A probabilistic reasoning approach to analyze the severity of single-vehicle crashes at mid-ramp locations

{"title":"A probabilistic reasoning approach to analyze the severity of single-vehicle crashes at mid-ramp locations","authors":"","doi":"10.1016/j.ijtst.2023.10.002","DOIUrl":null,"url":null,"abstract":"<div><div>Freeway ramps are one of the roadway elements that are considered as crash-prone sites with relatively more crashes per mile than other freeway segments. Among other crash types that occurred on freeway ramps, single-vehicle crashes have been found to be more severe. Thus, understanding the factors influencing the severity of single-vehicle crashes on freeway ramps is essential in improving the safety of our limited-access facilities. This study adopted a discrete Bayesian network (BN) approach to explore the probabilistic relationship among the potential factors associated with the severity of single-vehicle crashes at mid-ramp locations. The analysis was based on 6 041 single-vehicle crashes that occurred at the mid-ramp locations in California from 2009 to 2017. The findings indicated that ramp type, ramp traffic volume, road surface condition, and time of day were directly associated with the severity of single-vehicle crashes at the mid-ramp locations. The interdependency of off-ramps, ramp AADT of less than 13 000 vehicles per day, dry road surface condition, and off-peak hours were associated with the highest risk of fatal/severe injury crashes involving a single-vehicle. The study findings could potentially be used by transportation agencies in planning and implementing several strategies to improve the safety of freeway ramps.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"15 ","pages":"Pages 260-270"},"PeriodicalIF":4.3000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Transportation Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2046043023000783","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

Freeway ramps are one of the roadway elements that are considered as crash-prone sites with relatively more crashes per mile than other freeway segments. Among other crash types that occurred on freeway ramps, single-vehicle crashes have been found to be more severe. Thus, understanding the factors influencing the severity of single-vehicle crashes on freeway ramps is essential in improving the safety of our limited-access facilities. This study adopted a discrete Bayesian network (BN) approach to explore the probabilistic relationship among the potential factors associated with the severity of single-vehicle crashes at mid-ramp locations. The analysis was based on 6 041 single-vehicle crashes that occurred at the mid-ramp locations in California from 2009 to 2017. The findings indicated that ramp type, ramp traffic volume, road surface condition, and time of day were directly associated with the severity of single-vehicle crashes at the mid-ramp locations. The interdependency of off-ramps, ramp AADT of less than 13 000 vehicles per day, dry road surface condition, and off-peak hours were associated with the highest risk of fatal/severe injury crashes involving a single-vehicle. The study findings could potentially be used by transportation agencies in planning and implementing several strategies to improve the safety of freeway ramps.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
分析匝道中段单车碰撞严重程度的概率推理方法
与其他高速公路路段相比,高速公路匝道是每英里碰撞事故相对较多的易发路段之一。在高速公路坡道上发生的其他撞车类型中,单车撞车事故更为严重。因此,了解影响高速公路匝道上单车碰撞严重程度的因素对于提高我们有限通行设施的安全性至关重要。本研究采用离散贝叶斯网络(BN)方法探讨了与匝道中间位置单车碰撞严重程度相关的潜在因素之间的概率关系。分析基于 2009 年至 2017 年在加利福尼亚州中间匝道位置发生的 6 041 起单车碰撞事故。研究结果表明,匝道类型、匝道交通量、路面状况和一天中的时间与中间匝道位置单车碰撞事故的严重程度直接相关。非匝道的相互依存性、匝道每日平均车流量少于 13 000 辆车、干燥的路面状况以及非高峰时段与涉及单车的致命/重伤交通事故的最高风险相关。交通机构在规划和实施改善高速公路匝道安全的若干策略时,有可能会用到这些研究结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
International Journal of Transportation Science and Technology
International Journal of Transportation Science and Technology Engineering-Civil and Structural Engineering
CiteScore
7.20
自引率
0.00%
发文量
105
审稿时长
88 days
期刊最新文献
An exploration of the preferences and mode choice behavior between autonomous demand-responsive transit and traditional buses Connected vehicle enabled hierarchical anomaly behavior management system for city-level networks Operational measures to maintaining physical distancing at railway stations Investigating the dynamics of speed and acceleration at merging and diverging sections using UAV based trajectory data Evaluating the impacts of major transportation disruptions – San Francisco Bay Area case study
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1