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Published in: Transportation 5/2019

02-02-2018

Assessing network vulnerability of heavy rail systems with the impact of partial node failures

Authors: Qian Ye, Hyun Kim

Published in: Transportation | Issue 5/2019

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Abstract

Much of the literature in recent years has examined the vulnerability of transportation networks. To identify appropriate and operational measures of nodal centrality using connectivity in the case of heavy rail systems, this paper presents a set of comprehensive measures in the form of a Degree of Nodal Connection (DNC) index. The DNC index facilitates a reevaluation of nodal criticality among distinct types of transfer stations in heavy rail networks that present a number of multiple lines between stations. Specifically, a new classification of transfer stations—mandatory transfer, non-mandatory transfer, and end transfer—and a new measure for linkages—link degree and total link degree—introduces the characteristics of heavy rail networks when we accurately expose the vulnerability of a node. The concept of partial node failure is also introduced and compare the results of complete node failure scenarios. Four local and global indicators of network vulnerability are derived from the DNC index to assess the vulnerability of major heavy rail networks in the United States. Results indicate that the proposed DNC indexes can inform decision makers or network planners as they explore and compare the resilience of multi-hubs and multi-line networks in a comprehensive but accurate manner regardless of their network sizes.

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Metadata
Title
Assessing network vulnerability of heavy rail systems with the impact of partial node failures
Authors
Qian Ye
Hyun Kim
Publication date
02-02-2018
Publisher
Springer US
Published in
Transportation / Issue 5/2019
Print ISSN: 0049-4488
Electronic ISSN: 1572-9435
DOI
https://doi.org/10.1007/s11116-018-9859-6

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