受限泊车通道下自动驾驶平行泊车的路径规划方法OA北大核心CSTPCD

To solve to the problems of long planning times and low success rates in automatic parking in constrained parking lanes,a modified approach to path planning was proposed,which could improve the hybrid A∗ algorithm.Firstly,the parking path was divided into two parts:a forward pose adjustment segment and a reverse parking segment.A linear-arc constrained optimization model was established to plan the pose adjustment segment,while finding a suitable starting point for reverse parking.Subsequently,collision risk cost was introduced as an additional factor in the hybrid A∗ algorithm.The node expansion process was improved by checking whether the vehicle contour intersects with obstacle lines,enhancing the real-time performance and safety of the reverse parking segment.Finally,a cost function was designed with criteria such as path length,smoothness,and deviation,taking into account the vehicle's kinematic constraints.A quadratic programming approach was used to smooth the initial path,resulting in the final path.Simulation analysis was conducted using MATLAB to compare the modified algorithm with the original algorithm.The results showed that,in constrained parking lanes,the improved algorithm could produce a smooth,collision-free parking path with a reduced search time of 23.8%compared with the hybrid A∗ algorithm.Additionally,the obtained path was safer and more suitable for tracking control.