关键词: 城市交通, 重要度, K-means, 地铁路网, 异质性

Abstract:

This paper modeled a subway system as a directed and weighted network with consideration of the temporal and spatial distribution of passengers in the subway system. Based on the K-means clustering, stations (nodes) and intervals (edges) in a subway network were grouped by three metrics: two basic topologi- cal properties (degree and betweenness), and their roles in transporting people (passenger volume). Degree re- flects the nodes’local accumulation ability; betweenness reflects a node or edge’s the impact on the global network topology, and passenger volume reflects a node or edge’s importance in transport people at different times. Taking the Beijing Subway network as a case study, the paper tested the effectiveness of the proposed approach. The results suggested that the method could identify key nodes and edges and provide dynamic de- cision support for subway network operators.

Key words: urban traffic , key edges and nodes, K-means, subway network, heterogeneity