Vulnerability Assessment of Metro Systems Based on Dynamic Network Structure

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Title: Vulnerability Assessment of Metro Systems Based on Dynamic Network Structure
Author(s): Pu, J
Liu, C
Zhao, J
Han, K
Zhou, Y
Item Type: Conference Paper
Abstract: Invulnerable metro systems are essential for the safety and efficiency of urban transportation services. Therefore, it is of significant interest to systematically assess the vulnerability of metro systems. To this end, in this paper, we assess the vulnerability of metro systems with a data-driven framework in which dynamic travel patterns are considered. Specifically, we use effective attack strategies based on the topology structure of metro networks. The network structure depends on not only connectivity among metro stations but also dynamic passenger flow patterns. Thus, two data-driven metrics, satisfaction rate (SR) and satisfaction rate with path cost (SRPC), are proposed to quantify the vulnerability of metro networks after our attack strategies. Finally, we conduct experiments on Shanghai metro system. The results indicate that the metro system is vulnerable to malicious attacks while it shows strong robustness to random failures. Our results also highlight weak-points and bottlenecks in the system, which may bear practical managerial implications for policymakers to improve the reliability and robustness of the metro systems and the public transportation services.
Editor(s): Phung, D
Tseng, VS
Webb, GI
Ho, B
Ganji, M
Rashidi, L
Publication Date: 19-Jun-2018
Date of Acceptance: 3-Jun-2018
URI: http://hdl.handle.net/10044/1/64253
DOI: https://dx.doi.org/10.1007/978-3-319-93034-3_42
ISBN: 978-3-319-93033-6
ISSN: 0302-9743
Publisher: SPRINGER INTERNATIONAL PUBLISHING AG
Start Page: 525
End Page: 537
Journal / Book Title: ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PAKDD 2018, PT I
Volume: 10937
Conference Name: 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)
Copyright Statement: © 2018 Springer International Publishing AG, part of Springer Nature. The final publication is available at https://dx.doi.org/10.1007/978-3-319-93034-3_42
Keywords: Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Information Systems
Computer Science, Theory & Methods
Computer Science
Metro systems
Network vulnerability
Node centrality
Travel patterns
Dynamic networks
ROBUSTNESS ASSESSMENT
SAFETY MANAGEMENT
COMPLEX NETWORKS
SUBWAY
CONSTRUCTION
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Information Systems
Computer Science, Theory & Methods
Computer Science
Metro systems
Network vulnerability
Node centrality
Travel patterns
Dynamic networks
ROBUSTNESS ASSESSMENT
SAFETY MANAGEMENT
COMPLEX NETWORKS
SUBWAY
CONSTRUCTION
08 Information And Computing Sciences
Artificial Intelligence & Image Processing
Publication Status: Published
Start Date: 2018-06-03
Finish Date: 2018-06-06
Conference Place: Deakin Univ, Melbourne, AUSTRALIA
Embargo Date: 2019-06-19
Online Publication Date: 2018-06-19
Appears in Collections:Faculty of Engineering
Civil and Environmental Engineering



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