Caculation of traffic congestion index based on betweenness centrality

doi:10.13474/j.cnki.11-2246.2021.0148

Abstract

Abstract: Traditional betweenness centrality of road network mainly evaluates the theoretical road accessibility based on the proportion of the shortest paths in each section. Based on the traditional network betweenness centrality, this study proposes dynamic betweenness, as a new urban traffic congestion index, to evaluate the actual congestion of each section in the city from the perspective of the proportion of traffic volume. This paper calculates the betweenness of urban road network to reflect the accessibility of urban road sections, and calculates the dynamic betweenness and traffic trajectory with taxi GPS fixed-point data. The comparison of the two betweennesses can objectively and comprehensively reflect the traffic congestion, improves the reference value of the traffic congestion index, and provides a basis for decision-making for urban construction planning and road reconstruction, which contributes to alleviating the situation of urban road traffic congestion.

Key words: betweenness centrality, dynamic betweenness, traffic congestion index, machine learning, map matching

CLC Number:

P208

YE Yexing, YANG Fei. Caculation of traffic congestion index based on betweenness centrality[J]. Bulletin of Surveying and Mapping, 2021, 0(5): 86-90.

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