Parking curve optimization for oblique slots in multi-obstacle environment

Qiang Zhang; Yafei Wang; Xulei Liu; Yichen Zhang

doi:10.1117/12.2689754

7 September 2023 Parking curve optimization for oblique slots in multi-obstacle environment

Qiang Zhang, Yafei Wang, Xulei Liu, Yichen Zhang

Proceedings Volume 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023); 127901E (2023) https://doi.org/10.1117/12.2689754
Event: 8th International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 2023, Hangzhou, China

Abstract

For parking path generation, Reeds-Shepp curve is commonly adopted in algorithms such as Hybrid A*. However, path planning for underground parking with pillars and lanes occupancy cases is difficult due to the narrow space constraints. In narrow environment, RS curve might cause frequent turning and generate large radian arc that are not suitable for parking. In addition, the last segment of RS curve is an arc that occupies large area when parking into slots and is easy to collide with obstacles like pillars. Therefore, we proposed AP-RS curve to promote performance of path searching and obstacle avoidance by taking driver’s parking habits into consideration. For oblique parking lots, CCS curve is designed to ensure the last segment of curve parallel to the slot, which have less occupancy and straighten the car up in movement to reduce tire wear. The proposed method is tested under different oblique slot with 30, 60, 90, 120, 150 degrees and its performance is compared with RS curve and KKL-RS curve. The results show that AP-RS curve for oblique slot have fewer search iterations, higher adaptability to different kinds of slots, higher success rate of path planning in multipleobstacles environment.

Citation Download Citation

Qiang Zhang, Yafei Wang, Xulei Liu, and Yichen Zhang "Parking curve optimization for oblique slots in multi-obstacle environment", Proc. SPIE 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 127901E (7 September 2023); https://doi.org/10.1117/12.2689754

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