Nested PID steering control for lane keeping in autonomous vehicles

In this paper a nested PID steering control in vision based autonomous vehicles is designed and experimentally tested to perform path following in the case of roads with an uncertain curvature. The control input is the steering wheel angle: it is designed on the basis of the yaw rate, measured by a gyroscope, and the lateral offset, measured by the vision system as the distance between the road centerline and a virtual point at a fixed distance from the vehicle. No lateral acceleration and no lateral speed measurements are required. A PI active front steering control based on the yaw rate tracking error is used to improve the vehicle steering dynamics. The yaw rate reference is computed by an external control loop which is designed using a PID control with a double integral action based on the lateral offset to reject the disturbances on the curvature which increase linearly with respect to time. The proposed control scheme leads to a nested architecture with two independent control loops that allows us to design standard PID controls in a multivariable context (two outputs, one input). The robustness of the controlled system is theoretically investigated with respect to speed variations and uncertain vehicle physical parameters. Several simulations are carried out on a standard big sedan CarSim vehicle model to explore the robustness with respect to unmodelled effects. The simulations show reduced lateral offset and new stable μ-splitμ-split braking maneuvres in comparison with the model predictive steering controller implemented by CarSim. Finally the proposed control law is successfully tested by experiments using a Peugeot 307 prototype vehicle on the test track in Satory, 20 km west of Paris.