Transportation Letters-The International Journal of Transportation Research最新文献

{"title":"Optimizing battery electric bus allocations: an integrated approach to cost minimization and evolutionary game theory","authors":"Jing Liu ,&nbsp;Jie Zhang ,&nbsp;Chuntong Dong ,&nbsp;Qingling He","doi":"10.1080/19427867.2025.2595232","DOIUrl":"10.1080/19427867.2025.2595232","url":null,"abstract":"<div><div>High capital costs and vehicle allocation challenges impede urban public transport electrification. This paper presents an integrated optimization framework for battery electric bus (BEB) fleet scheduling under both opportunity and depot charging conditions, simultaneously optimizing battery capacity, dispatch frequency, and fleet size to minimize total annualized system cost. A hybrid heuristic algorithm achieves high-quality solutions within practical runtimes. An evolutionary game model captures dynamic interactions between operators and passengers under alternative allocation strategies. The framework is validated through a case study in Harbin, China. Results demonstrate that the optimal configuration reduces annualized system cost by approximately 17.8% (≈266 million CNY) relative to the baseline and identifies cost-effective combinations of key decision variables. Sensitivity analyses confirm robustness across varying wireless charging facility scenarios. These findings provide actionable insights for electric bus planning and sustainable fleet management in cold-climate urban environments.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 3","pages":"Pages 636-669"},"PeriodicalIF":3.3,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 impact of ride-hailing services on traffic congestion: quasi-experimental evidence from China","authors":"Zhuolun Wang ,&nbsp;Yan Lin ,&nbsp;Jing Yang","doi":"10.1080/19427867.2025.2570223","DOIUrl":"10.1080/19427867.2025.2570223","url":null,"abstract":"<div><div>Traffic congestion has gradually become an important social problem that hinders the sustainable development of transportation. With ride-hailing services become more widespread in Chinese cities, it is crucial for city managers to understand their impact on traffic congestion. Using panel data for 61 Chinese cities between 2014 and 2017, the results indicate that the overall impact of ride-hailing services on traffic congestion in China is insignificant. The main reason for this insignificance is the mutual offset between direct and indirect effects: on the one hand, they directly increase traffic congestion by 1.04%, but the direct effect is statistically insignificant; on the other hand, ride-hailing services indirectly mitigate traffic congestion by 1.18% through reducing private car ownership by 6.29%, indicating that private car ownership plays a suppression effect in this impact path. Didi Hitch significantly mitigates traffic congestion compared to Didi Express.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 3","pages":"Pages 508-522"},"PeriodicalIF":3.3,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cascading failure analysis for multimodal comprehensive transportation network considering time-delay characteristic of passenger flow redistribution","authors":"Jialiang Xiao ,&nbsp;Yongtao Zheng ,&nbsp;Wei Wang ,&nbsp;Xuedong Hua","doi":"10.1080/19427867.2025.2564831","DOIUrl":"10.1080/19427867.2025.2564831","url":null,"abstract":"<div><div>Under external disturbances, considering passenger flow transfer time – referred to as the time-delay characteristic – rather than redistributing the passenger flow instantaneously, is crucial for analyzing cascading failures in multimodal comprehensive transportation network (MCNet). This study proposes an improved cascading failure model that incorporates passenger flow transfer time, transfer paths, and multiple transfer modes. A systematic analytical method is designed to examine cascading failure characteristics under different influencing factors in MCNet. The experimental results reveal that attacking the highest-strength vertex triggers a more severe cascading failure. Besides, the cascading failure in MCNet is primarily induced by passenger flow rather than network structure, while the time-delay characteristic can slow down the failure propagation by 43.6%. Moreover, an increasing proportion of volume transferred within the same mode can mitigate the cascading effects. Finally, based on the research findings, we propose several suggestions for network design and optimization to enhance the resilience of MCNet.</div></div><div>Under external disturbances, considering passenger flow transfer time – referred to as the time-delay characteristic – rather than redistributing the passenger flow instantaneously, is crucial for analyzing cascading failures in multimodal comprehensive transportation network (MCNet). This study proposes an improved cascading failure model that incorporates passenger flow transfer time, transfer paths, and multiple transfer modes. A systematic analytical method is designed to examine cascading failure characteristics under different influencing factors in MCNet. The experimental results reveal that attacking the highest-strength vertex triggers a more severe cascading failure. Besides, the cascading failure in MCNet is primarily induced by passenger flow rather than network structure, while the time-delay characteristic can slow down the failure propagation by 43.6%. Moreover, an increasing proportion of volume transferred within the same mode can mitigate the cascading effects. Finally, based on the research findings, we propose several suggestions for network design and optimization to enhance the resilience of MCNet.</div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 3","pages":"Pages 481-507"},"PeriodicalIF":3.3,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Consumer adoption intention towards electric vehicles: Insights from Bangalore, India","authors":"Suraj Ghosh ,&nbsp;Biplab Sarkar","doi":"10.1080/19427867.2025.2593638","DOIUrl":"10.1080/19427867.2025.2593638","url":null,"abstract":"<div><div>Electric Vehicles (EVs) are vital for reducing carbon emissions from the transportation sector. Despite various policy efforts in India, EV adoption remains limited. This study examines key factors influencing EV adoption intentions, focusing on demand incentive, and publicity &amp; information policy measures, and perceived economic benefits. The moderating role of environmental concern is also examined. A cross-sectional survey of university students in Bengaluru, identified as potential early adopters, was conducted using a structured questionnaire, and the proposed model was tested through Partial Least Squares Structural Equation Modelling (PLS-SEM). Results indicate that demand incentives and perceived economic benefits significantly increase EV adoption intentions, with economic benefits being stronger driver. Demand incentives partially mediate this link, while publicity policy measures show no effect. Environmental concern boosts adoption intention but does not strengthen policy effects. These insights can inform policymaking and support industry stakeholders in designing more effective EV promotion strategies.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 3","pages":"Pages 603-619"},"PeriodicalIF":3.3,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fundamental diagram parameters in mixed traffic conditions: measurement methods and models","authors":"Aathira K. Das ,&nbsp;Bhargava Rama Chilukuri","doi":"10.1080/19427867.2025.2576260","DOIUrl":"10.1080/19427867.2025.2576260","url":null,"abstract":"<div><div>Fundamental diagram parameters including saturation flow, jam density, and wave speed, are essential for traffic modeling but are strongly influenced by composition under mixed traffic conditions. While traditional methods exist for saturation flow estimation, they introduce measurement errors, rely on PCU/hour units that mask heterogeneity, and rarely address jam density or wave speed. This study proposes intuitive, field-implementable measurement methods for the parameters: a cumulative count curve with oblique plots to estimate saturation flow; and theory-based, sensor-independent procedures to estimate jam density and wave speed. We further develop Multiple Linear Regression (MLR) models using traffic composition and interaction terms along with clustering-based MLR to capture composition-driven variability. Machine Learning (ML) alternatives: support vector regression and gradient-boosted regression trees are benchmarked. Results show that MLR, particularly clustering-based models, outperforms ML models and align well with field data. The framework is data-efficient, scalable, and suitable for routine traffic analysis in resource-limited settings.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 3","pages":"Pages 523-544"},"PeriodicalIF":3.3,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vehicle lane change intention recognition based on a mixed teacher forcing CNN-GCN-LSTM encoder-decoder model","authors":"Changxi Ma ,&nbsp;Keyan Gu ,&nbsp;Bo Du ,&nbsp;Yongpeng Zhao","doi":"10.1080/19427867.2025.2594082","DOIUrl":"10.1080/19427867.2025.2594082","url":null,"abstract":"<div><div>To enhance lane change intention recognition, this study introduces a novel model based on a Mixed Teacher Forcing (MTF) framework integrating Convolutional Neural Network (CNN), Graph Convolutional Network (GCN), and Long Short-Term Memory (LSTM) encoder-decoder architecture to capture dynamic changes in time series and interaction between. Vehicle trajectories extracted from NGSIM US101 highway dataset are used for numerical experiments. During training, a MTF strategy is implemented to enhance model flexibility, while a recursive strategy is used during testing to boost prediction performance. Comparative analysis against the traditional MTF-LSTM model shows significant improvements (40.50%/64.59%/44.00%/33.23% reduction in RMSE/MSE/MAE/MAPE, respectively, and increase in R² to 99.04%). A Harris Hawks Optimization (HHO)-enhanced LightGBM model is proposed for intention recognition. Comprehensive comparisons with baseline models, such as LSTM, BiGRU, Decision Tree, and Random Forest, demonstrate outstanding accuracy (97.79%) of the proposed HHO-LightGBM model with MTF-CNN-GCN-LSTM codec, underscoring the model’s effectiveness in recognizing lane change intentions.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 3","pages":"Pages 620-635"},"PeriodicalIF":3.3,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 the impacts of Intelligent Winter Road Information System on travel choices in winter weather: insights from a stated-preference survey","authors":"Gongda Yu ,&nbsp;Jiajun Pang ,&nbsp;Irina Benedyk","doi":"10.1080/19427867.2025.2595557","DOIUrl":"10.1080/19427867.2025.2595557","url":null,"abstract":"<div><div>Winter hazards can lead to traffic safety issues, often resulting from uninformed travel decisions. To address these challenges, the Intelligent Winter Road Information System (IWRIS) was developed to improve driver awareness by providing supportive information and timely alert notifications through various media platforms. This study utilizes a stated preference survey to examine how travelers respond to IWRIS and assesses its impact on driver decision-making during winter conditions. The results indicate a strong correlation between the consistent acceptance of navigation system recommendations, overall system usage, and critical variables, such as weather conditions, driver experience, route familiarity, and vehicle characteristics. The study underscores the necessity of understanding the impact of information provision on travel choices in challenging winter conditions and highlights the need for systems that effectively adapt to the unique challenges of winter.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 3","pages":"Pages 670-682"},"PeriodicalIF":3.3,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An inertia-infused ADMM-based splitting algorithm with parallel computing for traffic assignment","authors":"Pengjie Liu ,&nbsp;Hu Shao ,&nbsp;Emily Zhu Fainman ,&nbsp;Feng Shao ,&nbsp;Shengbei Xu ,&nbsp;Chunkai Tang","doi":"10.1080/19427867.2025.2564421","DOIUrl":"10.1080/19427867.2025.2564421","url":null,"abstract":"<div><div>In this paper, we propose an inertia-infused alternating direction method of multipliers (ADMM)-based splitting algorithm for the origin-based traffic assignment problem. The method is framed as a sequential Gauss–Seidel update with Jacobi-type parallelization in each subproblem. A Nesterov-accelerated inertial strategy, using information from previous iterations, is applied before updating link flows. Within each decomposed block, link-flow subproblems are solved in parallel via the gradient projection method with inertia. In updating Lagrange multipliers, a nonnegative relaxation factor is incorporated to improve flexibility. Numerical experiments show that with properly chosen inertial and relaxation parameters, the proposed algorithm achieves superior performance compared with the original ADMM.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 3","pages":"Pages 463-480"},"PeriodicalIF":3.3,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147588124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ubiquitous Traffic Eyes: trajectory dataset focus on multiple traffic states and state transition on urban expressways","authors":"Ruyi Feng ,&nbsp;Huihuang Zhu ,&nbsp;N. N. Sze ,&nbsp;Shunchao Wang ,&nbsp;Zhibin Li","doi":"10.1080/19427867.2025.2559276","DOIUrl":"10.1080/19427867.2025.2559276","url":null,"abstract":"<div><div>Vehicle trajectory data provides critical information for traffic flow modeling and analysis during different traffic states and state transitions. This paper introduces a trajectory dataset based on aerial videos called Ubiquitous Traffic Eyes (UTE). It contains high-resolution vehicle trajectories automatically extracted from UAV videos, addressing issues such as pixel shake, vehicle detection, and trajectory fragment reconstruction. To bridge the gap in available data for traffic transition conditions, UTE captures data from typical state transition periods and fixed bottleneck locations, such as interweave areas. The current dataset includes data from seven distinct locations, encompassing freeway basic segments, merge/diverge segments, and weaving segments. The dataset presents trajectory data under diverse traffic conditions, including free flow, congestion, and transitions. This facilitates a comprehensive analysis of how traffic evolves and adapts, particularly in regions characterized by frequent maneuvers. The dataset is available at <span><span>http://seutraffic.com/</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 2","pages":"Pages 446-462"},"PeriodicalIF":3.3,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147427491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drone-truck collaborative scheduling with simultaneous delivery and pickup under uncertainty","authors":"Zhaojie Wang ,&nbsp;Feifeng Zheng ,&nbsp;Yang Sui ,&nbsp;Hongjie Pan ,&nbsp;Hejie Zhang ,&nbsp;Ming Liu","doi":"10.1080/19427867.2025.2543379","DOIUrl":"10.1080/19427867.2025.2543379","url":null,"abstract":"<div><div>This work investigates a drone-truck collaborative scheduling problem, where customer packages may require delivery or pickup for transportation to the distribution center. In this study, the transportation speed of drones is subject to uncertainty arising from variables such as wind direction and intensity, etc. For solving the problem, a K-means with elbow method is firstly employed to cluster the 2D coordinate of customers, yielding cluster centers that represent the points requiring traversal by the truck. Subsequently, a mixed integer programming model with the objective of minimizing the weighted sum of the total transportation time and the total energy consumption of drones is formulated. For such the model, both the truck routing path and the drone scheduling plan for delivery and pickup are jointly optimized at the tactical level. To solve the model under uncertainty, a data-driven robust optimization approach is developed. Numerical experiments are conducted to demonstrate the effectiveness of our approaches.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 2","pages":"Pages 270-288"},"PeriodicalIF":3.3,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147427492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}