Dynamic Variable Emergency Path Planning Method Based on Spatio-Temporal Correlation Analysis of Vertices in Graph

In recent years, with the continuous rise of the number of vehicles in cities, the degree of road network congestion has become increasingly serious. For this purpose, this paper will focus on the congestion change law at the intersections of the road network. At the same time, three novel graph correlation analysis models are proposed to reduce the congestion of urban road networks. Compared with the traditional road network model, our proposed method will establish a rank-based graph correlation model and two vertex factor transfer models based on maximum probability path for each intersection in the road network through the congestion coefficient transfer strategy based on intersections. Combining three kinds of graph vertex models, a dynamic variable emergency path planning method with heuristic function is designed. Finally, the proposed model and method are verified by the travel time experiments of vehicles under different distances and distribution of vehicles in the road network. Three graph correlation analysis models were obtained by the congestion coefficient parameter results to reduce the impact of congestion coefficient in the global search and local search, respectively.