Evaluation Method for Node Importance of Urban Rail Network Considering Traffic Characteristics

Ting Chen, Jianxiao Ma (), Zhenjun Zhu and Xiucheng Guo
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Ting Chen: School of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
Jianxiao Ma: School of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
Zhenjun Zhu: School of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
Xiucheng Guo: School of Transportation, Southeast University, Nanjing 210096, China

Sustainability, 2023, vol. 15, issue 4, 1-20

Abstract: As a sustainable means of public transport, the safety of the urban rail transit is a significant section of public safety and is highly important in urban sustainable development. Research on the importance of urban rail stations plays an important role in improving the reliability of urban rail networks. This paper proposed an improved method for evaluating the importance of urban rail stations in a topology network, which was used to identify the key stations that affect the urban rail network performance. This method was based on complex network theory, considering the traffic characteristics of the urban rail network that runs on specific lines and integrating the structural characteristics and interrelationship of the lines where the stations are located. Hereafter, this method will be abbreviated as CLI. In order to verify that the high importance stations evaluated by this method were the key stations that had a great impact on the urban rail network performance, this paper designed a comparative attack experiment of betweenness centrality and CLI. The experiment was carried out by taking the Suzhou Rail Transit (SZRT) network as an example and the largest connected subgraph as well as the network efficiency as indicators to measure the network performance. The results showed that CLI had a greater impact on network performance and could better evaluate the key stations in the urban rail network than node degree and betweenness centrality.

Keywords: urban rail network; complex network; topological structure; node importance; network performance (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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