Abstract
Accurately identifying the key nodes of the road network and focusing on its management and control is an important means to improve the robustness and invulnerability of the road network. In this paper, a classification and identification method of key nodes in urban road networks based on multi-attribute evaluation and modification was proposed. Firstly, the emergency function guarantee grade of road network nodes was divided by comprehensively considering the importance of road network nodes, the consequences of failure, and the degree of difficulty of recovery. The evaluation indexes were selected according to the local attributes, global attributes, and functional attributes of the road network topology. The spatial distribution patterns of the evaluation indexes of the nodes were analyzed. The dynamic classification method was used to cluster the attributes of the road network nodes, and the TOPSIS method was used to comprehensively evaluate the importance ranking of the road network nodes. Attribute clustering of road network nodes by dynamic classification method (DT) and the TOPSIS method was used to comprehensively evaluate the ranking of the importance of road network nodes. Then, combined with the modification of the comprehensive evaluation and ranking of the importance of the road network nodes, the emergency function support classification results of the road network nodes were obtained. Finally, the method was applied to the road network within the second Ring Road of Beijing. It was compared with the clustering method of self-organizing competitive neural networks. The results show that this method can identify the key nodes of the road network more accurately. The first-grade key nodes are all located at the more important intersections on expressways and trunk roads. The spatial distribution pattern shows a “center-edge” pattern, and the important traffic corridors of the road network show a “five vertical and five horizontal” pattern.
Highlights
An urban road network is a complex network composed of a large number of nodes and road segments
The components of the road network are closely related, and the overall distribution range is wide. It is affected by unexpected events such as natural events, man-made events, traffic accidents, etc., which lead to the degradation of some key node functions, the decline of local road capacity or congestion, and even the paralysis of the road network due to the effect of cascade failure [1,2]
Because it is difficult for a single index to accurately reflect the importance of road network nodes as a whole [16,17], a multi-index comprehensive identification method has gradually emerged to reflect the importance of road network nodes from different angles [14,15,16,17,18], but too many indicators will increase the complexity of calculation
Summary
An urban road network is a complex network composed of a large number of nodes (intersections) and road segments. Some scholars have proposed to use node peak-hour traffic flow (the traffic volume in the hour of the day when the traffic volume is at its peak) [14], traffic load degree (the ratio of the actual traffic density of the road to the density under the maximum capacity) [15], flow ratio (the ratio of traffic flow to planning and design traffic flow at a certain time), and saturation (ratio of maximum traffic volume to maximum capacity) [1,2] to characterize the traffic operation characteristics of the road network Because it is difficult for a single index to accurately reflect the importance of road network nodes as a whole [16,17], a multi-index comprehensive identification method has gradually emerged to reflect the importance of road network nodes from different angles [14,15,16,17,18], but too many indicators will increase the complexity of calculation.
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