Unified Modeling of Path Planning and Tracking Control Based on Improved Genetic Algorithm

Abstract

Vehicle path planning and tracking control are the key to achieving autonomous driving. In this paper, a combined algorithm based on artificial potential field algorithm and genetic algorithm is proposed. Based on information about the vehicle's driving environment, establishing potential field functions in different environments. And the initialized populations in the genetic algorithm are optimized using the established artificial potential fields. Planning a reliable driving path. Using model predictive control algorithms. Tracking control of the planned path. Unified modeling was achieved. Experimental results show that the improved path planning algorithm and tracking control method are able to plan and track the path well.