HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

Automatic Tuning of MPC for Autonomous Vehicle using Bayesian Optimization

Abstract : The purpose of this paper is to develop an automated tuning procedure for autonomous vehicle lateral control. A low effort and high level method of automated Model Predictive Control tuning based on Bayesian Optimization is proposed. Except from reducing the workload and making the process less tedious, the method yields optimal gains in a sense defined by a user. The solution is implemented and verified in simulation on a driving scenario. The vehicle is able to perform lane keeping maneuvers under varying vehicle velocity.
Document type :
Conference papers
Complete list of metadata

Contributor : Frédéric Davesne Connect in order to contact the contributor
Submitted on : Friday, April 1, 2022 - 8:10:59 PM
Last modification on : Saturday, April 2, 2022 - 3:39:37 AM



Wojciech Strozecki, Naima Ait Oufroukh, Yacine Kebbati, Dalil Ichalal, Said Mammar. Automatic Tuning of MPC for Autonomous Vehicle using Bayesian Optimization. 18th IEEE International Conference on Networking, Sensing and Control (ICNSC 2021), Dec 2021, Xiamen, China. pp.1-6, ⟨10.1109/ICNSC52481.2021.9702240⟩. ⟨hal-03628275⟩



Record views