Modeling the Vulnerability and Resilience of Interdependent Transportation Networks under Multiple Disruptions
Publication: Journal of Infrastructure Systems
Volume 29, Issue 1
Abstract
Because infrastructure systems are highly interconnected, it is crucial to analyze their vulnerability and resilience with the consideration of interdependencies. This paper constructed a bus–metro interdependent network model based on the passenger transfer relationship and used deep learning to identify the network topology attributes. The vulnerability process of the interdependent network to different disruptions under structural and functional perspective was studied. On this basis, this paper adopted a resilience assessment framework and mainly focused on modeling and resilience analysis of interdependent networks’ recovery processes. The optimal and instructive recovery strategy was determined, and it is shown that the increase of the coupling distance cannot alleviate the vulnerability of the interdependent network effectively; after the tolerance coefficient reaches the threshold, the effect on the vulnerability of the dependent network is weakened; and a betweenness-based strategy (BBS) works best in the preferential recovery of key nodes.
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Data Availability Statement
The data that support the findings of this study are openly available at https://www.8684.cn/. Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request including data of bus and subway stations in Wuhan.
Acknowledgments
This work is jointly supported by the National Natural Science Foundations of China (61503166, 61801197), the Jiangsu Natural Science Foundation (BK20181004), the National Science Foundation of the Jiangsu Higher Education Institutions of China (18KJB510012), the Qinglan Project of Jiangsu Higher Education institutions of China (2020), and the Xuzhou Science and Technology Project of China (KC19006).
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Journal of Infrastructure Systems
Volume 29 • Issue 1 • March 2023
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© 2022 American Society of Civil Engineers.
History
Received: Apr 20, 2022
Accepted: Sep 16, 2022
Published online: Nov 15, 2022
Published in print: Mar 1, 2023
Discussion open until: Apr 15, 2023
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