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原文传递 Modeling Automated Vehicle Crashes with a Focus on Vehicle At-Fault, Collision Type, and Injury Outcome

题名：	Modeling Automated Vehicle Crashes with a Focus on Vehicle At-Fault, Collision Type, and Injury Outcome
正文语种：	eng
作者：	Kutela, Boniphace;Avelar, Raul E.;Bansal, Prateek
作者单位：	Texas A&M Transportat Inst Roadway Safety Program 1111 RELLIS Pkwy Bryan TX 77807 USA;Texas A&M Transportat Inst Roadway Safety Program 1111 RELLIS Pkwy Bryan TX 77807 USA;Natl Univ Singapore Dept Civil & Environm Engn 21 Lower Kent Ridge Rd Singapore 119077 Singapore
关键词：	Automated vehicles (AV);Bayesian network;Mixed traffic;Rear-end crash
摘要：	Automated vehicle (AV) technology is expected to make roads safer. However, until recently only a handful of studies could test such hypotheses due to limited access to testing data. This study contributes to the literature by jointly analyzing the associated factors of three interrelated outcome variables-vehicle at fault, collision type, and injury outcome in AV-involved crashes. We use Bayesian networks to analyze the manually extracted data from reports of 333 AV-involved crashes that occurred in California between January 2017 and October 2021. The summary statistics indicate that rear-end collisions are the dominant (63.5%), while AVs are at fault for a small proportion of crashes (14.4%), and a majority of crashes (84.4%) are noninjury. The joint inferences of the Bayesian networks show that irrespective of the collision type, when the AV is at fault, the chance of the physical injury in a crash increases significantly. Further, the chance of an AV being at fault seems higher in parking locations, and during driving at wet pavements in unclear weather. The chances of AV rear-end collisions are lower in the parking lot, and when nonvehicular participants are involved but increase in high traffic flow roadways. We also find that the likelihood of physical injury is higher at high-speed locations, intersections, and wet pavements. These insights suggest specific areas (unsignalized intersections, less structured right-of-way rules, and wet pavements) where technological improvements could enhance the safety performance of AVs.
出版年：	2022
期刊名称：	Journal of Transportation Engineering
卷：	148
期：	6
页码：	04022024.1-04022024.11