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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.
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https://hal.archives-ouvertes.fr/hal-03628275
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

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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⟩

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