Transverse Longitudinal Emergency Collision Avoidance Algorithm Based on Quartic Bezier Curve

Aims: To enhance the safety of intelligent vehicle drivers and help them achieve active collision avoidance. Background: Existing research on intelligent vehicles' active collision avoidance focuses on reference path optimization and stability tracking control. However, there is relatively little research on collision avoidance in emergency accident scenarios. Longitudinal emergency braking collision avoidance technology has been relatively mature, while steering collision avoidance still needs a long time to develop. The research on joint steering and braking collision avoidance in emergency situations is still limited. Objective: Modeling the longitudinal and lateral safety distances based on the safety conditions of adjacent lanes, two active collision avoidance strategies are designed, namely the steering strategy and combined lateral and longitudinal collision avoidance strategy, with the aim of reducing the risk of collision. Methods: In the steering strategy, five control points are first determined sequentially according to steering collision constraints. Then, a collision avoidance path is established based on the quartic Bezier curve. To enhance the tracking of this path, an LQR path-tracking controller is employed to reduce errors via feed-forward and feedback control. In the case of a combined lateral and longitudinal collision avoidance strategy, the LQR and PID controllers are first adjusted and optimized, and then the collision avoidance path is replanned. Besides, the safety risks associated with braking and steering are taken into consideration, and constraints are set on the braking deceleration accordingly. Results: The effectiveness of the designed steering strategy and combined lateral and longitudinal collision avoidance strategy is verified through simulation results obtained by using CarSIM and Matlab/Simulink. They can effectively avoid collisions in emergency situations. Conclusion: The proposed collision avoidance algorithm can avoid collision in emergency scenarios and enhance the safety of autonomous driving.