At present, the path planning methods based on short-term traffic flow prediction mostly use historical and real-time traffic flow data, and the timeliness of the prediction needs to be improved. In response to this problem, a path planning method based on travel plan data (RPTP) was proposed. The method can proactively obtain the future traffic demand of travelers and provide more reasonable routes for vehicles. Based on the idea of “travel plan”, the overall framework of optimal path planning was designed on the basis of travel plan data. An estimation algorithm was constructed to calculate the road network density in multiple future periods using the route data of the travel plan. The multi-period road network density was integrated using the spatial superposition method, based on which the heuristic function of the D*Lite algorithm was improved. Several simulation experiments were carried out using the SUMO simulation platform, and the simulation effects produced by the RPTP method were compared with that of static path planning method (SPP) and rolling path planning method (RPP) in the same condition. Experimental results show that the RPTP method can improve the traffic efficiency of the road network and alleviate the road traffic congestion, which effectively verifies the superiority of the RPTP method.