Steering and Speed Control System Design for Autonomous Vehicles by Developing an Optimal Hybrid Controller to Track Reference Trajectory

Abstract

In this paper, a longitudinal and lateral control system of an autonomous vehicle is presented by developing a novel hybrid trajectory tracking algorithm. In this proposed method, the longitudinal control system is developed based on the curvature information of the reference path. The autonomous vehicle modifies the desired speed according to the estimated size and types of the reference trajectory curves. This desired speed is integrated into the PID controller to maintain an optimal speed of the vehicle while following the given path. The lateral control system is designed based on feedforward (preview control) and feedback (LQR) controllers to reduce lateral errors between the trajectory and autonomous vehicle. The feedforward and the feedback controllers generate precise steering angles to eliminate orientation and lateral errors caused by the curvature of the trajectory and external disturbances. The effectiveness of the proposed method is evaluated by comparing simulation and experimental results with different trajectory tracking algorithms on simulated and experimented paths. It is proven that the proposed algorithm is capable of significantly minimizing lateral errors on sharp curves compared to other path tracking methods.