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The problem of path planning of the autonomous valet parking can be explained as the planning of a path from the entrance of the parking lot to the parking space. Firstly, by collecting the location information of key nodes in the parking Iot, the topological map of the parking lot is defined, which is composed of parking space information and road topological network. Secondly, the reasonable parking space searching path and parking path are planned, and their curvature discontinuity is smoothed. The parking path adopts the C-shaped method, the path of searching for parking spaces adopts the line-arc-line splicing method, and use the clothoid curve to smooth the path. Finally, Stanley path tracking algorithm is used to follow the planned path based on MATLAB to verify the effectiveness of the path planning algorithm. The simulation results show that the proposed algorithm can realize the seamless splicing between the searching path and the parking path, and the planned path can be tracked better.

In this article, we propose a new approach to solve local motion planning problem in autonomous vehicle field. Instead of generating several primitives and choosing the optimal trajectory from that, we get the future T time step horizon's vehicle state, and fit that into clothoid local trajectory by solving a dynamic programming problem. The trajectory generated is smooth enough and meet both ego vehicle's dynamics and traffic regulation's constraints. Iterate this process, the ego autonomous vehicle can obtain its future trajectory continuously. This method has a good performance in the simulation using Matlab and Prescan. This method has fast computing speed to apply on autonomous vehicle driving in real road online compared to other methods.