Prediction-Preview Cooperative Steering Control for Optimal Path Tracking in Autonomous Electric Vehicles

Optimal path tracking is a fundamental requirement for autonomous electric vehicles to ensure safety, stability, and driving comfort. This paper introduces a Prediction–Preview Cooperative Steering Control (MPC–PEM) method, which is a prediction-based steering control strategy designed to minimize lateral and heading errors. The approach utilizes a technique referred to as Preview Error Minimization (PEM). The controller predicts vehicle dynamics within a limited preview horizon to generate anticipative steering actions that adapt to road curvature and speed variations. A bicycle model is employed to represent the lateral–yaw dynamics, while the control law is formulated by considering system constraints and stability margins. Simulation results demonstrate that the proposed prediction–preview approach significantly improves tracking accuracy compared to conventional LQR and MPC methods, as evidenced by smaller heading and lateral errors, smoother steering angles, and more stable and realistic dynamic responses. This method offers an efficient, adaptive, and reliable steering control solution for the next generation of autonomous electric vehicles.