ARBOA-optimized cascaded PI–FOPID–PID controller for robust vehicle lateral path tracking

Existing vehicle lateral control strategies often struggle with nonlinear dynamics across varying speeds, leading to overshoot, slow response, and limited robustness. To address these challenges, this research proposes a novel cascaded Proportional Integral and Fractional Order Proportional Integral Derivative (PI–FOPID–PID) controller, where the outer loop ensures long-term lateral and yaw-error convergence and the inner loop handles actuator dynamics and high-frequency disturbances. This cascaded structure significantly enhances robustness and tracking accuracy compared to conventional single-loop controllers. Optimal controller parameters are obtained using a hybrid Artificial Rabbits Optimization–Bobcat Optimization Algorithm (ARBOA). Simulation results demonstrate rapid convergence with a settling time of approximately 3 s, steady-state error below 0.15 m, and RMSE of 0.18 m. During a high-speed double-lane-change maneuver at 15 m/s, the maximum lateral deviation is limited to 0.12 m. The results confirm improved robustness to tire–road friction variations and superior stability during high-speed autonomous driving.