Hegedűs, Tamás and Fényes, Dániel and Németh, Balázs and Van, Tan Vu and Gáspár, Péter (2024) A lateral control based on Physics Informed Neural Networks for autonomous vehicles. In: 16th International Symposium on Advanced Vehicle Control, 2-6 September 2024, Milan, Italy. (In Press)
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Abstract
In the paper, a lateral control strategy is presented using Physics-Informed Neural Network (PINN) for automated vehicles. The main idea is that the physics information is incorporated into the training process, which leads to an improvement in the performance level of the control algorithm. Moreover, in the highly nonlinear range of the lateral dynamics, which is not properly covered by the training dataset, the stability of the vehicle is guaranteed. The results are compared to a conventional neural network trained to control the vehicle.
| Item Type: | Conference or Workshop Item (Paper) |
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| Uncontrolled Keywords: | Automated vehicles · Neural networks · Lateral control |
| Subjects: | T Technology / alkalmazott, műszaki tudományok > TL Motor vehicles. Aeronautics. Astronautics / járműtechnika, repülés, űrhajózás |
| Depositing User: | Dr Dániel Fényes |
| Date Deposited: | 25 Sep 2024 07:32 |
| Last Modified: | 25 Sep 2024 07:32 |
| URI: | https://real.mtak.hu/id/eprint/205750 |
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