A Matched Case-Control Analysis of Autonomous vs Human-Driven Vehicle Accidents

Abstract

Despite the recent advancements that autonomous vehicles (AV) have shown in their potential to improve safety and operation, considering differences between AV and human-driven vehicles (HDV) in accidents remain unidentified due to the scarcity of real-world AV accident data. We investigate the difference in accident occurrence between AV levels and HDV by utilizing 2,100 AV (ADS and ADAS) and 35,113 HDV accident data. A matched case-control design was conducted to investigate the impact of different variables on the likelihood of accidents involving AV versus HDV. The analysis suggests that AVs tend to be safer than HDVs in many accident situations. Yet, the likelihood of an AV accident during dawn/dusk or while making turns is greater than that of HDVs in the same situations. Moreover, rear end accidents in which an AV hits an HDV are less common than those where an HDV hits an AV. Our research sheds light on the accident risk disparities between AVs and HDVs, informing future developments in AV technology and safety enhancements.

Analyzing Injury Severity of School Bus Crashes considering Temporal and Spatial Heterogeneity Using Random Parameters Ordered Probit Model

“…Echoing the methodologies of previous studies 34,37,38 , this approach also incorporates heterogeneity in means by de ning the random parameters as estimable, allowing for a nuanced analysis of individual differences.…”