Network-based method for assessing multi-modal transportation network vulnerability to cascading failures

Transportation systems are vulnerable to disruptive events such as natural disasters, industrial accidents, terrorist attacks, and climate change. Vulnerability assessment is necessary to understand the impacts of these disruptive events, identify underlying deficiencies within the network, and impr...

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Main Authors: Jingran Sun, Kyle Bathgate, Shidong Pan, Zhanmin Zhang
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Sustainability Analytics and Modeling
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Online Access:http://www.sciencedirect.com/science/article/pii/S2667259624000067
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author Jingran Sun
Kyle Bathgate
Shidong Pan
Zhanmin Zhang
author_facet Jingran Sun
Kyle Bathgate
Shidong Pan
Zhanmin Zhang
author_sort Jingran Sun
collection DOAJ
description Transportation systems are vulnerable to disruptive events such as natural disasters, industrial accidents, terrorist attacks, and climate change. Vulnerability assessment is necessary to understand the impacts of these disruptive events, identify underlying deficiencies within the network, and improve transportation system resilience. Multi-modal transportation networks are often interdependent and form a “system of systems”, which creates a susceptibility to cascading indirect impacts within the integrated transportation network. Accurately modeling these interdependencies typically requires a large amount of data, such as traffic flow and travel demand information for transportation systems, which may not be available or accessible. This paper proposes a network topology-based framework to conduct an interdependent transportation network vulnerability analysis by introducing an algorithm to simulate cascading failures across transport systems. The proposed framework estimates the vulnerability of the network with respect to a specific hazard, combining the network topology and the functional attributes of the transportation infrastructure components. A case study with real-world data is conducted to demonstrate the applicability of the framework to the Houston freight transportation network, and to understand the network performance under different scenarios. This study presents an alternate method that stakeholders may use to assess interdependent transportation network vulnerability when more detailed flow-based data is not available.
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spelling doaj-art-1c1c742373e9411a964336b434db35cd2024-12-18T08:54:09ZengElsevierSustainability Analytics and Modeling2667-25962024-01-014100034Network-based method for assessing multi-modal transportation network vulnerability to cascading failuresJingran Sun0Kyle Bathgate1Shidong Pan2Zhanmin Zhang3Center for Transportation Research, The University of Texas at Austin, Austin, 78759, TX, USA; Corresponding author.Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, Austin, 78712, TX, USADepartment of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, Austin, 78712, TX, USADepartment of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, Austin, 78712, TX, USATransportation systems are vulnerable to disruptive events such as natural disasters, industrial accidents, terrorist attacks, and climate change. Vulnerability assessment is necessary to understand the impacts of these disruptive events, identify underlying deficiencies within the network, and improve transportation system resilience. Multi-modal transportation networks are often interdependent and form a “system of systems”, which creates a susceptibility to cascading indirect impacts within the integrated transportation network. Accurately modeling these interdependencies typically requires a large amount of data, such as traffic flow and travel demand information for transportation systems, which may not be available or accessible. This paper proposes a network topology-based framework to conduct an interdependent transportation network vulnerability analysis by introducing an algorithm to simulate cascading failures across transport systems. The proposed framework estimates the vulnerability of the network with respect to a specific hazard, combining the network topology and the functional attributes of the transportation infrastructure components. A case study with real-world data is conducted to demonstrate the applicability of the framework to the Houston freight transportation network, and to understand the network performance under different scenarios. This study presents an alternate method that stakeholders may use to assess interdependent transportation network vulnerability when more detailed flow-based data is not available.http://www.sciencedirect.com/science/article/pii/S2667259624000067Infrastructure interdependenciesTransportation systemsResilienceCascading failuresBetweenness centrality
spellingShingle Jingran Sun
Kyle Bathgate
Shidong Pan
Zhanmin Zhang
Network-based method for assessing multi-modal transportation network vulnerability to cascading failures
Sustainability Analytics and Modeling
Infrastructure interdependencies
Transportation systems
Resilience
Cascading failures
Betweenness centrality
title Network-based method for assessing multi-modal transportation network vulnerability to cascading failures
title_full Network-based method for assessing multi-modal transportation network vulnerability to cascading failures
title_fullStr Network-based method for assessing multi-modal transportation network vulnerability to cascading failures
title_full_unstemmed Network-based method for assessing multi-modal transportation network vulnerability to cascading failures
title_short Network-based method for assessing multi-modal transportation network vulnerability to cascading failures
title_sort network based method for assessing multi modal transportation network vulnerability to cascading failures
topic Infrastructure interdependencies
Transportation systems
Resilience
Cascading failures
Betweenness centrality
url http://www.sciencedirect.com/science/article/pii/S2667259624000067
work_keys_str_mv AT jingransun networkbasedmethodforassessingmultimodaltransportationnetworkvulnerabilitytocascadingfailures
AT kylebathgate networkbasedmethodforassessingmultimodaltransportationnetworkvulnerabilitytocascadingfailures
AT shidongpan networkbasedmethodforassessingmultimodaltransportationnetworkvulnerabilitytocascadingfailures
AT zhanminzhang networkbasedmethodforassessingmultimodaltransportationnetworkvulnerabilitytocascadingfailures