Adaptive MPC-based Path Following Control for Autonomous Vehicles with Random Time Delays

TY - JOUR

T1 - Adaptive MPC-based Path Following Control for Autonomous Vehicles with Random Time Delays

AU - Yang, Chao

AU - Zhang, Ruixin

AU - Wang, Weida

AU - Zhang, Yuhang

AU - Wang, Qi

N1 - Publisher Copyright: © 1967-2012 IEEE.

PY - 2026

Y1 - 2026

N2 - Autonomous vehicles are further improved with the development of in-vehicle networks and X-by-wire technologies. Due to the increasing integration of vehicle systems and the growing complexity of control links, time delays in information transmission and execution have become increasingly prominent. Because of late responses to control inputs, autonomous vehicles have deterioration in terms of path following accuracy and control stability, which poses a threat to driving safety. To solve this problem, an adaptive model predictive path following control strategy is presented in this paper. Firstly, a real-time delay estimator is designed based on historical feedback information processing and the gradient descent algorithm. Secondly, based on the estimated delay, a delay-augmented model with variable dimension is proposed for adaptive control to mitigate the impact of time-varying delay. Meanwhile, a tube-based model predictive control method is modified for the proposed model to deal with uncertainties generated by time-varying delays. Finally, the proposed control strategy is verified by simulations and experiments in multiple cases. The results show that the proposed strategy achieved a smaller lateral offset than that in the ordinary model predictive control method, leading to a 52.86% improvement in accuracy under the existence of time-varying delays.

AB - Autonomous vehicles are further improved with the development of in-vehicle networks and X-by-wire technologies. Due to the increasing integration of vehicle systems and the growing complexity of control links, time delays in information transmission and execution have become increasingly prominent. Because of late responses to control inputs, autonomous vehicles have deterioration in terms of path following accuracy and control stability, which poses a threat to driving safety. To solve this problem, an adaptive model predictive path following control strategy is presented in this paper. Firstly, a real-time delay estimator is designed based on historical feedback information processing and the gradient descent algorithm. Secondly, based on the estimated delay, a delay-augmented model with variable dimension is proposed for adaptive control to mitigate the impact of time-varying delay. Meanwhile, a tube-based model predictive control method is modified for the proposed model to deal with uncertainties generated by time-varying delays. Finally, the proposed control strategy is verified by simulations and experiments in multiple cases. The results show that the proposed strategy achieved a smaller lateral offset than that in the ordinary model predictive control method, leading to a 52.86% improvement in accuracy under the existence of time-varying delays.

KW - Autonomous vehicle

KW - model predictive control

KW - path following

KW - time-varying delay

UR - https://www.scopus.com/pages/publications/105036239602

U2 - 10.1109/TVT.2026.3684029

DO - 10.1109/TVT.2026.3684029

M3 - Article

AN - SCOPUS:105036239602

SN - 0018-9545

JO - IEEE Transactions on Vehicular Technology

JF - IEEE Transactions on Vehicular Technology

ER -