Collision Avoidance for Autonomous Vehicles Based on MPC With Adaptive APF
Hongjiu Yang, Yongqi He, Yang Xu, Hai Feng Zhao
Abstract
In this paper, a model predictive control (MPC) strategy is developed to realize collision avoidance with dynamic obstacle vehicles for an autonomous vehicle. A novel collision constraint based on road width and vehicle shape is proposed to ensure a safe distance between the autonomous vehicle and an obstacle vehicle. A smooth path is guaranteed in collision avoidance by the adaptive artificial potential field (APF) method for the autonomous vehicle using the MPC strategy. Both recursive feasibility and practical stability are analyzed for the autonomous vehicle based on the MPC strategy with multiple constraints and variable longitudinal velocity. Experimental results are presented to demonstrate the effectiveness and superiority of the MPC strategy with the adaptive APF method.