Transportation Research Part A-Policy and Practice最新文献

{"title":"Spatial transferability of pedestrian trip generation models","authors":"Fatemeh Nourmohammadi,&nbsp;Taha H. Rashidi,&nbsp;Meead Saberi","doi":"10.1016/j.tra.2025.104618","DOIUrl":"10.1016/j.tra.2025.104618","url":null,"abstract":"<div><div>The availability and consistency of pedestrian travel data vary across different locations, often requiring the transfer of estimated models in the absence of comprehensive local data. However, the extent to which pedestrian demand models are spatially transferable is not well understood. This study explores the spatial transferability of both aggregate and disaggregate pedestrian trip generation models using data from the Household Travel Surveys of Sydney, Melbourne, and Brisbane, Australia and two cities in the United States, Seattle and Chicago. We estimate Negative Binomial regression, Bayesian regression, and Random Forest models as aggregate approaches, while for disaggregate individual walking trip generation, we estimate a Poisson zero-inflated model, a two-step Logit-Bayesian approach, and a two-step Random Forest model. Results suggest that aggregate models exhibit reasonable transferability under certain conditions, while disaggregate models show greater limitations. The study demonstrates that while Random Forest generally outperforms other models in estimating the number of walking trips and shows strong transferability between cities, Negative Binomial Regression is effective at handling data with high variability, often surpassing machine learning models. The results highlight that both traditional and machine learning approaches have distinct advantages depending on data characteristics and under some data conditions such as sample size, the distribution of variables, and the heterogeneity of input variables. The combined use of these models can effectively capture the behavior of walking trip generation at different scales and provide valuable insights for policymakers and urban planners at both city-wide and localized levels, especially in areas where data might be lacking.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"199 ","pages":"Article 104618"},"PeriodicalIF":6.8,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The determinants of walking habit strength in urban China: A mixed-method study","authors":"Eric T.H. Chan ,&nbsp;Tingting Elle Li ,&nbsp;Jonas De Vos","doi":"10.1016/j.tra.2025.104639","DOIUrl":"10.1016/j.tra.2025.104639","url":null,"abstract":"<div><div>Promoting walking as a habitual mode of transportation supports public health and sustainability goals, particularly within high-density urban areas, where integrating walking into daily routines is feasible. Yet, the factors that contribute to walking habits remain underexplored. Investigating these determinants is essential to effectively inform transport policies and interventions that promote walking. In order to address this gap, our study employed a mixed-methods approach, combining qualitative semi-structured interviews with questionnaire surveys in examining the socio-demographic, psychosocial, and built environmental determinants of walking habit strength in Shenzhen, China. The results indicate that while environmental factors such as destination accessibility and maintenance of the walking environment are vital in fostering robust walking habits, psychosocial factors including attitudes towards walking and neighbourhood attachment, are also significant. Furthermore, our qualitative data suggest a dynamic interplay between supportive built environments and psychosocial factors, where conducive physical settings positively interact with individuals’ attitudes, values, and neighbourhood attachment, thereby reinforcing walking as a daily practice. Such interplay accentuates the need to create environments that not only physically support walking but also emotionally and socially motivate individuals to choose walking over other modes of transportation. This holistic approach recognises that human behaviour is influenced by more than just physical infrastructure, making integrated policies likely more effective and sustainable. By prioritising the development of sustainable transport habits early on, communities can achieve improved public health and environmental outcomes in the face of rapid urbanisation.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"200 ","pages":"Article 104639"},"PeriodicalIF":6.8,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144889206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How do citizens prioritize the accessibility goals of the Dutch national government against other transport goals? Results of a Participatory Value Evaluation","authors":"Niek Mouter ,&nbsp;Jetske Mulder ,&nbsp;Martijn Olivier de Vries","doi":"10.1016/j.tra.2025.104643","DOIUrl":"10.1016/j.tra.2025.104643","url":null,"abstract":"<div><div>The goals of transportation planning have been broadened in the last decades. Scholars increasingly argue to include goals such as reducing social exclusion and providing a minimal level of accessibility to all in the appraisal of transport policies. We conducted a Participatory Value Evaluation (PVE) with 6,784 Dutch citizens to investigate how different segments of the Dutch population prioritize these goals against other goals of transportation planning. In the PVE, participants indicated for 14 accessibility and mobility goals whether they thought a goal should receive more attention or less attention, subject to a budget constraint. We find that respondents recommend the government to pay the most attention to goals related to providing a basic level of accessibility for everyone such as ‘being able to access important facilities easily’, ‘being able to reach places affordably’ and ‘accessibility for people with disabilities’. Participants think that safeguarding these accessibility standards should be a core government task. They particularly prioritize improving accessibility to healthcare facilities such as hospitals and general practitioners. Participants think that the government should give relatively little attention to other goals such as ‘reducing travel times’, ‘being able to access different jobs’, ‘more pleasant and comfortable travel’ and ‘improving connections to other countries’. Many participants do not think that achieving such goals should be a core task of the government. They believe that the responsibility for achieving these goals lies more with citizens themselves, or with the market.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"200 ","pages":"Article 104643"},"PeriodicalIF":6.8,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144889205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring factors affecting how transit service level influences house prices by individual transit mode","authors":"Jian Liang ,&nbsp;Graham Currie ,&nbsp;Kang Mo Koo ,&nbsp;James Reynolds","doi":"10.1016/j.tra.2025.104636","DOIUrl":"10.1016/j.tra.2025.104636","url":null,"abstract":"<div><div>This paper investigates how the provisions of different types of public transportation modes affect the housing value by adopting an index that represents both ‘to-transit’ (accessibility) and ‘by-transit’ (level of service) accessibility. Our findings provide empirical evidence to support the value capture of public transportation infrastructure that the investment in public transportation, especially in rail and bus, lead to increases in housing value. Further, this paper contributes to the literature by showing the importance of regional income consideration when assessing the impact of transport provision. We find that the housing prices in low-income areas benefit more from the provision of rail and buses compared to the high-income areas, while increasing provision of light rail leads to a reduction in housing value in areas with lower income-level. These moderating effects of income level are found significant in metropolitan areas only. Further, heterogeneity analysis finds that the provision of light rail and rail benefits the value of houses, but not units’ value. Finally, the income level moderates the impact of light rail negatively for houses, but positively for the unit sub-market.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"200 ","pages":"Article 104636"},"PeriodicalIF":6.8,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding factors influencing ride-splitting adoption in Beijing: A comparative analysis with solo ride-hailing","authors":"Danyue Zhi ,&nbsp;Ying Lv ,&nbsp;Huijun Sun ,&nbsp;Xiaoyan Feng ,&nbsp;Weize Song ,&nbsp;Alejandro Tirachini ,&nbsp;Constantinos Antoniou","doi":"10.1016/j.tra.2025.104625","DOIUrl":"10.1016/j.tra.2025.104625","url":null,"abstract":"<div><div>Ride-splitting, a special kind of ride-hailing service, presents significant potential for energy savings and emission reduction. Studying factors that promote ride-splitting can help build sustainable transportation systems. Although many studies have analyzed the impact of the built environment and sociodemographic variables on ride-splitting, there is a lack of consideration of variables specific to ride-hailing systems. This study aims to analyze the complex impact of explanatory variables (including ride-hailing system-specific variables) on ride-splitting, based on an interpretable machine-learning framework. Firstly, the price ratio between shared and solo trips, the distance passengers wait for the driver to pick them up (called passenger waiting distance), and the driver’s detour index are extracted from Beijing’s data. Then, a machine learning-based framework combining XGBoost and SHAP is constructed. The explained variables are the daily trip numbers of ride-splitting and solo ride-hailing between origin–destination (OD) pairs. The results show that price ratio, passenger waiting distance, and detour index have a greater impact on ride-splitting than solo ride-hailing. Based on SHAP values, a nonlinear threshold-based relationship between individual variables and ride-splitting demand is investigated. Exogenous variables related to the high adoption of ride-splitting include OD pairs having trip durations shorter than 20 min, a zonal per capita GDP below a certain threshold, and being located away from the city center. The interaction effects of multiple variables on ride-splitting, such as distance from the origin/destination to the city center and travel time, are investigated based on the SHAP interaction value. These findings help to adapt specific variables to facilitate the shift from solo trips to shared trips, which is conducive to more sustainable transportation patterns.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"200 ","pages":"Article 104625"},"PeriodicalIF":6.8,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144878848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empowering econometric methods with machine learning for policy making: A comparative study in maritime transportation","authors":"Ruihan Wang ,&nbsp;Tianyu Shang ,&nbsp;Dong Yang ,&nbsp;Ran Yan","doi":"10.1016/j.tra.2025.104635","DOIUrl":"10.1016/j.tra.2025.104635","url":null,"abstract":"<div><div>The maritime transportation plays a critical role in global trade, yet ensuring its safety and regulatory compliance remains a significant challenge. This study investigates the comparative strengths and limitations of econometric methods and machine learning in supporting policymaking. Leveraging publicly accessible data from port state control (PSC) inspections as the case study, we develop models to identify key factors influencing ship deficiencies (i.e., non-compliance) in PSC and to predict the number of deficiencies during inspections. The results show that machine learning outperforms econometric methods in predictive performance, while econometric methods offer unique advantages in providing interpretable causal insights, enabling a deep understanding of the factors influencing ship deficiencies. Furthermore, by integrating machine learning techniques into econometric frameworks, we uncover nuanced relationships — such as the heterogeneous impact of ship age on ship deficiencies and a U-shaped relationship between ship tonnage and deficiencies — while also enhancing the predictive reliability of econometric methods. By combining the interpretability of econometric methods with the predictive power of machine learning, this study establishes a robust framework for assessing ship risk, enhancing maritime safety management, mitigating maritime risks, and improving transportation policies and regulations.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"200 ","pages":"Article 104635"},"PeriodicalIF":6.8,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A stochastic model-free reinforcement learning framework for optimizing runway capacity management under uncertainty","authors":"Lucas Orbolato Carvalho,&nbsp;Mayara Condé Rocha Murça","doi":"10.1016/j.tra.2025.104620","DOIUrl":"10.1016/j.tra.2025.104620","url":null,"abstract":"<div><div>Air traffic operations are often subject to congestion due to rising air travel demand levels and capacity limitations at airport and airspace resources. These capacity constraints are frequently exacerbated by adverse weather conditions, one of the primary causes of flight delays and additional operational costs. To mitigate the impact of demand-capacity imbalances on overall aviation system performance, there is a pressing need for more advanced Air Traffic Flow Management (ATFM) processes, which must be able to better address the complexities and challenges arising from dynamic and stochastic operational environments. In recent years, machine learning techniques have emerged as promising tools to enhance ATFM decision-making, offering potential solutions to these challenges. This study investigates the application of different reinforcement learning (RL) approaches and algorithms for runway capacity management under uncertainty, including both runway configuration selection and airport service rate allocation decisions. The problem is formulated as a Markov Decision Process (MDP), and two approaches are proposed: data-based and forecast-based. Both approaches leverage a state-of-the-art model-free RL method, with the Maskable Proximal Policy Optimization (PPO) algorithm, which is compared to a traditional RL algorithm - Deep Q-Network (DQN). The results reveal that both algorithms perform similarly, with our stochastic forecast-based and incremental data-driven approaches outperforming traditional methods. These approaches offer notable reductions in delay costs compared to the baseline policy typically used in practice and yield results comparable to the best theoretical solutions derived from genetic algorithms. This study highlights two efficient methods for addressing runway capacity management challenges at airports and provides valuable insights into data-driven ATFM optimization and policy implications.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"200 ","pages":"Article 104620"},"PeriodicalIF":6.8,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of real-time information on passenger satisfaction across varying public transport quality levels in 13 Chilean cities","authors":"Bastian Henriquez-Jara ,&nbsp;Jacqueline Arriagada ,&nbsp;Alejandro Tirachini","doi":"10.1016/j.tra.2025.104622","DOIUrl":"10.1016/j.tra.2025.104622","url":null,"abstract":"<div><div>This paper addresses the satisfaction effect of real-time information applications (apps) and their interaction with the actual quality of service of public transport (PT) in 13 Chilean cities. Our study has two methodological innovations; first, we combine a discrete choice model and a sentiment analysis conducted with a Large Language Model (ChatGPT3.5-turbo), which classifies an open-ended satisfaction question, allowing us to embed qualitative data into a quantitative model. Second, we used an objective quality of service metric (a headway reliability index, based on bus GPS data) as input in the passenger satisfaction model, which is an improvement over previous passenger satisfaction models that rely on perceived (rather than measured) service attributes only. Therefore, the model accounts for the relationship between user satisfaction, service attributes, app-induced behavior, and perception changes. The results highlight a symbiotic relationship between having access to real-time information and the PT level of service. That is, the use of real-time information makes passengers more satisfied, but the effect is greater under higher PT service regularity conditions. Sentiment analysis revealed that satisfied users (70% of the sample) value the waiting time information provided by the app and the resulting ability to manage their time. Unsatisfied users (12% of the sample) mainly criticize the frequency of service and the accuracy of the data displayed in the app. These findings promote user-centered policy making, especially in developing countries where high-quality real-time information should be more widely available. Finally, service regularity is statistically significant in explaining user satisfaction, even when controlled for the use of real-time information. This indicates that having regular headways matters to users, regardless of whether they receive real-time information about waiting times.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"200 ","pages":"Article 104622"},"PeriodicalIF":6.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144860464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing built environment effects on bike-sharing and electric bike-sharing usage: a spatiotemporal machine learning approach","authors":"Yisong Zhu ,&nbsp;Ziqi Yang ,&nbsp;Xi Feng ,&nbsp;Cheng Cheng ,&nbsp;Yuntao Guo ,&nbsp;Qiumeng Li ,&nbsp;Tianhao Wu ,&nbsp;Xinghua Li ,&nbsp;Frank Witlox","doi":"10.1016/j.tra.2025.104642","DOIUrl":"10.1016/j.tra.2025.104642","url":null,"abstract":"<div><div>Shared micromobility has been widely recognized as a promising solution for promoting sustainable urban transportation, experiencing rapid growth and diversifying into various services, such as bike-sharing (BS) and electric bike-sharing (EBS). However, existing studies have primarily examined BS and EBS separately, leaving comparative analyses of their travel patterns and determinants notably limited. Moreover, although machine learning approaches have become prevalent for modeling nonlinear relationships, these methods typically overlook spatiotemporal heterogeneity, potentially resulting in biased estimations and inaccurate interpretations. To address these gaps, this study develops a novel modeling framework integrating XGBoost with geographically and temporally weighted regression (GTWR), enabling simultaneous consideration of spatiotemporal heterogeneity and nonlinearity. Using trip data from Hefei, China, we comparatively analyze the travel characteristics of BS and EBS and apply the integrated modeling framework to investigate the built environment’s influence on both modes. The results indicate that both BS and EBS exhibit distinct peak-hour usage patterns, while spatially, BS usage is concentrated in downtown areas and EBS usage is more evenly distributed citywide. Among examined factors, distance to metro stations and employment density emerge as the most significant predictors for both modes. Additionally, nonlinear relationships reveal that higher branch road density and lower major road density are associated with increased BS but reduced EBS usage, while land use mix demonstrates clear threshold effects, beyond which usage of both modes significantly increases. These findings provide valuable insights for operators to optimize fleet deployment and for policymakers to design targeted interventions supporting coordinated and sustainable shared micromobility development.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"200 ","pages":"Article 104642"},"PeriodicalIF":6.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144860465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Planning UAM network under uncertain travelers’ preferences: A sequential two-layer stochastic optimization approach","authors":"Tao Guo ,&nbsp;Hao Wu ,&nbsp;Qing-Long Lu ,&nbsp;Constantinos Antoniou","doi":"10.1016/j.tra.2025.104632","DOIUrl":"10.1016/j.tra.2025.104632","url":null,"abstract":"<div><div>Urban Air Mobility (UAM) holds significant promise for enhancing travel efficiency and improving regional accessibility. However, policymakers face a fundamental challenge: infrastructure planning decisions must often be made before demand is known. This study develops a single-stage stochastic optimization framework with sequential decision layers that mirrors real-world planning constraints. It allows agencies to determine vertiport locations and trip allocations before individual mode choices are realized, incorporating behavioral uncertainty via discrete choice modeling and Monte Carlo simulation. To ensure computational tractability at realistic scales, an improved greedy algorithm (GRD-U) is introduced and benchmarked against established heuristics. Experiments on synthetic instances show that cost-saving potential is greatest in larger regions with low road connectivity, as well as unicentric or dispersed demand patterns. A real-world case study in the Munich Metropolitan Area confirms the framework’s applicability, demonstrating notable improvements in generalized travel cost savings, demand coverage, and accessibility compared to existing siting strategies. A sensitivity analysis highlights how UAM performance responds to changes in operational parameters, such as cruise speed, pricing strategies, and vertiport quantity. The framework offers a transparent and behaviorally grounded tool for early-stage UAM planning. It enables public agencies to anticipate demand patterns under uncertainty, weigh trade-offs between investment scale and system performance, and align infrastructure planning with equity and efficiency goals. These contributions provide practical decision support for cities navigating the complexities of UAM deployment</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"200 ","pages":"Article 104632"},"PeriodicalIF":6.8,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144852475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}