{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T21:50:11Z","timestamp":1785880211213,"version":"3.56.0"},"reference-count":34,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52432010"],"award-info":[{"award-number":["52432010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Accident Analysis & Prevention"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.aap.2026.108639","type":"journal-article","created":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T20:22:39Z","timestamp":1782246159000},"page":"108639","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Cyclist behavioral persistence across consecutive intersections: Re-ID based analysis and intention prediction"],"prefix":"10.1016","volume":"235","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1331-3802","authenticated-orcid":false,"given":"Haojie","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziqian","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gang","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.aap.2026.108639_b0005","first-page":"48","article-title":"Crash modeling for intersections and segments along corridors: a Bayesian multilevel joint model with random parameters","volume":"16","author":"Alarifi","year":"2017","journal-title":"Anal. Methods Accid. Res"},{"key":"10.1016\/j.aap.2026.108639_b0010","first-page":"1","article-title":"Multi-camera trajectory based vehicle re-identification for robust traffic monitoring","volume":"2025","author":"Athilakshmi","year":"2025","journal-title":"Proc. ICAECT"},{"key":"10.1016\/j.aap.2026.108639_b0015","first-page":"32","article-title":"Comprehensive evaluation of signal-coordinated arterials on traffic safety","volume":"21","author":"Fan","year":"2019","journal-title":"Anal. Methods Accid. Res"},{"key":"10.1016\/j.aap.2026.108639_b0020","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1080\/19475683.2025.2453550","article-title":"A GIS based spatiotemporal modelling approach for cycling risk mapping using crowd-sourced sensor data","volume":"31","author":"Feizizadeh","year":"2025","journal-title":"Ann. GIS"},{"key":"10.1016\/j.aap.2026.108639_b0025","first-page":"893","article-title":"Cyclist intention estimation at signalized intersections using deep neural networks","author":"Gu","year":"2023","journal-title":"IEEE GCCE"},{"key":"10.1016\/j.aap.2026.108639_b0030","unstructured":"Guo, F., Wang, X., & Abdel-Aty, M. (2009). Corridor-level signalized intersection safety analysis using Bayesian spatial models. Transportation Research Board 88th Annual Meeting, 09-1163."},{"issue":"1","key":"10.1016\/j.aap.2026.108639_b0035","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.aap.2009.07.005","article-title":"Modeling signalized intersection safety with corridor-level spatial correlations","volume":"42","author":"Guo","year":"2010","journal-title":"Accid. Anal. Prev."},{"key":"10.1016\/j.aap.2026.108639_b0040","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.aap.2018.03.006","article-title":"Exploring unobserved heterogeneity in bicyclists\u2019 red-light running behaviors at different crossing facilities","volume":"115","author":"Guo","year":"2018","journal-title":"Accid. Anal. Prev."},{"key":"10.1016\/j.aap.2026.108639_b0045","doi-asserted-by":"crossref","first-page":"1341","DOI":"10.5198\/jtlu.2021.2112","article-title":"Advances in pedestrian travel monitoring: Temporal patterns and spatial characteristics using pedestrian push-button data from Utah traffic signals","volume":"14","author":"Humagain","year":"2021","journal-title":"J. Transp. Land Use"},{"key":"10.1016\/j.aap.2026.108639_b0050","unstructured":"Jocher, G., Chaurasia, A., & Qiu, J. (2023). Ultralytics YOLOv8 (Version 8.0.0) [Software]. Available from https:\/\/github.com\/ultralytics\/ultralytics."},{"key":"10.1016\/j.aap.2026.108639_b0055","article-title":"Assessing the impact of traffic signal performance on crash frequency for signalized intersections along urban arterials: a random parameter modeling approach","volume":"149","author":"Kabir","year":"2020","journal-title":"Accid. Anal. Prev."},{"key":"10.1016\/j.aap.2026.108639_b0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.trc.2021.103453","article-title":"A context-aware pedestrian trajectory prediction framework for automated vehicles","volume":"134","author":"Kalatian","year":"2022","journal-title":"Transp. Res. Part C Emerging Technol."},{"key":"10.1016\/j.aap.2026.108639_b0065","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1016\/j.jsr.2022.09.005","article-title":"The impacts of non-motorized traffic enforcement cameras on red light violations of cyclists at signalized intersections","volume":"83","author":"Lv","year":"2022","journal-title":"J. Saf. Res."},{"key":"10.1016\/j.aap.2026.108639_b0070","doi-asserted-by":"crossref","DOI":"10.1016\/j.compenvurbsys.2020.101554","article-title":"Space-time analytics of human physiology for urban planning","volume":"85","author":"Millar","year":"2021","journal-title":"Comput. Environ. Urban Syst."},{"key":"10.1016\/j.aap.2026.108639_b0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2023.107156","article-title":"How do cyclists interact with motorized vehicles at unsignalized intersections? Modeling cyclists' yielding behavior using naturalistic data","volume":"190","author":"Mohammadi","year":"2023","journal-title":"Accid. Anal. Prev."},{"key":"10.1016\/j.aap.2026.108639_b0080","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1016\/j.jsr.2024.05.007","article-title":"Understanding the interaction between cyclists and motorized vehicles at unsignalized intersections: results from a cycling simulator study","volume":"90","author":"Mohammadi","year":"2024","journal-title":"J. Saf. Res."},{"key":"10.1016\/j.aap.2026.108639_b0085","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2022.106872","article-title":"Incorporating driving volatility measures in safety performance functions: improving safety at signalized intersections","volume":"178","author":"Mohammadnazar","year":"2022","journal-title":"Accid. Anal. Prev."},{"key":"10.1016\/j.aap.2026.108639_b0090","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1109\/OJITS.2022.3169700","article-title":"A Data-Driven Model for Pedestrian Behavior Classification and Trajectory Prediction","volume":"3","author":"Papathanasopoulou","year":"2022","journal-title":"IEEE Open Journal of Intelligent Transportation Systems"},{"key":"10.1016\/j.aap.2026.108639_b0095","series-title":"Paying attention to vehicles: a systematic review on transformer-based vehicle re-identification","author":"Qian","year":"2024"},{"key":"10.1016\/j.aap.2026.108639_b0100","first-page":"657","article-title":"Context-based prediction for crossing intentions of cyclists at signalized intersections","author":"Song","year":"2022","journal-title":"IEEE GCCE"},{"issue":"1","key":"10.1016\/j.aap.2026.108639_b0105","doi-asserted-by":"crossref","DOI":"10.1016\/j.multra.2022.100049","article-title":"Investigating pedestrian behaviour in urban environments: a Wi-Fi tracking and machine learning approach","volume":"2","author":"Stanitsa","year":"2023","journal-title":"Multimodal Transportation"},{"key":"10.1016\/j.aap.2026.108639_b0110","first-page":"1","article-title":"YOLOv8: a novel object detection algorithm with enhanced performance and robustness","volume":"2024","author":"Varghese","year":"2024","journal-title":"International Conference on Advances in Data Engineering and Intelligent Computing Systems (ADICS)"},{"key":"10.1016\/j.aap.2026.108639_b0115","doi-asserted-by":"crossref","first-page":"45556","DOI":"10.1109\/ACCESS.2020.2978344","article-title":"A comprehensive overview of person re-identification approaches","volume":"8","author":"Wang","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.aap.2026.108639_b0120","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.aap.2011.06.001","article-title":"The red-light running behavior of electric bike riders and cyclists at urban intersections in China: an observational study","volume":"49","author":"Wu","year":"2012","journal-title":"Accid. Anal. Prev."},{"issue":"18","key":"10.1016\/j.aap.2026.108639_b0125","doi-asserted-by":"crossref","first-page":"7830","DOI":"10.3390\/s23187830","article-title":"Traffic Agents Trajectory Prediction based on Spatial\u2013Temporal Interaction attention","volume":"23","author":"Xie","year":"2023","journal-title":"Sensors"},{"key":"10.1016\/j.aap.2026.108639_b0130","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.aap.2012.10.003","article-title":"Corridor-level signalized intersection safety analysis in Shanghai using Bayesian hierarchical models","volume":"50","author":"Xie","year":"2013","journal-title":"Accid. Anal. Prev."},{"issue":"12","key":"10.1016\/j.aap.2026.108639_b0135","doi-asserted-by":"crossref","first-page":"7619","DOI":"10.1109\/TITS.2020.3006047","article-title":"Vehicle re-identification with image processing and car-following model using multiple surveillance cameras from urban arterials","volume":"22","author":"Xiong","year":"2021","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.aap.2026.108639_b0140","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.aap.2014.10.014","article-title":"A hazard-based duration model for analyzing crossing behavior of cyclists and electric bike riders at signalized intersections","volume":"74","author":"Yang","year":"2015","journal-title":"Accid. Anal. Prev."},{"key":"10.1016\/j.aap.2026.108639_b0145","article-title":"Advances in vehicle re-identification techniques: a survey","volume":"614","author":"Yi","year":"2024","journal-title":"Neurocomputing"},{"issue":"24","key":"10.1016\/j.aap.2026.108639_b0150","doi-asserted-by":"crossref","first-page":"3162","DOI":"10.3390\/math9243162","article-title":"Trends in Vehicle Re-Identification past, present, and Future: a Comprehensive Review","volume":"9","author":"Zakria","year":"2021","journal-title":"Mathematics"},{"issue":"8","key":"10.1016\/j.aap.2026.108639_b0155","doi-asserted-by":"crossref","first-page":"12877","DOI":"10.1109\/TITS.2021.3118206","article-title":"Vehicle re-identification for lane-level travel time estimations on congested urban road networks using video images","volume":"23","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.aap.2026.108639_b0160","article-title":"Investigating different types of red-light running behaviors among urban e-bike rider mixed groups","volume":"1977388","author":"Zhang","year":"2021","journal-title":"J. Adv. Transp."},{"key":"10.1016\/j.aap.2026.108639_b0165","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2021.105977","article-title":"Analysis of factors influencing delivery e-bikes\u2019 red-light running behavior: a correlated mixed binary logit approach","volume":"152","author":"Zhang","year":"2021","journal-title":"Accid. Anal. Prev."},{"key":"10.1016\/j.aap.2026.108639_b0170","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"3701","article-title":"Omni-scale feature learning for person re-identification","author":"Zhou","year":"2019"}],"container-title":["Accident Analysis & Prevention"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0001457526002484?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0001457526002484?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T21:26:48Z","timestamp":1785878808000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0001457526002484"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":34,"alternative-id":["S0001457526002484"],"URL":"https:\/\/doi.org\/10.1016\/j.aap.2026.108639","relation":{},"ISSN":["0001-4575"],"issn-type":[{"value":"0001-4575","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Cyclist behavioral persistence across consecutive intersections: Re-ID based analysis and intention prediction","name":"articletitle","label":"Article Title"},{"value":"Accident Analysis & Prevention","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.aap.2026.108639","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"108639"}}