A network centrality measure framework for analyzing urban traffic flow: A case study of Wuhan, China
| Autor: | Pengxiang Zhao, Shuangming Zhao, Yunfan Cui |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Statistics and Probability
050210 logistics & transportation Relation (database) Computer science 05 social sciences 0211 other engineering and technologies Mode (statistics) 021107 urban & regional planning 02 engineering and technology Complex network Condensed Matter Physics computer.software_genre Traffic flow Measure (mathematics) law.invention PageRank Betweenness centrality law 0502 economics and business Data mining Centrality computer |
| Zdroj: | Physica A: Statistical Mechanics and its Applications. 478:143-157 |
| ISSN: | 0378-4371 |
| Popis: | In this paper, we propose an improved network centrality measure framework that takes into account both the topological characteristics and the geometric properties of a road network in order to analyze urban traffic flow in relation to different modes: intersection, road, and community, which correspond to point mode, line mode, and area mode respectively. Degree, betweenness, and PageRank centralities are selected as the analysis measures, and GPS-enabled taxi trajectory data is used to evaluate urban traffic flow. The results show that the mean value of the correlation coefficients between the modified degree, the betweenness, and the PageRank centralities and the traffic flow in all periods are higher than the mean value of the correlation coefficients between the conventional degree, the betweenness, the PageRank centralities and the traffic flow at different modes; this indicates that the modified measurements, for analyzing traffic flow, are superior to conventional centrality measurements. This study helps to shed light into the understanding of urban traffic flow in relation to different modes from the perspective of complex networks. |
| Databáze: | OpenAIRE |
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