## 3 Case Application and Analysis
The multi-attribute comprehensive evaluation method integrates the comprehensive evaluation value of road network nodes according to the characteristics of the road network node index. Then the comprehensive evaluation and ranking of road network nodes are used to modify the classification results of road network nodes. This method comprehensively considers the inherent relevance of each index data, as well as the ranking of the integrated results of the evaluation indicators, which shows that the method takes into account the macro and micro characteristics of road network nodes. The first-grade nodes identified by self-organizing competitive neural network method [15] were as follows: 2, 3, 5, 8, 9, 55, 75, 76, 84, 96, 102, 107, and 110. The nodes 2, 8, 75, and 110 did not belong to the first-grade node sequence determined by the method proposed in this paper. The comprehensive evaluation values of the four nodes are 0.4276, 0.4131, 0.4421, and 0.4365, respectively, which were all less than the comprehensive evaluation value of  
Figure 3:4 Final classification results. Node 5 (see Figure 15), and the dynamic clustering results of the four nodes all belonged to the secondary-grade nodes (see Figures 10 and 11). It can be seen that the recognition result by the method in this paper is more accurate and reasonable. Figure 3:5 Distribution map of key nodes of the urban road network. According to the spatial distribution pattern of first-grade and secondary-grade nodes, the \"five vertical and five horizontal\" pattern of the important traffic corridor of the regional road network was formed, that is, five vertical corridors (green marking): (1) 9\({}^{\#}\)\(\rightarrow\)62\({}^{\#}\)\(\rightarrow\)75\({}^{\#}\)\(\rightarrow\)102\({}^{\#}\); (2) 2\({}^{\#}\)\(\rightarrow\)105\({}^{\#}\); (3) 5\({}^{\#}\)\(\rightarrow\)81\({}^{\#}\)\(\rightarrow\)80\({}^{\#}\)\(\rightarrow\)107\({}^{\#}\); (4) 6\({}^{\#}\)\(\rightarrow\)82\({}^{\#}\)\(\rightarrow\)109\({}^{\#}\); (5) 8\({}^{\#}\)\(\rightarrow\)74\({}^{\#}\)\(\rightarrow\)112\({}^{\#}\). Five horizontal corridors (pink marking): (1) 9\({}^{\#}\)\(\rightarrow\)1\({}^{\#}\)\(\rightarrow\)8\({}^{\#}\); (2) 18\({}^{\#}\)\(\rightarrow\)28\({}^{\#}\); (3) 53\({}^{\#}\)\(\rightarrow\)61\({}^{\#}\); (4) 76\({}^{\#}\)\(\rightarrow\)84\({}^{\#}\); (5) 102\({}^{\#}\)\(\rightarrow\)112\({}^{\#}\). From the perspective of road network system engineering, preventive measures such as monitoring and early warning, project resilience improvement, and emergency function guarantee should be implemented the event prevention resilience of the first-grade key nodes of the road network before an emergency occurs. The improvement of the engineering toughness of road network nodes can enhance the anti-event robustness of road network nodes and reduce their failure probability, to enhance the security of urban road network systems. To adapt and absorb the damage situation of the road network caused by emergencies and reduce the impact of failure nodes on the overall performance of the road network, the failure degree and the number of failure nodes should be reduced as much as possible. After the occurrence of an emergency, the rapid and efficient intervention of the monitoring and early warning of the transportation department, emergency traffic organization, and emergency safeguard measures can reduce the recovery time of the failure nodes of the road network. Emergency traffic organizations can guide on-site vehicles to flow into the secondary or tertiary road network nodes and their connected roads, to avoid the cascade failure effect of the road network nodes caused by the failure of important nodes, which paralyzes the local overall performance of the road network. From the microscopic point of view of nodes, for the bridge nodes in the first-grade nodes, the vulnerability of various types of bridges under all kinds of emergencies is analyzed, the damage forms of different bridges are summarized and sorted out, and the corresponding emergency disposal plan and process is formulated.