Autonomous path tracking control of intelligent electric vehicles based on lane detection and optimal preview method

Abstract In this paper, a novel autonomous tracking control (ATC) of intelligent electric vehicles (IEVs) based on lane detection and sliding-mode control (SMC) is innovatively developed to implement accurate path tracking and optimal torque distribution between the motors of IEVs. Initially, the road image was captured by the camera and was processed to extract the lane markings and to calculate the desired steering angle by the lateral trajectory tracking error and the head tracking error. Then, to accurately track the desired path, an optimal preview linear quadratic regulator (OP_LQR) based on SMC approach with 2-DOF vehicle model was proposed. To prove the effectiveness of the proposed OP_LQR scheme, the marking recognition analysis and the optimization results of the traditional three controllers are obtained and compared. Results show that the lane marking identification algorithm has high accuracy. Moreover, the actual path with the proposed method can better track the desired trajectory and appropriate differential braking torques are allocated into four wheels.