Scott Kelley , Cole Peiffer , Fei Guan , Hao Xu , James Okorocha , Kelly Dunn , Carlos Cardillo
{"title":"Mapping and quantifying near-miss events involving vehicles and vulnerable road users in Reno and Sparks, Nevada","authors":"Scott Kelley , Cole Peiffer , Fei Guan , Hao Xu , James Okorocha , Kelly Dunn , Carlos Cardillo","doi":"10.1016/j.trip.2025.101514","DOIUrl":null,"url":null,"abstract":"<div><div>Rising injury and fatality rates of vulnerable road users (VRUs) challenge policy efforts to make roads safer and contribute to public hesitancy to bike or walk more. To date, data-driven solutions to address VRU safety often rely on official crash data, but these data are limited in reflecting total safety experiences of VRUs. Near-miss events, which occur when a crash involving a vehicle and a VRU is narrowly averted, also contribute to hesitancy to bike or walk, but comparatively little is known about their location and frequency relative to official crashes. To address this, we distributed a web-based survey to bicyclists and pedestrians in Reno and Sparks, Nevada, USA. Analysis of their survey responses reveals that most traveled as a VRU frequently and had concerns about infrastructure and their safety. Using an interactive map, 175 respondents identified 277 locations where they either previously experienced a near-miss or felt unsafe with traveling as a VRU. We deployed mobile roadside LiDAR sensors to continuously collect data over two 72-hour periods in October 2023 at the 10 most frequently identified intersections in the survey responses. We recorded 251 near-miss events between vehicles and either bicyclists or pedestrians using LiDAR trajectory data and the post-encroachment time (PET) near-miss detection method. Our results underscore the prevalence of near-misses, as only 26 official crashes were recorded at these same intersections over the previous five years. The observed high relative frequency of near-miss events underscores the importance of integrating near-miss events into countermeasure planning.</div></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":"32 ","pages":"Article 101514"},"PeriodicalIF":3.9000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Interdisciplinary Perspectives","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590198225001939","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0
Abstract
Rising injury and fatality rates of vulnerable road users (VRUs) challenge policy efforts to make roads safer and contribute to public hesitancy to bike or walk more. To date, data-driven solutions to address VRU safety often rely on official crash data, but these data are limited in reflecting total safety experiences of VRUs. Near-miss events, which occur when a crash involving a vehicle and a VRU is narrowly averted, also contribute to hesitancy to bike or walk, but comparatively little is known about their location and frequency relative to official crashes. To address this, we distributed a web-based survey to bicyclists and pedestrians in Reno and Sparks, Nevada, USA. Analysis of their survey responses reveals that most traveled as a VRU frequently and had concerns about infrastructure and their safety. Using an interactive map, 175 respondents identified 277 locations where they either previously experienced a near-miss or felt unsafe with traveling as a VRU. We deployed mobile roadside LiDAR sensors to continuously collect data over two 72-hour periods in October 2023 at the 10 most frequently identified intersections in the survey responses. We recorded 251 near-miss events between vehicles and either bicyclists or pedestrians using LiDAR trajectory data and the post-encroachment time (PET) near-miss detection method. Our results underscore the prevalence of near-misses, as only 26 official crashes were recorded at these same intersections over the previous five years. The observed high relative frequency of near-miss events underscores the importance of integrating near-miss events into countermeasure planning.