Path Tracking for Autonomous Vehicles Based on Nonlinear Model Predictive Control Method 2019-01-1017
Path planning and tracking are two important means for autonomous vehicle in obstacle avoidance in the last decade. In this study, the reference path is planned on the basis of the sigmoid function which represents the driver intent in accordance with obstacle information. Meanwhile, a nonlinear model predictive controller for path tracking of autonomous vehicles is proposed. The proposed controller drives vehicle to track the reference path by controlling the front steering angle and direct yaw moment. Computer simulation of a closed-loop driver–vehicle system based on CarSim and MATLAB/Simulink was performed to verify the feasibility and effectiveness of the controller.