Optimized adaptive MPC for lateral control of autonomous vehicles

Yassine Kebbati (1) , Vicenc Puig (2) , Naïma Aït Oufroukh (1) , Vincent Vigneron (1) , Dalil Ichalal (1)

1 IBISC - Informatique, BioInformatique, Systèmes Complexes
2 CS2AC

Autonomous vehicles are the upcoming solution to most transportation problems such as safety, comfort and efficiency. The steering control is one of the main important tasks in achieving autonomous driving. Model predictive control (MPC) is among the fittest controllers for this task due to its optimal performance and ability to handle constraints. This paper proposes an adaptive MPC controller (AMPC) for the path tracking task, and an improved PSO algorithm for optimising the AMPC parameters. Parameter adaption is realised online using a lookup table approach. The propose AMPC performance is assessed and compared with the classic MPC and the Pure Pursuit controller through simulations.

Keywords: Particle Swarm Optimization; Adaptive Control; Autonomous Vehicles; Optimization; Model Predictive Control

Domains: Automatic

Yassine Kebbati, Vicenc Puig, Naïma Aït Oufroukh, Vincent Vigneron, Dalil Ichalal. Optimized adaptive MPC for lateral control of autonomous vehicles. 9th International Conference on Control, Mechatronics and Automation (ICCMA 2021), Nov 2021, Luxembourg, Luxembourg. pp.95--103, ⟨10.1109/ICCMA54375.2021.9646218⟩. ⟨hal-03485108⟩