Minimum decision of collision injury based on drivable area in unavoidable scene

The existing technology for assisted driving collision avoidance has improved the active safety of vehicles, but it is primarily designed for scenarios where collisions can be avoided. It is not suitable for situations where pedestrians suddenly intrude. Therefore, there is a need to develop a control strategy that can minimize collision injuries in unavoidable situations. This study focuses on typical collision scenarios where pedestrians suddenly intrude. It proposes a real-time online double-layer optimal pre-collision control strategy based on drivable area, using the Head Injury Criteria (HIC) as a quantifiable measure of collision injury. The upper-layer controller designs a cost function based on a three Degrees of Freedom (DOF) collision solving model to minimize collision injuries. It takes the constraints of vehicle dynamics, maximum front wheel steering angle, pedestrian avoidance into account, and the optimal pre-impact state point with the minimum HIC value is calculated in real-time. Meanwhile, the lower-layer controller is designed to track the optimal pre-impact state point using Model Predict Control (MPC) algorithm. The effectiveness of the proposed control strategy is verified through Simulink simulation, achieving the dual objectives of avoiding pedestrians suddenly intruding and minimizing passenger collision injuries.