Fuzzy Goal Programming Algorithm for Multi-Objective Trajectory Optimal Parking of Autonomous Vehicles

With the development of autonomous vehicle technology, planning an efficient trajectory for automatic parking while considering multiple factors such as path length, task time, and passenger comfort is increasingly necessary. This article proposes a solution to the automatic parking problem using an improved fuzzy goal programming algorithm, a multi-objective technique capable of finding a compromised solution among all objectives using a function transformation. Furthermore, it efficiently solves the optimized automatic maneuver parking problem while considering fuzzy factors. In this way, the proposed solution can compensate for the difficulty of precisely determining excepted values for each optimization objective. The designed multi-objective strategy is validated and analyzed through a series of simulation and experimental studies. The simulation results indicate that the improved fuzzy goal programming approach has a better performance than the general goal programming method, the weighted sum method and single-objective optimization method in searching for a compromised solution of the multi-objective trajectory optimization automatic parking problem. Moreover, experimental results verify the effectiveness of the proposed method in solving multi-objective optimal automatic parking problem.