Improved Tabu Search Algorithm in Driverless Cars Research on Path Planning
Aiming at the complex driverless traffic environment,it proposes a path planning method for driverless vehicles based on the driverless vehicle system architecture,this method combines an improved tabu search algorithm with an improved artificial po-tential field.The improved tabu search algorithm is used for global path planning,and the improved artificial potential field meth-od is used for local path planning.The advantages of the method are verified by analyzing the path planning method through simu-lation.The results show that the proposed global path planning method achieves the optimal time efficiency and path selection.Af-ter adding local path planning,the search range of the method becomes smaller,and the path planning will be safer and more adaptive.This study provides a reference for the development of unmanned driving technology.
Driverless VehicleGlobal Path PlanningLocal Path PlanningTabu Search AlgorithmArtificial Po-tential Field
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