We propose a risk-aware crash mitigation system (RCMS), to augment any
existing motion planner (MP), that enables an autonomous vehicle to perform
evasive maneuvers in high-risk situations and minimize the severity of
collision if a crash is inevitable. In order to facilitate a smooth transition
between RCMS and MP, we develop a novel activation mechanism that combines
instantaneous as well as predictive collision risk evaluation strategies in a
unified hysteresis-band approach. For trajectory planning, we deploy a modular
receding horizon optimization-based approach that minimizes a smooth
situational risk profile, while adhering to the physical road limits as well as
vehicular actuator limits. We demonstrate the performance of our approach in a
simulation environment.Comment: Presented at the 26th IEEE International Conference on Intelligent
Transportation Systems (ITSC) 2023, Bilbao, Bizkaia, Spai