Uniform Finite Time Safe Path Tracking Control for Obstacle Avoidance of Autonomous Vehicle via Barrier Function Approach
Jinheng Han, Junzhi Zhang, Chengkun He, Chen Lv, Henglai Wei, Junfeng Zhang, Shiyue Zhao
Abstract
Precise path tracking and agilely avoiding obstacles are essential for the stability and safety of autonomous driving. In this paper, we introduce a uniform safe path tracking control strategy that combines obstacle avoidance with path tracking via a barrier function. Unlike the conventional hierarchical collision avoidance methods, our approach employs an integral heuristic barrier function that addresses obstacle avoidance planning and reference trajectory tracking problems simultaneously. Via this, the complex safe trajectory following problem is simplified into a tractable yaw angle tracking problem. We then present a novel finite-time adaptive barrier function-based sliding mode controller that handles input saturation and enhances robustness. This ensures precise and robust yaw angle tracking within specified performance constraints. Moreover, the proposed approach achieves accelerated finite-time convergence compared to the exponential convergence rate. Finally, the Carsim-Simulink co-simulations and real-vehicle experiments validate the effectiveness and superiority of our method in addressing the path-tracking challenge, while upholding driving safety.