Optimal Path Planning for Multi-stage Automatic Parking and Simulation Analysis

Authors

Qiming Wang, School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;Follow
Gaoqiang Zong, School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;
Jinming Xu, School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;

Abstract

Abstract: To resolve the path planning for narrow parallel parking spaces and the discontinuous curvature of the parking trajectory, this paper proposes a method of optimal multi-stage parking path planning considering collision avoidance constraints. A trajectory equation for the center of the vehicle rear axle is derived for the case when the steering wheel speed is constant. A function of collision avoidance constraints is developed to ensure the safe parking of the vehicle. With the center of the rear axle of the parking path as the control point, the optimal path is solved according to parking indicators such as the minimum parking space and the smallest final parking attitude angle. Simulink/Carsim co-simulation is performed to build a model. The simulation results show that a parking path designed by this method can achieve fast and stable parking in narrow parallel parking spaces under the premise of meeting parking safety needs.

Recommended Citation

Wang, Qiming; Zong, Gaoqiang; and Xu, Jinming (2022) "Optimal Path Planning for Multi-stage Automatic Parking and Simulation Analysis," Journal of System Simulation: Vol. 34: Iss. 2, Article 21.
DOI: 10.16182/j.issn1004731x.joss.20-0715
Available at: https://dc-china-simulation.researchcommons.org/journal/vol34/iss2/21

First Page

385

Revised Date

2021-01-11

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.20-0715

Last Page

395

CLC

U471.15

Recommended Citation

Qiming Wang, Gaoqiang Zong, Jinming Xu. Optimal Path Planning for Multi-stage Automatic Parking and Simulation Analysis[J]. Journal of System Simulation, 2022, 34(2): 385-395.

DOI

10.16182/j.issn1004731x.joss.20-0715