability, toll prices, and psychological traits (e.g., need for cognitive closure (NFCC)) significantly influence both the likelihood of being a chooser and the decision to use MLs. Participants with lower NFCC scores were more often choosers, consistent with expectations that those more comfortable with uncertainty are more likely to evaluate travel alternatives. While the observed behavioral patterns from the models align with established theory, the integration of psychological constructs such as need for cognitive closure (NFCC) and conscientiousness etc. with revealed-preference travel data contributes novel empirical insight into ML choice research. All models showed strong accuracy in identifying choosers and non-choosers, however, the MTL and ICLV hierarchical models outperformed the two-stage Random Forest model in predicting lane choice. While these findings provide valuable insights, a larger validation study in partnership with a managed lane operator is recommended.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"44 ","pages":"Article 101254"},"PeriodicalIF":5.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146189884","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}