Important intersections identification method considering node information and network controllability
Peiju Shi · 2025
To ensure the normal operation of urban road traffic systems, excavate important intersections and analyze the network resilience. The paper proposes the GINI-TOPSIS method for identifying critical nodes, by utilizing the Gini coefficient and enhancing the TOPSIS algorithm. From both structural and functional perspectives, we select node degree, betweenness centrality, closeness centrality, and the delay status indicator as evaluation criteria for critical intersection recognition. Applying the Popov-Belevitch-Hautus (PBH) criterion to identify control intersections in urban road networks. Developing various attack strategies based on node importance and analyzing network robustness to further identify critical nodes in the road network. To verify the applicability of the proposed method, this paper is based on the real road network and applies the node identification method. The experimental results show that the GINI-TOPSIS algorithm has high applicability on the real road network, and its attack strategy reduces the network robustness to 69%. The critical nodes and driver nodes identified by GINI-TOPSIS and PBH are connected in location distribution, which further identifies important intersections in the road network.