Rear-End Collision Risk Analysis for Autonomous Driving

Since there will be a mix of automated vehicles (AVs) and human-driven vehicles (HVs) on future roadways, in the literature, while many existing studies have investigated collisions where an AV hits an HV from behind, few studies have focused on the scenarios where an HV hits an AV from behind (called HV-AV collision). In this paper, we will investigate the HV-AV collision risk in the Stop-in-Lane (SiL) scenario. To achieve this aim, a Human-like Brake (HLB) model is proposed first to simulate the driver brake control. In particular, the joint distribution of Off-Road-Glance and Time-Headway is originally introduced to simulate the glance distraction of drivers during their dynamic vehicle control. Sequentially, a case study of HV-AV collisions in the SiL scenario of autonomous driving (AD) is conducted based on the HLB model, to reveal how the collision probability changes with respect to various parameters. The results of the case study provide us with an in-depth understanding of the dynamic driving conditions that lead to rear-end collisions in the SiL scenario.