{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T16:07:10Z","timestamp":1785427630953,"version":"3.56.0"},"reference-count":72,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["202506090141"],"award-info":[{"award-number":["202506090141"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52525204"],"award-info":[{"award-number":["52525204"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52131203"],"award-info":[{"award-number":["52131203"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52232012"],"award-info":[{"award-number":["52232012"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52272343"],"award-info":[{"award-number":["52272343"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012154","name":"Graduate Research and Innovation Projects of Jiangsu Province","doi-asserted-by":"publisher","award":["KYCX24_0452"],"award-info":[{"award-number":["KYCX24_0452"]}],"id":[{"id":"10.13039\/501100012154","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Reliability Engineering & System Safety"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.ress.2026.112274","type":"journal-article","created":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T16:15:10Z","timestamp":1769271310000},"page":"112274","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":7,"special_numbering":"C","title":["A Bayesian hierarchical spatio-temporal generalized extreme value modeling for safety analysis from traffic conflicts"],"prefix":"10.1016","volume":"271","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-5082-984X","authenticated-orcid":false,"given":"Quansheng","family":"Yue","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0367-2673","authenticated-orcid":false,"given":"Yanyong","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8797-0541","authenticated-orcid":false,"given":"Tarek","family":"Sayed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5808-1489","authenticated-orcid":false,"given":"Pan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4692-639X","authenticated-orcid":false,"given":"Hao","family":"Lyu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"5","key":"10.1016\/j.ress.2026.112274_bib0001","first-page":"291","article-title":"The statistical analysis of crash-frequency data: a review and assessment of methodological alternatives","volume":"44","author":"Lord","year":"2010","journal-title":"Transp Res Part A"},{"key":"10.1016\/j.ress.2026.112274_bib0002","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.ress.2017.09.005","article-title":"Quantitative risk assessment of freeway crash casualty using high-resolution traffic data","volume":"169","author":"Xu","year":"2018","journal-title":"Reliab Eng Syst Safety"},{"key":"10.1016\/j.ress.2026.112274_bib0003","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1016\/j.ress.2018.07.035","article-title":"Traffic accident modelling via self-exciting point processes","volume":"180","author":"Li","year":"2018","journal-title":"Reliab Eng Syst Safety"},{"key":"10.1016\/j.ress.2026.112274_bib0004","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2022.108720","article-title":"Discovering injury severity risk factors in automobile crashes: a hybrid explainable AI framework for decision support","volume":"226","author":"Amini","year":"2022","journal-title":"Reliab Eng Syst Safety"},{"key":"10.1016\/j.ress.2026.112274_bib0005","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.aap.2017.02.022","article-title":"Crash data quality for road safety research: current state and future directions","volume":"130","author":"Imprialou","year":"2019","journal-title":"Accid Anal Prev"},{"issue":"4","key":"10.1016\/j.ress.2026.112274_bib0006","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1080\/03081069908717634","article-title":"Traffic conflict standards for intersections","volume":"22","author":"Sayed","year":"1999","journal-title":"Transp Plan Technol."},{"key":"10.1016\/j.ress.2026.112274_bib0007","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2024.107552","article-title":"Modeling temporal correlation and heterogeneity in real-time conflict rates using bayesian tobit models for signalized intersections","volume":"202","author":"Guo","year":"2024","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0008","article-title":"If it cannot be seen, can it be quantified? explicit and implicit risks in AV\u2013HV mixed traffic","author":"Xia","year":"2025","journal-title":"Reliab Eng Syst Safety"},{"issue":"7","key":"10.1016\/j.ress.2026.112274_bib0009","doi-asserted-by":"crossref","first-page":"6142","DOI":"10.1109\/TITS.2021.3083927","article-title":"A survey of driving safety with sensing, vehicular communications, and artificial intelligence-based collision avoidance","volume":"23","author":"Fu","year":"2021","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"10.1016\/j.ress.2026.112274_bib0010","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.trf.2024.12.002","article-title":"Investigating the effects of in-vehicle warning strategies to drivers: a driving simulator study","volume":"109","author":"Yue","year":"2025","journal-title":"Transp Res Part F"},{"key":"10.1016\/j.ress.2026.112274_bib0011","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109554","article-title":"Multi-scale collision risk estimation for maritime traffic in complex port waters","volume":"240","author":"Xin","year":"2023","journal-title":"Reliab Eng Syst Safety"},{"key":"10.1016\/j.ress.2026.112274_bib0012","article-title":"Modeling bidirectional mixed flow of pedestrians, bicycles and e-mopeds at signalized crosswalks","author":"Zhang","year":"2025","journal-title":"Reliab Eng Syst Safety"},{"key":"10.1016\/j.ress.2026.112274_bib0013","article-title":"A cross-comparison of different extreme value modeling techniques for traffic conflict-based crash risk estimation","volume":"44","author":"Niu","year":"2024","journal-title":"Anal Method Accid Res"},{"key":"10.1016\/j.ress.2026.112274_bib0014","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2025.108108","article-title":"Advanced traffic conflict analysis for safety evaluation at roundabouts under mixed traffic using extreme value theory","volume":"219","author":"Maji","year":"2025","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2024.107854","article-title":"Assessment of the collision risk on the road around schools during morning peak period","volume":"210","author":"Hu","year":"2025","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0016","series-title":"An introduction to statistical modeling of extreme values","volume":"vol. 208","author":"Coles","year":"2001"},{"key":"10.1016\/j.ress.2026.112274_bib0017","article-title":"Bayesian hierarchical modeling of the non-stationary traffic conflict extremes for crash estimation","volume":"23","author":"Zheng","year":"2019","journal-title":"Anal Method Accid Res"},{"key":"10.1016\/j.ress.2026.112274_bib0018","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2020.105772","article-title":"A hierarchical bayesian peak over threshold approach for conflict-based before-after safety evaluation of leading pedestrian intervals","volume":"147","author":"Guo","year":"2020","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0019","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2024.107717","article-title":"Bayesian hybrid gamma-GPD model for extreme traffic conflict threshold determination in the peak over threshold approach","volume":"206","author":"Yue","year":"2024","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2025.108249","article-title":"Bayesian hierarchical non-stationary hybrid modeling for threshold estimation in peak over threshold approach","volume":"223","author":"Yue","year":"2025","journal-title":"Accid Anal Prev"},{"issue":"4","key":"10.1016\/j.ress.2026.112274_bib0021","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1016\/j.aap.2006.02.003","article-title":"The extreme value theory approach to safety estimation","volume":"38","author":"Songchitruksa","year":"2006","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0022","article-title":"A multivariate method for evaluating safety from conflict extremes in real time","volume":"36","author":"Fu","year":"2022","journal-title":"Anal Method Accid Res"},{"key":"10.1016\/j.ress.2026.112274_bib0023","first-page":"1","article-title":"Analytic methods in accident research: methodological frontier and future directions","volume":"1","author":"Mannering","year":"2014","journal-title":"Anal Method Accid Res"},{"key":"10.1016\/j.ress.2026.112274_bib0024","series-title":"Statistical and econometric methods for transportation data analysis","author":"Washington","year":"2020"},{"key":"10.1016\/j.ress.2026.112274_bib0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2025.108164","article-title":"A spatial generalized extreme value framework for traffic conflict using max-stable process approach","volume":"220","author":"Yue","year":"2025","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0026","article-title":"Short-term conflict-based crash risk forecasting: a bayesian conditional peak-over-threshold approach","volume":"46","author":"Niu","year":"2025","journal-title":"Anal Method Accid Res"},{"issue":"1","key":"10.1016\/j.ress.2026.112274_bib0027","first-page":"826","article-title":"Real-time safety analysis using autonomous vehicle data: a bayesian hierarchical extreme value model","volume":"11","author":"Kamel","year":"2023","journal-title":"Transportm B"},{"key":"10.1016\/j.ress.2026.112274_bib0028","article-title":"Dynamic bayesian hierarchical peak over threshold modeling for real-time crash-risk estimation from conflict extremes","volume":"40","author":"Fu","year":"2023","journal-title":"Anal Method Accid Res"},{"key":"10.1016\/j.ress.2026.112274_bib0029","series-title":"Tech. Rep.","article-title":"A bridging analysis for estimating the benefits of active safety technologies","author":"Campbell","year":"1996"},{"key":"10.1016\/j.ress.2026.112274_bib0030","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.aap.2011.07.008","article-title":"Use of crash surrogates and exceedance statistics to estimate road safety","volume":"45","author":"Tarko","year":"2012","journal-title":"Accid Anal Prev"},{"issue":"4","key":"10.1016\/j.ress.2026.112274_bib0031","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1109\/TIV.2017.2768219","article-title":"Using extreme value theory for vehicle level safety validation and implications for autonomous vehicles","volume":"2","author":"\u00c5sljung","year":"2017","journal-title":"IEEE Trans Intell Veh"},{"key":"10.1016\/j.ress.2026.112274_bib0032","doi-asserted-by":"crossref","DOI":"10.1016\/j.trc.2024.104509","article-title":"A bivariate, non-stationary extreme value model for estimating opposing-through crash frequency by severity by applying artificial intelligence-based video analytics","volume":"160","author":"Howlader","year":"2024","journal-title":"Transp Res Part C"},{"key":"10.1016\/j.ress.2026.112274_bib0033","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.trc.2019.04.015","article-title":"From univariate to bivariate extreme value models: approaches to integrate traffic conflict indicators for crash estimation","volume":"103","author":"Zheng","year":"2019","journal-title":"Transp Res Part C"},{"key":"10.1016\/j.ress.2026.112274_bib0034","article-title":"Evaluating the safety of autonomous vehicle\u2013pedestrian interactions: an extreme value theory approach","volume":"35","author":"Alozi","year":"2022","journal-title":"Anal Method Accid Res"},{"key":"10.1016\/j.ress.2026.112274_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2025.108211","article-title":"Safety evaluation for heavy vehicle drivers using extreme value model based on the multi-source sensing data","volume":"221","author":"Zhang","year":"2025","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0036","article-title":"A hybrid modelling framework of machine learning and extreme value theory for crash risk estimation using traffic conflicts","volume":"36","author":"Hussain","year":"2022","journal-title":"Anal Method Accid Res"},{"key":"10.1016\/j.ress.2026.112274_bib0037","article-title":"A ship\u2013bridge collision risk assessment method based on surrogate safety measures and bivariate extreme value theory","author":"Liu","year":"2025","journal-title":"Reliab Eng Syst Safety"},{"key":"10.1016\/j.ress.2026.112274_bib0038","article-title":"Identification of adequate sample size for conflict-based crash risk evaluation: an investigation using bayesian hierarchical extreme value theory models","volume":"39","author":"Fu","year":"2023","journal-title":"Anal Method Accid Res"},{"key":"10.1016\/j.ress.2026.112274_bib0039","doi-asserted-by":"crossref","DOI":"10.1016\/j.trc.2022.103653","article-title":"How many are enough?: investigating the effectiveness of multiple conflict indicators for crash frequency-by-severity estimation by automated traffic conflict analysis","volume":"138","author":"Arun","year":"2022","journal-title":"Transp Res Part C"},{"key":"10.1016\/j.ress.2026.112274_bib0040","article-title":"Bayesian dynamic extreme value modeling for conflict-based real-time safety analysis","volume":"34","author":"Fu","year":"2022","journal-title":"Anal Method Accid Res"},{"key":"10.1016\/j.ress.2026.112274_bib0041","doi-asserted-by":"crossref","DOI":"10.1016\/j.tust.2024.106216","article-title":"Collision causal discovery and real-time prediction of freeway tunnels: a novel dual-task approach","volume":"155","author":"Jin","year":"2025","journal-title":"Tunnel Underground Space Technol"},{"key":"10.1016\/j.ress.2026.112274_bib0042","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.109787","article-title":"Deep forest with SHapley additive explanations on detailed risky driving behavior data for freeway crash risk prediction","volume":"141","author":"Ma","year":"2025","journal-title":"Eng Appl Artif Intell"},{"key":"10.1016\/j.ress.2026.112274_bib0043","article-title":"Stcagnn-rnkde: a traffic accident prediction model for spatiotemporal combinatorial attention graph neural networks using ripley\u2019s k and network kernel density estimation","author":"Gao","year":"2025","journal-title":"Reliab Eng Syst Safety"},{"key":"10.1016\/j.ress.2026.112274_bib0044","doi-asserted-by":"crossref","DOI":"10.1016\/j.measurement.2024.115783","article-title":"Real-time accident risk identification for freeway weaving segments based on video analytics","volume":"242","author":"Ma","year":"2025","journal-title":"Measurement"},{"key":"10.1016\/j.ress.2026.112274_bib0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2019.105429","article-title":"Predicting real-time traffic conflicts using deep learning","volume":"136","author":"Formosa","year":"2020","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0046","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2020.105660","article-title":"Real-time conflict-based bayesian tobit models for safety evaluation of signalized intersections","volume":"144","author":"Guo","year":"2020","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0047","article-title":"Real-time traffic conflict prediction at signalized intersections using vehicle trajectory data and deep learning","author":"Zhang","year":"2024","journal-title":"Int J Transp Sci Technol"},{"key":"10.1016\/j.ress.2026.112274_bib0048","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2024.107904","article-title":"Assessing the impact of car-following driving style on traffic conflict risk using asymmetric behavior model and explainable machine learning","volume":"211","author":"Ma","year":"2025","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0049","doi-asserted-by":"crossref","DOI":"10.1016\/j.trc.2025.105171","article-title":"Real-time lane-changing crash prediction model at the individual vehicle level using real-world trajectories prior to crashes","volume":"176","author":"Chen","year":"2025","journal-title":"Transp Res Part C"},{"key":"10.1016\/j.ress.2026.112274_bib0050","article-title":"Bayesian forecasting of short-term crash risk with conditional extreme value models: a comparison between one-stage and two-stage approaches","author":"Niu","year":"2025","journal-title":"Anal Method Accid Res"},{"key":"10.1016\/j.ress.2026.112274_bib0051","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2025.108065","article-title":"Dynamic short-term crash risk prediction from traffic conflicts at signalized intersections with emerging mixed traffic flow: a novel conflict indicator","volume":"217","author":"Fu","year":"2025","journal-title":"Accid Anal Prev"},{"issue":"6","key":"10.1016\/j.ress.2026.112274_bib0052","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1002\/env.764","article-title":"A bayesian hierarchical extreme value model for lichenometry","volume":"17","author":"Cooley","year":"2006","journal-title":"Environmetrics"},{"issue":"3","key":"10.1016\/j.ress.2026.112274_bib0053","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1007\/s10651-007-0078-0","article-title":"Hierarchical modeling for extreme values observed over space and time","volume":"16","author":"Sang","year":"2009","journal-title":"Environ Ecol Stat"},{"key":"10.1016\/j.ress.2026.112274_bib0054","first-page":"1","article-title":"Investigating risky driving events in urban corridors: a study with large-scale trajectory datasets","author":"Yue","year":"2025","journal-title":"J Transp Safety Secur"},{"key":"10.1016\/j.ress.2026.112274_bib0055","unstructured":"Hayward J.. Near miss determination through use of a scale of danger. Reliability Engineering and System Safety, 1972;."},{"key":"10.1016\/j.ress.2026.112274_bib0056","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.trc.2019.11.023","article-title":"On the new era of urban traffic monitoring with massive drone data: the pNEUMA large-scale field experiment","volume":"111","author":"Barmpounakis","year":"2020","journal-title":"Transp Res Part C"},{"key":"10.1016\/j.ress.2026.112274_bib0057","first-page":"29","article-title":"Multivariate space-time modeling of crash frequencies by injury severity levels","volume":"15","author":"Ma","year":"2017","journal-title":"Anal Method Accid Res"},{"key":"10.1016\/j.ress.2026.112274_bib0058","article-title":"Exploring the effects of area-level factors on traffic crash frequency by severity using multivariate space-time models","volume":"31","author":"Azimian","year":"2021","journal-title":"Anal Method Accid Res"},{"key":"10.1016\/j.ress.2026.112274_bib0059","doi-asserted-by":"crossref","first-page":"55","DOI":"10.3141\/2061-07","article-title":"Analysis of road crash frequency with spatial models","volume":"2061","author":"Aguero-Valverde","year":"2008","journal-title":"Transp Res Rec"},{"key":"10.1016\/j.ress.2026.112274_bib0060","first-page":"104","article-title":"Exploring spatio-temporal effects in traffic crash trend analysis","volume":"16","author":"Liu","year":"2017","journal-title":"Anal Method Accid Res"},{"key":"10.1016\/j.ress.2026.112274_bib0061","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.aap.2011.09.051","article-title":"Traffic safety among motorcyclists in norway: a study of subgroups and risk factors","volume":"49","author":"Bj\u00f8rnskau","year":"2012","journal-title":"Accid Anal Prev"},{"issue":"4","key":"10.1016\/j.ress.2026.112274_bib0062","doi-asserted-by":"crossref","first-page":"710","DOI":"10.1016\/j.aap.2009.03.010","article-title":"A review of risk factors and patterns of motorcycle injuries","volume":"41","author":"Lin","year":"2009","journal-title":"Accid Anal Prev"},{"issue":"8","key":"10.1016\/j.ress.2026.112274_bib0063","doi-asserted-by":"crossref","first-page":"1234","DOI":"10.1016\/j.ssci.2007.07.005","article-title":"Modelling motorcyclist injury severity by various crash types at t-junctions in the UK","volume":"46","author":"Pai","year":"2008","journal-title":"Saf Sci"},{"key":"10.1016\/j.ress.2026.112274_bib0064","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2024.107864","article-title":"Driving against the clock: investigating the impacts of time pressure on taxi and non-professional drivers\u2019 safety and compliance","volume":"210","author":"Hussain","year":"2025","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0065","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/j.aap.2017.08.010","article-title":"Occupant-level injury severity analyses for taxis in hong kong: a bayesian space-time logistic model","volume":"108","author":"Meng","year":"2017","journal-title":"Accid Anal Prev"},{"issue":"2","key":"10.1016\/j.ress.2026.112274_bib0066","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.aap.2005.07.004","article-title":"Driving speed and the risk of road crashes: a review","volume":"38","author":"Aarts","year":"2006","journal-title":"Accid Anal Prev"},{"issue":"6","key":"10.1016\/j.ress.2026.112274_bib0067","doi-asserted-by":"crossref","first-page":"1107","DOI":"10.1016\/j.aap.2007.02.009","article-title":"Contributory factors to traffic crashes at signalized intersections in hong kong","volume":"39","author":"Wong","year":"2007","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0068","doi-asserted-by":"crossref","first-page":"63","DOI":"10.3141\/2318-08","article-title":"Exploring traffic safety and urban form in portland, oregon","volume":"2318","author":"Gladhill","year":"2012","journal-title":"Transp Res Rec"},{"key":"10.1016\/j.ress.2026.112274_bib0069","doi-asserted-by":"crossref","DOI":"10.1016\/j.trc.2020.102683","article-title":"A novel approach for real time crash prediction at signalized intersections","volume":"117","author":"Zheng","year":"2020","journal-title":"Transp Res Part C"},{"key":"10.1016\/j.ress.2026.112274_bib0070","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2024.107880","article-title":"Real-time risk estimation for active road safety: leveraging waymo AV sensor data with hierarchical bayesian extreme value models","volume":"211","author":"Anis","year":"2025","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112274_bib0071","first-page":"1","article-title":"Incorporating region-variability of model bias into liquefaction-triggering procedures for sandy and gravelly soils through BUS-powered hierarchical bayesian updating","volume":"62","author":"Wang","year":"2024","journal-title":"Canad Geotech J"},{"issue":"6","key":"10.1016\/j.ress.2026.112274_bib0072","doi-asserted-by":"crossref","first-page":"2967","DOI":"10.1785\/0120190244","article-title":"Vine copula-based dependence modeling of multivariate ground-motion intensity measures and the impact on probabilistic seismic slope displacement hazard analysis","volume":"110","author":"Wang","year":"2020","journal-title":"Bull Seismol Soc Am"}],"container-title":["Reliability Engineering & System Safety"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0951832026000906?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0951832026000906?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T12:23:58Z","timestamp":1774009438000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0951832026000906"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":72,"alternative-id":["S0951832026000906"],"URL":"https:\/\/doi.org\/10.1016\/j.ress.2026.112274","relation":{},"ISSN":["0951-8320"],"issn-type":[{"value":"0951-8320","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A Bayesian hierarchical spatio-temporal generalized extreme value modeling for safety analysis from traffic conflicts","name":"articletitle","label":"Article Title"},{"value":"Reliability Engineering & System Safety","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ress.2026.112274","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":"112274"}}