Optimized adaptive MPC for lateral control of autonomous vehicles

2025/09/21 by Kebbati, Yassine, Puig, Vicenç, Ait-Oufroukh, Naima +2 · 5 citations
#FOS: Mathematics #Optimization and Control (math.OC)

paper · doi:10.48550/arxiv.2509.17215

Abstract

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. Code can be found here: https://github.com/yassinekebbati/Optimized_adaptive_MPC

Citations

• A Survey of Autonomous Driving: Common Practices and Emerging Technologies
• Adaptive MPC for Autonomous Lane Keeping
• A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles

Cited by

• RNN-based linear parameter varying adaptive model predictive control for autonomous driving
• Learning-based model predictive control with moving horizon state estimation for autonomous racing
• Coordinated PSO-PID based longitudinal control with LPV-MPC based lateral control for autonomous vehicles
• Autonomous driving using an optimized neural network based adaptive LPV-MPC controller
• Neural Network and ANFIS based auto-adaptive MPC for path tracking in autonomous vehicles
• A Survey on Deep Multi-Task Learning in Connected Autonomous Vehicles

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