Hegedűs, Tamás and Fényes, Dániel and Németh, Balázs and Vu, V T and Gáspár, Péter (2024) A Lateral Control Based on Physics Informed Neural Networks for Autonomous Vehicles. LECTURE NOTES IN MECHANICAL ENGINEERING, 2024. pp. 812-818. ISSN 2195-4356 10.1007/978-3-031-70392-8_115

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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:	Article
Subjects:	Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions:	Systems and Control Lab
SWORD Depositor:	MTMT Injector
Depositing User:	MTMT Injector
Date Deposited:	09 Oct 2024 08:16
Last Modified:	09 Oct 2024 08:16
URI:	https://eprints.sztaki.hu/id/eprint/10794

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