An Adaptive Constrained Path Following Control Scheme for Autonomous Electric Vehicles

To ensure driving safety, autonomous electric vehicles need to follow the planned path accurately, which depends on the vehicle path following control strategy. It is widely acknowledged that the model-based control strategies have excellent potential on path following, but their effect is seriously affected by the parametric uncertainty. To solve this problem, an adaptive constrained path following control scheme considering the influence of parametric uncertainty is proposed for autonomous electric vehicles. Firstly, an adaptive feedback control law and its update law are proposed to deal with the variation of tire cornering stiffness during vehicle path following process. Secondly, a constraint function for lateral displacement error during path following process is designed to further improve driving safety. And then, the closed-loop stability of the proposed control scheme is proved. Finally, the validation is implemented by simulation and experiment, the results show that the proposed control scheme is effective under different working conditions. The maximum lateral displacement error is reduced to 0.0297m by using the proposed scheme in the experiment. The proposed scheme might provide a theoretical reference for control practice of autonomous vehicles.

Automated summary

This paper proposes an adaptive constrained path following control scheme considering the influence of parametric uncertainty for autonomous electric vehicles. By utilizing adaptive feedback control law, designing a constraint function, and proving the closed-loop stability, the proposed scheme achieves effective driving safety and accurate path following.