Transportation Research Interdisciplinary Perspectives最新文献

{"title":"The partial adaptation of mobility practices to public transport shock effects: evidence from the Greater Geneva cross-border region","authors":"Alexis Gumy,&nbsp;Vincent Kaufmann,&nbsp;Frédéric Varone,&nbsp;Maria Masood Dechevrens","doi":"10.1016/j.trip.2026.102219","DOIUrl":"10.1016/j.trip.2026.102219","url":null,"abstract":"<div><div>The introduction of public transport infrastructures is typically accompanied by political discourse expecting “shock effects” on the supply side to translate unconditionally into sustainable mobility practices on the demand side. This study examines how mobility practices have evolved in the wake of such a shock effect, focusing on the introduction of the Léman Express, a cross-border regional rail network that substantially enhanced public transport in the Greater Geneva. Drawing on two surveys conducted before (2018) and after (2022) the inauguration, we combine inductive Multiple Correspondence Analysis with Difference-in-Differences design and Propensity Score Matching to compare matched populations exposed and not exposed to the new infrastructure. We identify two latent dimensions structuring mobility practices in the region – environmental concern and valuation logic – along which the evolution of practices can be tracked while controlling for the confounding role of the COVID-19 pandemic. Our findings reveal that exposure to the Léman Express is associated with a partial attenuation of a general decline in sustainable mobility practices over the period, rather than with a positive shift. This attenuation is moreover narrow in scope – concentrated on environmental concern – and unevenly distributed across the population, remaining confined to urban, well-educated subgroups. By holding the behavioral, attitudinal, and practical aspects of mobility within a single analytical frame, this study contributes to an interdisciplinary dialogue between Transport Studies, Transit Oriented Development scholarship, and Social Practice Theories, and offers evidence on how mobility practices (do not) adapt when confronted with a major infrastructural change.</div></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":"39 ","pages":"Article 102219"},"PeriodicalIF":4.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148958483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Do tougher DUI sanctions reduce crashes and fatalities? Evidence from Brazil’s federal highways after the 2008 and 2021 reforms","authors":"Thiago Cavalcante,&nbsp;Helder Alexandre Rodrigues de Jesus","doi":"10.1016/j.trip.2026.102202","DOIUrl":"10.1016/j.trip.2026.102202","url":null,"abstract":"<div><div>This study investigates the effects of Brazilian zero tolerance alcohol policies, implemented in 2008 and revised in 2021, on accident and mortality levels along federal highways. The analysis uses a monthly panel from 2007 to 2023 and applies a difference in differences model to identify structural changes in driver behavior following the legal reforms. The empirical strategy is based on comparing weekdays, weekends and holidays, which represent different levels of exposure to the risk associated with driving under the influence of alcohol. The results show that the 2021 legislation produced stronger and more consistent effects, with significantly larger reductions in accidents and deaths compared with the 2008 version. The superior performance of the recent reform is associated with increased penalty severity, expanded conditions for criminal accountability and greater predictability of enforcement. From a theoretical perspective, the findings reflect a combination of rational deterrence and loss aversion, suggesting that raising the expected cost of the infraction modifies both perceived utility and the cognitive salience of risk. The results reinforce that road safety policies are more effective when they combine institutional robustness, continuous enforcement and mechanisms of normative internalization.</div></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":"39 ","pages":"Article 102202"},"PeriodicalIF":4.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148853989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting pavement roughness evolution in data-limited contexts using spatially validated probabilistic hindcasting","authors":"Angela Odera,&nbsp;Michael Henry","doi":"10.1016/j.trip.2026.102231","DOIUrl":"10.1016/j.trip.2026.102231","url":null,"abstract":"<div><div>Many low- and middle-income countries must manage extensive road networks using temporally sparse condition data and incomplete maintenance histories, while prevailing pavement deterioration modelling paradigms assume data-richness in these dimensions. This structural mismatch limits the predictive utility of conventional Pavement Management Systems (PMS). To address this, a spatially validated, probabilistic hindcasting framework is proposed for characterizing pavement roughness evolution under such constraints, demonstrated on Kenya’s asphalt-surfaced national trunk road network. Using network-level surveys from 2018 and 2023, five-year International Roughness Index (IRI) class changes were modelled as an interval-based process conditioned on baseline (2018) condition, inventory, structural, and contextual attributes. Penalized logistic regression (PLR), decision tree (CART), and random forest (RF) models were trained across binary, three-class and six-class IRI formulations and evaluated under a spatially blocked nested cross-validation framework. Model performance was assessed using discrimination metrics (ROC-AUC, PR-AUC) and probability calibration diagnostics (Brier, Brier Skill, Expected Calibration Error, slope, and intercept). Post-hoc recalibration using Platt scaling and isotonic regression was applied selectively to correct miscalibration. Results show moderate-to-strong, spatially transferable discrimination (ROC-AUC = 0.66–0.87; PR-AUC consistently exceeding prevalence baselines), confirming effective ranking of deterioration risk from sparse condition archives, while CART exhibited discrimination collapse for some targets. Recalibration of PLR and RF effectively improved probability reliability. Retrospective consistency analysis incorporating attribute-change information confirmed temporal robustness of baseline models. Overall, the framework demonstrates that spatially transferable, uncertainty-aware deterioration forecasts can be achieved from limited data, providing a practical pathway for strengthening predictive PMS capability in data-scarce environments.</div></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":"39 ","pages":"Article 102231"},"PeriodicalIF":4.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning-based behavioral pattern extraction from transit station videos modeling structural gender differences using CNN and Vision Transformers","authors":"Rasa Nobahar","doi":"10.1016/j.trip.2026.102224","DOIUrl":"10.1016/j.trip.2026.102224","url":null,"abstract":"<div><div>Urban transit stations are among the most behaviorally complex environments in public transport systems, yet planners still lack scalable methods for converting continuous video observations into interpretable, planning-relevant behavioral evidence. Existing transportation research relies heavily on surveys and self-reports that capture perceptions rather than observed behavior, while computer-vision studies achieve high detection and tracking accuracy but rarely transform trajectories into standardized indicators usable for station design, capacity assessment, or equity analysis. This study addresses this methodological gap by developing and demonstrating an interpretable behavioral measurement framework that extracts trajectory-based indicators waiting duration, interpersonal distance, trajectory entropy, walking speed, and congestion exposure from transit-station video and quantifies context-dependent differences associated with visually inferred gender presentation. A hybrid Convolutional Neural Network–Vision Transformer (CNN–ViT) architecture is employed to produce reliable, identity-preserving trajectories under the occlusion, density, and illumination conditions typical of real stations. The hybrid design combines the local feature extraction strengths of CNNs with the long-range contextual modeling of Vision Transformers, yielding higher-quality trajectories than conventional single-architecture baselines. Explainable AI techniques are used solely to enhance transparency of the computational pipeline, not to validate theoretical constructs. Behavioral differences are interpreted strictly as patterns associated with visually inferred gender under specific environmental conditions, maintaining a clear distinction from lived-experience constructs of gendered mobility. The framework bridges the disconnect between algorithmic outputs and the analytical needs of transportation planning by delivering compact, reproducible indicators that can inform passenger-flow management, station design evaluation, and operational analysis while respecting the evidential limits of observational data. The principal contribution is therefore methodological: an evidence-based measurement bridge that strengthens, rather than replaces, existing transportation knowledge.</div></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":"39 ","pages":"Article 102224"},"PeriodicalIF":4.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Designing road networks for hazardous materials transportation: a review toward a regulator-carrier risk optimization framework","authors":"Musharraf Ahmad Khan,&nbsp;Jonathan D. Regehr,&nbsp;Babak Mehran,&nbsp;Chaouki Regoui","doi":"10.1016/j.trip.2026.102227","DOIUrl":"10.1016/j.trip.2026.102227","url":null,"abstract":"<div><div>Complexities in route planning for hazardous materials (HAZMAT) arise because of the fundamental need to optimize risk while considering the perspectives of regulators and transport carriers. The trade-off between risk and other criteria is skewed in the HAZMAT transportation context due to stringent regulatory requirements. Hence, risk is not weighted among other criteria but considered as a performance evaluator for other criteria. This reality changes the optimization goals and introduces complexities for the hazardous transportation network design problem (HNDP). It is evident that HNDPs solved in the literature often fail to penetrate actual practice. This article delivers a holistic review of the HNDP context from the literature, including risk regulatory setups and models, HNDP formulation challenges and variations, optimization approaches, and risk measures and constraints. The review reveals knowledge gaps that potentially deter the practicality of HNDP solutions. Specifically, more work is needed to develop optimization approaches that integrate non-linear cost functions and a mix of direct and indirect routing while following the user-optimal routing strategies. Data availability continues to limit such approaches. Addressing risk equity among communities and cost equity among transport carriers, requires tactical use of soft constraints and consideration of emergency response capacity. Moreover, network reliability may be critical for HAZMAT transportation and should be addressed to make HNDP solutions more practical. The review motivated the development of a novel regulator-carrier generic risk optimization framework that situates knowledge gaps within the complexities of the HNDP.</div></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":"39 ","pages":"Article 102227"},"PeriodicalIF":4.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Restorative lighting–color ambience and experience in underground transit spaces: Evidence from VR and fNIRS","authors":"Daren Wei,&nbsp;Guanghui Li,&nbsp;Pengfei Li,&nbsp;Miaohui Wang,&nbsp;Yan Li,&nbsp;Wu Song","doi":"10.1016/j.trip.2026.102203","DOIUrl":"10.1016/j.trip.2026.102203","url":null,"abstract":"<div><div>Subways are central to underground transit environments and subtly influence passengers’ moods and mental states, yet the effects of lighting and decorative design remain underexplored. This study employed a within-subject design in which 21 participants experienced nine virtual subway environments, generated by crossing three illuminance levels (300, 500, 750 lx) with three lighting–color ambience configurations (2700 K–green, 4300 K–blue, 6500 K–white). Functional near-infrared spectroscopy (fNIRS) was used to measure prefrontal oxygenated hemoglobin during stress-inducing tasks, alongside PAD mood ratings, the Perceived Restorativeness Scale (PRS), and the State-Trait Anxiety Inventory (STAI). Results showed that the 500 lx, 4300 K blue–sky environment produced comfort and restorative effects, which were accompanied by increased DLPFC–AFC functional connectivity. Higher illuminance (750 lx) was associated with increased subjective alertness and greater prefrontal activation, alongside reduced perceived restoration. This pattern was associated with greater neurocognitive engagement under higher illuminance conditions, although the underlying neural mechanisms require further investigation. In contrast, the 300 lx, 2700 K green-toned condition was associated with lower restorative ratings, indicating context-dependent differences in affective responses across lighting configurations. Overall, the findings provide evidence of condition-dependent relationships between illuminance, color ambience, and both subjective and neural responses within a controlled virtual subway context.</div></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":"39 ","pages":"Article 102203"},"PeriodicalIF":4.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148853996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of dynamic correlated colour temperature on road user safety and perception: a review of methodologies, challenges and human-centric future directions","authors":"Pallav Dutta,&nbsp;Suddhasatwa Chakraborty","doi":"10.1016/j.trip.2026.102204","DOIUrl":"10.1016/j.trip.2026.102204","url":null,"abstract":"<div><div>Correlated Colour Temperature (CCT) is an essential design parameter in road lighting, as variations in spectral output significantly influence visual performance, perceived comfort and safety. This article reviews the impact of different CCT ranges on driver alertness, fatigue, reaction times and pedestrian hazard detection. The review particularly highlights differences between traditional fixed-CCT installations and new adaptive lighting technologies capable of real-time modulation of spectral output. Where such technologies have been implemented, real-world examples are included to illustrate their practical application. Instead of a simple report of findings, this article evaluates the primary investigative approaches: laboratory studies, driving simulators and field investigations. Each methodology presents unique strengths and weaknesses regarding experimental control and ecological validity. We provide an objective overview of existing evidence while debating current obstacles to widespread adaptive CCT adoption, including the lack of human response datasets, unreliable validation processes, uncertain spectral transitions and privacy concerns in connected infrastructure. Emerging digital twin methodologies, standardized protocols and human-centred frameworks can reinforce future research. Finally, key research priorities for the next generation of adaptive road lighting are articulated. More specifically, they concern the importance of experimentally validated adaptive spectral thresholds, standardized validation methodologies and human-centred performance metrics inevitably needed to inform subsequent lighting recommendations and support the establishment of adaptive road lighting standards.</div></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":"39 ","pages":"Article 102204"},"PeriodicalIF":4.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148853986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis and modeling of human driving behavior in highway merging areas using a combined approach of stochastic methods and artificial intelligence","authors":"Xinzhe Zhang,&nbsp;István Varga,&nbsp;Tamás Tettamanti","doi":"10.1016/j.trip.2026.102213","DOIUrl":"10.1016/j.trip.2026.102213","url":null,"abstract":"<div><div>The paper investigates the driving behavior patterns of mainline human-driven vehicles during highway ramp-merging interactions. Using the exiD dataset, a dynamic merging window was defined in time and space to identify mainline vehicles with potential interactions with ramp vehicles. Using the neighboring-vehicle information for each ramp vehicle within the merging window, one-to-one merging events between mainline and ramp vehicles were extracted. To identify heterogeneous driving behavior patterns within the merging area, a Bayesian Gaussian Mixture Model was employed for cluster analysis of driving behaviors. Subsequently, the Hierarchical Bayesian Inverse Reinforcement Learning framework was adopted to infer global and cluster-specific bias weights that represent relative reward preferences across behavioral patterns. Afterward, using reinforcement learning, the driving behavior trajectories of human-driven vehicles in each cluster were reproduced in SUMO (Simulation of Urban MObility), providing a more comprehensive representation of lateral and longitudinal driving behavior. Finally, the exiD-trained policy was deployed in a high-fidelity SUMO merging scenario representing the Hungarian M1 highway. The results showed stable closed-loop execution and supported the cross-scenario portability of the framework. Overall, this study presents a configurable empirical framework for on-ramp merging analysis that connects traffic interaction representation, human driving behavior heterogeneity, data-driven preference inference, and closed-loop traffic simulation.</div></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":"39 ","pages":"Article 102213"},"PeriodicalIF":4.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A socio-ecological model of drowsy driving in the UK: Are we there yet?","authors":"Pamela Alfonso-Miller,&nbsp;Jason G. Ellis,&nbsp;Dawn Thomson,&nbsp;Karen McDonnell","doi":"10.1016/j.trip.2026.102235","DOIUrl":"10.1016/j.trip.2026.102235","url":null,"abstract":"<div><div>Despite its substantial contribution to road traffic collisions, injuries, fatalities, and associated economic costs, drowsy driving remains a persistent transportation safety and public health concern. Although there is substantial literature regarding sleepiness and fatigue in the context of driving, alongside policies, practices and safeguarding procedures, levels of drowsy driving appear to remain consistent, highlighting the need for a more integrated understanding of the factors influencing this behaviour. This narrative review synthesises interdisciplinary evidence from transportation, sleep science, psychology, occupational health, and public health. It examines the scale of drowsy driving, its contributing factors, and its emergence as a complex transportation behaviour shaped by interacting individual, social, and societal influences rather than solely by individual choice. Building on the reviewed evidence, a socio-ecological model of drowsy driving is proposed to integrate biological, behavioural, occupational, technological, and policy influences within a single conceptual framework. The review identifies key knowledge gaps and future research priorities and provides a framework to guide interdisciplinary transportation research, policy, and practice addressing drowsy driving and improving road safety.</div></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":"39 ","pages":"Article 102235"},"PeriodicalIF":4.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic review of crowdsourced pedestrian data","authors":"Caitlyn Linehan,&nbsp;Trisalyn Nelson,&nbsp;Somayeh Dodge,&nbsp;Victoria Fast","doi":"10.1016/j.trip.2026.102238","DOIUrl":"10.1016/j.trip.2026.102238","url":null,"abstract":"<div><div>Cities are increasing investments in walkable environments due to the health, environmental, and social benefits of walking. However, accurately measuring pedestrian patterns remains challenging due to data limitations. Crowdsourced data presents an opportunity to address data limitations but there are also challenges. This paper aims to take a systematic look into crowdsourced data that are being used to fill gaps and advance pedestrian research with three primary objectives: (1) to identify key gaps and opportunities in the current application of crowdsourced data in pedestrian-related research, (2) to critically evaluate the methods used to process and integrate crowdsourced data for pedestrian research, and (3) to provide key recommendations to guide future research and planning efforts through the effective use of crowdsourced data in pedestrian studies. Conducting a systematic literature review, we screened an initial set of 653 papers to identify 48 peer-reviewed studies published between 2011 and 2024 for full review. We identify eight thematic uses of crowdsourced data in pedestrian research and planning: travel patterns, infrastructure detection, mode detection, navigation, policy, route/infrastructure choice, safety, and walkability/accessibility. Additionally, we highlight four promising future research opportunities: understanding disruptions that shape pedestrian mobility, incorporating equity considerations into research and planning, integrating pedestrian perspectives into crowdsourced imagery, and refining methodologies for analyzing crowdsourced data. We provide a guide for both researchers and policy makers in advancing pedestrian research through the integration of crowdsourced and traditional data sources.</div></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":"39 ","pages":"Article 102238"},"PeriodicalIF":4.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}