Path planning algorithm regarding rapid parking based on static optimization

To solve problems of automatic parking during the autonomous driving, a rapid optimization algorithm regarding parking has been proposed in this paper. The biggest challenge comes from the non-holonomic characteristics of automobiles and short-distance obstacles. The algorithm in question solves the obstacles avoidance by using Minkowski sum. Geometric path planning is derived from kinematics and connected with path parameters of Runge-Kutta discretization method. Since parking paths and relevant parameters can be obtained by virtue of Runge-Kutta discretization method, the optimization method for every discrete path is to calculate parking paths that are independent from parking lots. The static optimization method can be resolved by digitization in an effective way. Effects of the above mentioned algorithm will be evaluated by different stimulation scenarios. The stimulation experiments show that path planning algorithm regarding rapid parking based on static optimization is feasible for the following three parking scenarios-parallel parking, vertical parking and angle parking. All these three parking forms can be achieved on the premise of no modification in algorithm. Path planning can be completed within several milliseconds even in a narrow space.