Multi-Feature Fusion Identification of Important Nodes in Traffic Network

摘要

Different modeling and analysis methods describe different characteristics of the traffic network and lead to different conclusions for the identification of important road sections and intersections. In this paper, the road network and bus network of Langfang city are integrated to model the composite traffic network, and the actual traffic flow data are added to analyze. A bioinformatics approach called SPRING is introduced to determine the importance of certain nodes. This method gives the ranking result of node importance with a combination of various characteristics, which include the similarity of network characteristics and traffic conditions between certain nodes and others. Through comparing the node importance of multi-feature fusion and the node importance of single traditional network characteristic, it is concluded that multi-feature fusion method has the feasibility, advantages, and disadvantages in identification of important nodes and shows effectiveness when considering the real traffic situation and the demand of traffic analysis.