Vulnerability Assessments of Urban Rail Transit Networks Based on Redundant Recovery
Jianhua Zhang,
Ziqi Wang,
Shuliang Wang,
Shengyang Luan and
Wenchao Shao
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Jianhua Zhang: School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou 221116, China
Ziqi Wang: School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou 221116, China
Shuliang Wang: School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou 221116, China
Shengyang Luan: School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou 221116, China
Wenchao Shao: School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou 221116, China
Sustainability, 2020, vol. 12, issue 14, 1-14
Abstract:
Urban rail transit has received much attention in the last two decades, and a significant number of cities have established urban rail transit networks (URTNs). Although URTNs have brought enormous convenience to the daily life of citizens, system failures still frequently occur, therefore the vulnerability of URTNs must be a concern. In this paper, we propose a novel measurement called the node strength parameter to assess the importance of nodes and present a redundant recovery scheme to imitate the system recovery of URTNs subjected to failures. Employing three malicious attacks and taking the Nanjing subway network as the case study, we investigated the network vulnerability under scenarios of different simulated attacks. The results illustrate that passenger in-flow shows the negligible impact on the vulnerability of the node, while out-flow plays a considerable role in the largest strength node-based attack. Further, we find that vulnerability will decrease as passenger out-flow increases, and the vulnerability characteristics are the same with the increase in the construction cost of URTNs. Considering different attack scenarios, the results indicate that the highest betweenness node-based attack will cause the most damage to the system, and increasing the construction cost can improve the robustness of URTNs.
Keywords: vulnerability assessments; node strength; redundant recovery; urban rail transit networks (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)
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