An efficient bidirectional search hybrid A* method for parking path planning in adjacent vehicle deviation scenarios to enhance passenger comfort

The coexistence of manual and autonomous driving leads to a nonstandard final parking state (FPS) of adjacent vehicles. In these instances, maintaining a standard FPS for the target vehicle will engender a predicament of challenging door access. To increase the comfort of passenger boarding and alighting (CPBA), this study proposes a bidirectional search hybrid A* (BHA*) method for parking path planning. First, a characterization variable for the CPBA is constructed on the basis of the allowable and required opening angles of vehicle doors under the constraint of adjacent vehicles. An optimization model for FPS is subsequently established with the comprehensive objective of the CPBA for both the target and adjacent vehicles, along with a safe distance. The genetic algorithm is then utilized to obtain the optimal FPS. Furthermore, the Voronoi potential and a bidirectional search strategy are employed to improve the hybrid A* algorithm, aiming to achieve the optimal FPS and enhance the efficiency of parking path planning. Finally, simulation experiments are conducted on the parameters of real vehicles and parking scenarios to verify the effectiveness and adaptability of the proposed method. A comparison with the hybrid A* algorithm further confirms the superiority of the proposed method in terms of search efficiency.