## 3 Case Application and Analysis  
The regional road network in the second Ring Road of Beijing was taken as an example, shown in Figure 2. Road network and nodes outside the second Ring Road were not considered. This model was used to evaluate the importance of 113 nodes in the road network. The classification and sorting of all the nodes were obtained based on the importance of nodes for the hierarchical control of the key nodes in the road network. Figure 1: Flow diagram of TOPSIS-DT method. Figure 3 is the topology diagram of the road network in the study area. The node is the intersection and the edge is the road segment. The roads in the area include expressways, trunk roads, secondary trunk roads, and branch roads. According to the abstract diagram of the road network shown in Figure 3, the topological adjacency matrix of the road network was established based on graph theory. The weighted connection degree of the node could be calculated with the method of road grade  
Figure 3: The road network topology map of Beijing Second Ring. Figure 2: Location of the study area in Beijing (enclosed area of dashed line). weighting. The scatter diagram after standardization was shown in Figure 4. To identify the spatial characteristics of the weighting connection degree of road network nodes more intuitively, the weighted connection degree of road network nodes was divided into three grades according to the natural breakpoint classification, and its spatial distribution was shown in Figure 5. The results show that the spatial distribution of the weighted connection degree values of nodes presents certain differentiation. The nodes with high connection degree (the standard value of weighted connection degree is greater than 0.63) are basically evenly distributed on the expressways, accounting for 22% of all the nodes in the whole road network, indicating that the connection grade of the peripheral expressways is relatively high. The nodes with moderate connection degree (the standard value of weighted connection degree is greater than OR equal to 0.45, but less than 0.63) are distributed on the trunk roads on the east and west sides of the whole road network. Most of them are intersections between the trunk roads, and it accounts for about 27% of all the nodes. The nodes with low connection degree are (the standard value of weighted connection degree is less than 0.63) are mostly distributed on the secondary trunk roads, accounting for about 51% of all the nodes in the whole road network. It can be seen that the distribution of nodes with weighted connection degree in the whole road network generally shows the structure of \"peripheral high connectivity degree-central low connectivity degree\". If the key nodes are identified according to the high weighted connection degree of the nodes, most of the key nodes are on the expressways in the road network. Figure 4: Normalized values of node degrees. With regard to the calculation for the betweenness of nodes, it is assumed that the shortest path between two nodes in the road network is all in the expressway ring. The betweenness of 113 nodes in the road network were obtained, and the scatter plot was obtained by standardization, shown in Figure 6. All the nodes were divided into three grades according to the natural breakpoint classification, and its spatial distribution was shown in Figure 7. The results show that the betweenness of nodes shows a \"triangular\" distribution, and most of the nodes with high betweenness values are distributed between the 50 th and the 70 th nodes, showing a certain degree of agglomeration. The nodes with a high betweenness value (the standard value of the betweenness is greater than OR equals 0.49) were distributed on the trunk roads in the central area of the road network. The spatial distribution pattern was an \"L-type\" pattern, and they accounted for 10% of all the nodes.