Study on Path Planning of Multi-storey Parking Lot Based on Combined Loss Function

Path planning research can effectively solve the problem of finding free parking space in multi-storey parking lots. This paper takes advantage of the decision ability of reinforcement learning and the perception ability of deep learning to improve the algorithm based on traditional DQN. On the one hand, Q value is updated with qualification trace; On the other hand, different loss functions are set for the main network and the target network, and the two are combined to improve the accuracy of path planning. The experimental results show that the improved DQN model can accomplish the path planning task of multi-storey parking lot more accurately and efficiently.