Nonlinear Model Predictive Path-Following Control with Steering Lag Compensation for Autonomous Vehicles

Autonomous driving is a cutting-edge field of automotive intelligence development that can effectively improve driving safety and alleviate traffic congestion. Path-following control is a vital control task for autonomous vehicles. However, the lag of the steering actuator can deteriorate path-following accuracy and system stability. This paper presents an efficient path-following control strategy for autonomous vehicles that ensures precise and stable navigation. To address the complex scenarios encountered in autonomous driving, this paper adopts the nonlinear model predictive control (NMPC) path-following control. Additionally, the issue of steering lag in path-following is solved by introducing a first-order lag system to the model. Finally, path-following simulations are carried out in contrast to NMPC neglecting the steering lag to verify the superiority of the strategy. The simulation results demonstrate that the path-following control accuracy increases by 81.45% and 38.08% in the two given scenarios, improving driving stability and tracking performance.