Yikai Luo , Yuge Wang , Yan Li , Jinhua Xu , Hui Hu
{"title":"A post-disaster emergency logistics location-routing optimization method considering road risks","authors":"Yikai Luo , Yuge Wang , Yan Li , Jinhua Xu , Hui Hu","doi":"10.1080/19427867.2025.2528818","DOIUrl":"10.1080/19427867.2025.2528818","url":null,"abstract":"<div><div>Sudden natural disasters pose significant threats to lives, property, and infrastructure, underscoring the critical need to determine optimal locations for emergency reserve depots and plan efficient transportation routes. Therefore, this paper focuses on the location-routing optimization in emergency logistics following a disaster. In addition to the traditional considerations of rescue time and cost, we propose a novel approach that incorporates risk factors of transportation routes. The aim is to avoid secondary disasters during transport and improve rescue efficiency. Using the 2008 Wenchuan earthquake as a case, results show the hybrid machine learning CPSO-XGBoost approach employed as our road segment risk identification model achieves 0.9668 accuracy. Compared to NSGA-II, the improved ACONSGA-II algorithm shows superior optimization capability. Unlike traditional emergency location-routing models that overlook road risks, the proposed approach identifies safer location-routing solutions for material transport while maintaining rescue time and cost.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 1","pages":"Pages 72-87"},"PeriodicalIF":3.3,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146098762","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}
Son Van Pham , Akimasa Fujiwara , Makoto Chikaraishi , Anh Son Le , Nang Ho Xuan
{"title":"Mobility experiment twin for analyzing travel behavior decisions employing shared electric autonomous vehicles","authors":"Son Van Pham , Akimasa Fujiwara , Makoto Chikaraishi , Anh Son Le , Nang Ho Xuan","doi":"10.1080/19427867.2025.2525290","DOIUrl":"10.1080/19427867.2025.2525290","url":null,"abstract":"<div><div>The introduction of new mobility services (NMS) strongly depends on the public acceptance. Acceptance is evaluated by allowing users to experience these solutions before their widespread implementation. However, there is limited research on establishing robust frameworks for analyzing travel behavior decisions across the stages and environmental contexts of implementation. This study proposes the mobility experiment twin (MEXT) framework, which integrates cyber and physical experiments using a five-step approach. We introduced shared autonomous electric vehicles (SAEVs) as first-last-mile (FLM) urban mobility vehicles in Hanoi. Utilizing randomized controlled trials with cyber and physical groups to estimate the impact of MEXT. The users preferred SAEVs, willingly accepting longer travel times and higher costs, while young people were more inclined to adopt SAEVs with economic costs. Future works must consider more representative experimental locations and develop a theoretical model that better reflects the current SAEV situation in developing societies.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 1","pages":"Pages 23-38"},"PeriodicalIF":3.3,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146098760","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":"“Car sharers are not bigger tree-huggers than others: at least not in the Swedish forest”","authors":"John Magnus Roos","doi":"10.1080/19427867.2025.2537175","DOIUrl":"10.1080/19427867.2025.2537175","url":null,"abstract":"<div><div>Car sharing is often promoted as a sustainable mobility solution and a hallmark of the sharing economy. It is commonly assumed that environmental concerns are a key motivation for consumers who use car sharing services. However, previous studies offer mixed findings regarding the link between car sharing and environmental attitudes. Drawing on nationally representative survey data from 2019 to 2024 (<em>N</em> = 10,170), this study examines the relationship between consumers’ environmental attitudes and car sharing use. Results show that environmental attitudes have only limited influence. Most attitudinal measures, including general environmental concern and support for reducing car use, did not significantly differ (<em>p</em> < .05) between car sharers and non-car sharers. These findings challenge the notion that environmental motivations are central to car sharing adoption. Instead, they suggest that practical considerations, such as cost and convenience, may be more influential. In the context of Mobility as a Service (MaaS), this underscores the need to prioritize everyday mobility needs over assumed ecological values.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 1","pages":"Pages 179-193"},"PeriodicalIF":3.3,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146098797","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}
Qile Li , Zhizhen Liu , Lan Yao , Hangze Li , Guanzhi Xiong , Yuxuan Zhang
{"title":"Traffic signal coordinated control model for long arterial based on traffic flow spatiotemporal characteristics","authors":"Qile Li , Zhizhen Liu , Lan Yao , Hangze Li , Guanzhi Xiong , Yuxuan Zhang","doi":"10.1080/19427867.2025.2488971","DOIUrl":"10.1080/19427867.2025.2488971","url":null,"abstract":"<div><div>Traditional signal coordination methods face challenges in ensuring efficient traffic flow on long arterials due to urban expansion and complex spatiotemporal variations. However, existing methods struggle to achieve effective signal coordination under complex spatiotemporal variations, and lack methodological framework for universally applicable green wave coordination. To address this, a spatiotemporal partitioning-based green wave trajectory feature coordination optimization model is proposed. First, temporal partitioning is performed using an improved Fisher optimal segmentation method, while spatial subarea division is achieved via an enhanced K-Medoids algorithm. For each subarea, an arterial traffic signal control model is established based on green wave trajectory characteristics. Phase difference coordination equations are then applied to synchronize adjacent subareas. The model is validated on Foshan’s Lvjing Road, with evening peak performance compared against a classical green wave trajectory approach. Results indicate that the proposed model reduces vehicle average delay by 13.18% and the number of stops by 18.05%.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"17 10","pages":"Pages 1739-1754"},"PeriodicalIF":3.3,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665514","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}
Junting Lin , Maolin Li , Ning Qin , Mingjun Ni , Xiaohui Qiu
{"title":"An optimization method of high-speed train rescheduling based on PER-D3QN","authors":"Junting Lin , Maolin Li , Ning Qin , Mingjun Ni , Xiaohui Qiu","doi":"10.1080/19427867.2025.2496860","DOIUrl":"10.1080/19427867.2025.2496860","url":null,"abstract":"<div><div>This paper addresses delay problems from moderate and slight disturbances in high-speed train operation by constructing an optimization model that minimizes total train delay time, solved using reinforcement learning. The research introduces a linear programming method to balance rescheduling frequency and total delay time, proposing a dynamic adjustment method of state transfer step size based on reinforcement learning’s greedy strategy and train operation constraints. This approach shortens calculation time and improves solution quality. The simulation environment is on a single direction of the double-track railway from Beijing South Station to Jinan West Station, and three experimental scenarios are designed. The experimental results show that dynamic adjustment of state transfer step size reduces average algorithm computation time by 30.5% and average total train delay by 8.2%. Compared to the CPLEX solver-based strategy, the approach decreases average timetable generation time by 7.4%.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"17 10","pages":"Pages 1839-1855"},"PeriodicalIF":3.3,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665517","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":"Analyzing severity of vehicle–bicycle crashes: an explainable boosting machine strategy","authors":"Sheng Dong , Afaq Khattak , Feng Chen , Jibiao Zhou , Feifei Xu","doi":"10.1080/19427867.2025.2500817","DOIUrl":"10.1080/19427867.2025.2500817","url":null,"abstract":"<div><div>Vehicular crashes involving bicycles result in substantial annual fatalities, raising serious concerns for traffic safety authorities. Understanding the factors influencing crash severity is vital for designing effective countermeasures. However, the limited interpretability of many machine learning models complicates traffic safety assessments. This study introduces the Explainable Boosting Machine (EBM), a transparent glass-box model developed to predict the severity of vehicle–bicycle crashes and identify influential factors. A dataset of 5,341 crashes from the Ningbo Public Security Bureau (2020–2021) was analyzed. To address class imbalance, multiple data augmentation techniques were employed, and Bayesian optimization was used for hyperparameter tuning. EBM performance was benchmarked against black-box models, including LightGBM and XGBoost, using holdout evaluation. The EBM combined with borderline-SMOTE achieved a G-mean of 0.816 and an imbalanced accuracy of 0.651. Key predictors included weather and seasonal effects, with season–location interactions significantly influencing crash severity. This framework provides interpretable insights for data-driven traffic safety interventions and future research.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"17 10","pages":"Pages 1856-1869"},"PeriodicalIF":3.3,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665518","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}
Jinghui Wang , Yajuan Jiang , Xiaoying Zhang , Fangwei Deng , Wei Lv
{"title":"Discrepancies in Pedestrian Crossing of Static vs. Dynamic Crowds: An Experimental Study","authors":"Jinghui Wang , Yajuan Jiang , Xiaoying Zhang , Fangwei Deng , Wei Lv","doi":"10.1080/19427867.2025.2522592","DOIUrl":"10.1080/19427867.2025.2522592","url":null,"abstract":"<div><div>In this paper, we investigate disparities in pedestrian crossing behaviors within static and dynamic crowds through experimental analysis. First, qualitative trajectory observations revealed significant behavioral differences. To quantitatively assess these discrepancies, we introduced a metric termed the swarm factor. In static contexts, limited variations in speed and swarm factor were observed, which may contribute to the formation of cross-channels, a phenomenon of pedestrian self-organization (tactical level). In contrast, speed and swarm factor exhibited inverse synchronization in dynamic contexts, indicating density-dependent behavioral adaptation (operational level). Finally, orthogonal velocity analysis demonstrated a fundamental pattern in crossing motions: as global density increased, both instantaneous velocity and crossing velocity decreased, while transverse velocity remained stable.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"17 10","pages":"Pages 1904-1913"},"PeriodicalIF":3.3,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665520","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}
Nengye Mu , Yunjin Han , Huimei Fan , Peiling Tian , Yuanshun Wang , Dudu Guo
{"title":"Robustness assessment of a multilayer composite network with a two-stage fusion community detection algorithm","authors":"Nengye Mu , Yunjin Han , Huimei Fan , Peiling Tian , Yuanshun Wang , Dudu Guo","doi":"10.1080/19427867.2025.2496805","DOIUrl":"10.1080/19427867.2025.2496805","url":null,"abstract":"<div><div>Multimodal transportation, including aviation, high-speed rail, and waterways, is crucial for urban freight in China. To evaluate the robustness of urban freight networks, this study constructs a multilayer composite network model for aviation, high-speed rail, and waterways based on complex network theory. A two-stage fusion community detection algorithm (TFCA) is proposed for community partitioning. The study simulates network attack risks under deliberate attack strategies, based on network characteristics and community division results. Results show that nodes with high equilibrium centrality, mainly in East and Central China, require early intervention to enhance network robustness; the network is resilient against random risks but more vulnerable to attacks targeting high equilibrium centrality nodes; Adjusting capacity coefficients <em>φ</em>, <em>τ</em>, and <em>ε</em> can strengthen network robustness, with <em>τ</em> and <em>ε</em> having a more significant impact. These findings provide a scientific basis for optimizing urban freight networks and improving their overall risk resistance.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"17 10","pages":"Pages 1819-1838"},"PeriodicalIF":3.3,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665513","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}
Ziqian Zhang , Haojie Li , Wenzhang Yang , Gang Ren
{"title":"Evaluation of conflict classification methods in pedestrian safety analyses: a comparative study with practical guidance","authors":"Ziqian Zhang , Haojie Li , Wenzhang Yang , Gang Ren","doi":"10.1080/19427867.2025.2514986","DOIUrl":"10.1080/19427867.2025.2514986","url":null,"abstract":"<div><div>This study compares different conflict classification methods based on three surrogate safety indicators (PET, TTC, DST). Single-indicator measures (PET-based, TTC-based, DST-based thresholds) and mixed-indicator measures (Accumulative-percentile, Clustering, Manual-review) are evaluated. Results show PET-based thresholds method detects more serious conflicts, while TTC-based thresholds method identifies more minor conflicts. Among mixed methods, the classification results of Accumulative-percentile method largely depend on the selection of dividing percentiles, while Clustering method and Manual-review method differ mainly in ‘normal passage’ and ‘minor conflict’ proportions. For single-indicator measures, PET-based thresholds method covers the widest range of influencing factors, whereas TTC-based and DST-based methods focus more on ‘evasive action’ factors. Mixed-indicator measures generally identify more variables than single-indicator measures. We further provide practical guidance to help with the selection of conflict classification methods.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"17 10","pages":"Pages 1870-1887"},"PeriodicalIF":3.3,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665522","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":"Optimal location planning for battery exchange and charging stations for electric scooters in leisure areas considering stochastic user dwell times","authors":"Chih-Kang Lin , Shangyao Yan , Guan-Ting Ou","doi":"10.1080/19427867.2025.2521080","DOIUrl":"10.1080/19427867.2025.2521080","url":null,"abstract":"<div><div>Stochastic factors significantly affect the optimal planning for locating electric scooter charging stations and scheduling battery exchanges in real operations. A plan that does not account for stochastic factors might turn out to be overly optimistic when implemented in real-world operations, where such stochastic disturbances are common. In this study, we apply mathematical programming and network flow techniques to develop a model for determining the optimal locations of battery exchange and charging stations for electric scooters, while accounting for stochastic user dwell times in leisure areas. The proposed stochastic model, designed to address a location-scheduling problem, is formulated as a mixed-integer network flow problem with side constraints. We develop a simulation-based evaluation method and conduct computational tests to assess the model’s performance. Computational tests using real data from a city in Taiwan show that the stochastic model outperforms the deterministic model and has significant potential for practical applications.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"17 10","pages":"Pages 1888-1903"},"PeriodicalIF":3.3,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665516","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}