SEVA3D: Using Arti cial Neural Networks to Autonomous Vehicle Parking Control
Milton Roberto Heinen, Fernando Santos Osório, F.J. Heinen, Christian Roberto Kelber · The 2006 IEEE International Joint Conference on Neural Network Proceedings · 2006
This paper describes the simulation system proposed in order to study and to implement intelligent autonomous vehicle control. The developed system can automatically drive a vehicle, implementing a robust control system capable of simulating in a realistic way autonomous parking in a parallel parking space. The system controls the vehicles based on the reading of sonar sensors and uses a neural network to automatically generate acceleration and steering commands, parking it in a parallel parking space. The controller was implemented using a Jordan-Net based neural network, and the results obtained in our simulations demonstrated that the proposed controller is perfectly able to correctly park the vehicle in different situations.