Research on the Mechanism Influencing the Coupling Coordination Between Road Significance and Traffic State

Urban road significance and traffic state have a complex interaction relationship, which affects people’s travelling efficiency and satisfaction. In this paper, two types of traffic state indicators are extracted from the GPS trajectory data of taxis, namely the number of GPS points and the ratio of average speed during the morning traffic peak to the free-flow speed at night. Based on the theory of complex networks, the node degree, betweenness centrality, closeness centrality and eigenvector centrality in the topological structure are obtained to characterize the road significance at different levels, and the coupling relationship between traffic state and the four significance indexes is explored by using the coupling coordination degree model. With the coupling relationship as the dependent variable, thirteen independent variables are selected to regress the mechanism of the coupling degree using CatBoost algorithm combined with SHAP. The results show that the number of intersections, the green area, and the number of bus stops promote the coupling coordination between traffic state and road significance, and that the road separation type has a significant positive effect on the degree of coupling between traffic state and betweenness centrality, closeness centrality as well as node degree. In addition, for the positively uncoordinated roads, the intensities of public management land and residential land have a negative effect on the coupling coordination between traffic state and closeness centrality, and the intensity of residential land has a negative effect on the coupling coordination between traffic state and eigenvector centrality; while for the negatively uncoordinated roads, the intensity of residential land has a negative effect on the coupling coordination between traffic state and closeness centrality.