Integrated planning and tracking control for vehicle dynamic obstacle avoidance with cooperation of longitudinal and lateral directions

Abstract

This study constructs an integrated obstacle avoidance control strategy that can account for both lateral and longitudinal dynamic obstacles, enabling vehicles to quickly and stably evade obstacles in even emergency scenarios, thereby preventing accidents in complex road environments. Firstly, based on the safety distance model, a risk area dynamic partition method that considers both lateral and longitudinal directions is established. Subsequently, within the Frenet coordinate system, quintic polynomial candidate paths are generated based on the vehicle’s acceleration, speed, and position before and after lane-changing, and the optimal path is determined with consideration of driving safety and comfort, as well as the constraints associated with it. Finally, utilizing a two-degree-of-freedom vehicle dynamics model and a lateral tracking error model, a lateral tracking controller based on Linear Quadratic Regulator (LQR) and a longitudinal tracking controller based on double Proportional-Integral-Derivative (PID) approach are designed. The results of hardware-in-the-loop experiments demonstrate that, compared to the LQR algorithm, the proposed strategy more effectively ensures the stability and obstacle avoidance capability of the vehicle during operation. Furthermore, data collected under various scenarios indicate that the proposed strategy meets the requirements for tracking performance and driving comfort while successfully ensuring obstacle avoidance. Overall, the proposed method satisfies the criteria for safety, comfort, and stability in vehicle obstacle avoidance within complex environments.