Global path planning for autonomous driving considering dynamic traffic impedance based on A* algorithm

Traffic impedance reflects the travel time spent by the passenger on the road and can provide more information about the road network for path planning. In this paper, due to the dynamic characteristics of the road network, a dynamic traffic impedance function that considers the economic and time costs, and passengers' preference is established based on the concept of generalized cost, which is combined with the heuristic weighted A* algorithm. It can be updated in real-time with the road conditions and uses the directed graph obtained from map abstraction for global path planning. Experimental results show that the improved algorithm can find the best path quickly and accurately.