A Predictive Frontal and Oblique Collision Mitigation System for Autonomous Vehicles

Abstract

This paper presents a collision mitigation system for an unavoidable collision with an arbitrary oncoming obstacle vehicle. A set of candidate trajectories are generated by a model-based method and a hierarchical efficient collision-checking method is applied to check the potential collision between the predicted trajectory of the obstacle vehicle and the candidate trajectories of the ego vehicle. A novel method based on the vehicle polygon is applied to identify the specific impact location of the vehicle body. The predicted Delta-V and the identified impact location are combined to evaluate the outcome severity of the upcoming accident for each candidate trajectory. Based on the evaluated results, a path with the least damage would be selected and executed to mitigate the collision. Simulation and analysis are performed to investigate the performance of the presented system in a high-speed scenario of a detailed vehicle model.