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A Path Planning Method for Parallel Parking in Constrained Parking Channels
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[1]QIN Dongchen,ZHANG Wencan,WANG Tingting,et al.A Path Planning Method for Parallel Parking in Constrained Parking Channels[J].Journal of Zhengzhou University (Engineering Science),2024,45(05):1-7.[doi:10.13705/j.issn.1671-6833.2024.05.006]
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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 45 Number of periods: 2024 05 Page number: 1-7 Column: Public date: 2024-08-08
Title:
A Path Planning Method for Parallel Parking in Constrained Parking Channels
Author(s):
QIN Dongchen;  ZHANG Wencan;  WANG Tingting;  CHEN Jiangyi
School of Mechanical and Power Engineering, Zhengzhou University, Zhengzhou 450001, China
Keywords:
automatic parking;  hybrid A∗algorithm;  path planning;  quadratic programming;  autonomous driving
CLC:
TP242. 6
DOI:
10.13705/j.issn.1671-6833.2024.05.006
Abstract:
To solve to the problems of long planning times and low success rates in automatic parking in constrainedparking lanes, a modified approach to path planning was proposed, which could improve the hybrid A∗algorithm.Firstly, the parking path was divided into two parts: a forward pose adjustment segment and a reverse parkingsegment. A linear-arc constrained optimization model was established to plan the pose adjustment segment, whilefinding a suitable starting point for reverse parking. Subsequently, collision risk cost was introduced as anadditional factor in the hybrid A∗algorithm. The node expansion process was improved by checking whether thevehicle contour intersects with obstacle lines, enhancing the real-time performance and safety of the reverse parkingsegment. Finally, a cost function was designed with criteria such as path length, smoothness, and deviation, takinginto account the vehicle′s kinematic constraints. A quadratic programming approach was used to smooth the initialpath, resulting in the final path. Simulation analysis was conducted using MATLAB to compare the modifiedalgorithm with the original algorithm. The results showed that, in constrained parking lanes, the improved algorithmcould produce a smooth, collision-free parking path with a reduced search time of 23. 8% compared with the hybridA∗algorithm. Additionally, the obtained path was safer and more suitable for tracking control.
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Last Update: 2024-09-02
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