Optimal control problem of multi‐vehicle cooperative autonomous parking trajectory planning in a connected vehicle environment. Issue 11 (31st July 2019)

• Record Type: Journal Article
• Authors: Wu, Bing; Qian, Lijun; Lu, Meiling; Qiu, Duoyang; Liang, Haiqin
• Is Part Of: IET intelligent transport systems. Volume 13:Issue 11(2019)
• Page Start: 1677
• Page End: 1685
• Publication Date: 2019-07-31
• Subjects: optimisation -- nonlinear programming -- path planning -- iterative methods -- optimal control -- mathematics computing -- mobile robots -- collision avoidance -- trajectory control -- linear programming; optimal control problem -- connected vehicle environment -- intelligent vehicle technology -- autonomous parking condition -- vehicle kinematics model -- collision avoidance constraints -- autonomous parking trajectory planning problem -- shortest parking completion time -- optimal cost function -- nonlinear programming problem; Intelligent transportation systems -- Periodicals; Electronics in transportation -- Periodicals; 388.31205
• DOI: 10.1049/iet-its.2019.0119
• Languages: English
• ISSNs: 1751-956X

Abstract

Abstract : The development of intelligent network and intelligent vehicle technology makes it possible for multi‐vehicle cooperative driving. In this study, the multi‐vehicle cooperative autonomous parking condition is addressed by establishing a vehicle kinematics model combined with dynamic constraints and endpoint and collision avoidance constraints. The autonomous parking trajectory planning problem is transformed into an optimal control problem. The shortest parking completion time is set as the optimal cost function, and the optimal control problem is discretised by using the Gauss pseudo‐spectral method. Then, the non‐linear programming problem is solved. Moreover, an initial guess generation strategy is proposed, and the iteration method is used to solve the problem by adding collision avoidance constraints to the collision situation of the vehicle to improve the convergence and robustness of the problem. The simulation model is built in MATLAB/Simulink to simulate multi‐vehicle cooperative autonomous parking under different working conditions. The simulation results show that the proposed method can solve the multi‐vehicle cooperative autonomous parking trajectory planning problem uniformly and effectively. Compared with the traditional pseudo‐spectral method, the proposed method has a faster convergence speed.