Divergent Effects of Factors on Crash Severity under Autonomous and Conventional Driving Modes Using a Hierarchical Bayesian Approach

Abstract

Influencing factors on crash severity involved with autonomous vehicles (AVs) have been paid increasing attention. However, there is a lack of comparative analyses of those factors between AVs and human-driven vehicles. To fill this research gap, the study aims to explore the divergent effects of factors on crash severity under autonomous and conventional (i.e., human-driven) driving modes. This study obtained 180 publicly available autonomous vehicle crash data, and 39 explanatory variables were extracted from three categories, including environment, roads, and vehicles. Then, a hierarchical Bayesian approach was applied to analyze the impacting factors on crash severity (i.e., injury or no injury) under both driving modes with considering unobserved heterogeneities. The results showed that some influencing factors affected both driving modes, but their degrees were different. For example, daily visitors’ flowrate had a greater impact on the crash severity under the conventional driving mode. More influencing factors only had significant impacts on one of the driving modes. For example, in the autonomous driving mode, mixed land use increased the severity of crashes, while daytime had the opposite effects. This study could contribute to specifying more appropriate policies to reduce the crash severity of both autonomous and human-driven vehicles especially in mixed traffic conditions.

Leveraging autonomous vehicles crash narratives to understand the patterns of parking-related crashes

“…A scan of studies that used real AVs crash data from California suggests mixed findings. However, only two studies, Ren et al (2022) and Xu et al (2019), have some details regarding parking-related crashes.…”

“…According to Ren et al (2022), on-street parking is associated with an increased likelihood of severe AV crashes. However, the observation does not indicate that the AV was involved in parking-related crashes.…”

Establishing Emergency Sections on Land Roads in Order to Improve the Quality of Transport Services, Creating Comfortable Conditions for International and Local Traffic

“…For this reason, other causes of the traffic accident, such as the technical condition of the car [26,27,28] and the road infrastructure, are also being examined [29,30,31]. Some researchers see the improvement of safety in the technology of autonomous vehicles [32,33,34], but this is still a distant prospect.…”

Investigating the impacts of autonomous vehicles on crash severity and traffic safety

“…Robinson et al (2022) explored the moral dilemma presented by unavoidable collisions and discussed the implications of existing studies; however, they failed to consider the real-world safety of AVs. Many researchers have utilized the CA DMV data to evaluate the actual performance of AVs (Xu et al, 2019;Sinha et al, 2021), and Yuan et al (2022) and Ren et al (2022), analyzed the data to determine the factors that influence the severity of the crashes. Unfortunately, however, they failed to combine the data with that obtained from a literature review or discuss the policy impacts of unavoidable collisions and the public perception of AV safety.…”