Training a path planning agent for the automatic parking of a motor vehicle, planning a path for the automatic parking of a motor vehicle, and automatic parking of a motor vehicle.

Abstract

In a computer-implemented training procedure for training a path planning agent (16) to automatically park a motor vehicle (1) by reinforcement learning based on a variety of training scenarios (18, 19, 20), wherein each training scenario (18, 19, 20) is characterized by a vehicle start position, a vehicle start orientation, a vehicle destination position and a vehicle destination orientation, for each training scenario (18, 19, 20) the path planning agent (16) generates a simulated path from the respective vehicle start position with the respective vehicle start orientation to a simulated vehicle end position with a simulated vehicle end orientation based on a reinforcement learning strategy.At least one value of a reward function for the simulated path is calculated and the reinforcement learning strategy is updated depending on the at least one value of the reward function, where the reward function depends on an orientation term that corresponds to a deviation of the simulated vehicle end orientation from the respective vehicle destination orientation.

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