An autonomous parking algorithm based on A-star algorithm correction and MPC path tracking

Yijie Liu; Ping Wang

doi:10.1117/12.2631818

14 April 2022 An autonomous parking algorithm based on A-star algorithm correction and MPC path tracking

Yijie Liu, Ping Wang

Proceedings Volume 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021); 1217824 (2022) https://doi.org/10.1117/12.2631818
Event: International Conference on Signal Processing and Communication Technology (SPCT 2021), 2021, Tianjin, China

Abstract

Generally, autonomous parking is divided into two parts: path planning and path tracking. Path planning algorithms such as A*, ant colony algorithm, etc., all have the problem of insufficient trajectory points. Meantime, path tracking algorithms: the proportional integral derivative (PID) and model predictive control (MPC) are used wisely. PID cannot eliminate errors, control lag, and easily cause overshoot. Therefore, this paper uses A* correction and MPC to solve these problems. First, the A* algorithm is used to obtain the planned trajectory of the vehicle, considering the slot boundary and the road boundary. Second, the algorithm selects the appropriate Bezier curve to reduce the jitter at the path joints. Finally, the path tracking is realized based on MPC. Then, using MATLAB and PreScan (a vehicle simulation software) to simulate and implement the autonomous parking algorithm. The results show that the algorithm has certain reliability and stability for vertical parking spaces.

Citation Download Citation

Yijie Liu and Ping Wang "An autonomous parking algorithm based on A-star algorithm correction and MPC path tracking", Proc. SPIE 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021), 1217824 (14 April 2022); https://doi.org/10.1117/12.2631818

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