Identifying Factors Affecting Fatal Crashes Involving At-Fault and Not-At-Fault Level 1 and Level 2 Automated Vehicles

Abstract

Recent technological advancements, especially automated vehicles (AVs), are likely to reduce human involvement while driving by assisting drivers in various tasks such as steering, accelerating, or braking. The effect of AVs with different levels of automation on crash occurrence, especially considering fatal crashes, could vary based on road geometry and weather conditions. In addition, the factors affecting crashes where AVs are at-fault could differ from those affecting crashes where AVs are not at-fault, demanding further research. Therefore, this study focuses on identifying the factors affecting fatal crashes involving at-fault and not-at-fault level 1 and level 2 AVs using crash data from the United States. The partial proportionality odds modeling technique was used to develop two separate models for crashes involving at-fault and not-at-fault AVs. The results showed that level 1 and level 2 AVs have higher odds of getting involved in crashes with pedestrians and bicyclists due to their fault. In addition, they have higher odds of getting involved in crashes at intersections, at entry/exit ramps, and on one-way roads due to the fault of other drivers. The results from this study help enhance traffic safety, considering crash involvement factors of not-at-fault and at-fault AVs. Moreover, they assist the practitioners in developing safety countermeasures and manufacturers to improve smart features, especially for AVs with higher levels of automation.