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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.
Wu et al. (Fri,) studied this question.