Abstract: Aiming at the problem that the convergence rate is slow when solving the optimal control problem of autonomous parking path planning, a method of autonomous parking path planning based on hp-adaptive Gauss pseudospectral method is proposed. First, the vehicle kinematical model is established, then the collision avoidance constraints and the boundary constraints in autonomous parking processes are further considered, finally the problem of autonomous parking path planning is converted into the optimal control problem which takes the shortest parking time as the cost function. The optimal control problem is discretized by Gauss pseudospectral method, and solved by sequential quadratic programming, in which the number of mesh intervals and degree of the polynomial are adjusted dynamically improving the convergence rate. According to the actual scenario, four autonomous parking conditions are designed and path planning is simulated, and three pseudospectral methods are compared and analyzed. The simulation results show that the convergence rate of the optimal control problem of autonomous parking path planning is improved by the hp-adaptive Gauss pseudospectral method, and the proposed mothed can obtain the parking path in a narrow parking lot, the effectiveness of the proposed method for autonomous parking path planning is verified by real vehicle tests.

Key words: autonomous parking, path planning, hp-adaptive pseudospectral method, optimal control