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Article: A spatiotemporal analysis of the robustness of high-speed rail network in China

TitleA spatiotemporal analysis of the robustness of high-speed rail network in China
Authors
KeywordsHigh-speed railNetwork capacity
Weighted network efficiency
Robustness
Spatiotemporal variation
Issue Date2020
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/trd
Citation
Transportation Research Part D: Transport and Environment, 2020, v. 89, p. article no. 102584 How to Cite?
AbstractMost studies on the robustness of high-speed rail (HSR) network examine the issue at the aggregate level and consider a fixed period (e.g., a day or a month), regardless of when and where the disruption occurs. This study proposes a holistic framework of assessing the impact of node cascading disruptions in HSR network considering different affected times-of-day and geographic regions. A weighted network efficiency metric is proposed to assess network performance considering both travel time and train frequency along the topological shortest path. Analysis of China’s HSR finds that (1) the network is less robust to disruptions occurring in East China or along the Harbin-Hong Kong corridor; (2) Disruptions during 10:00–15:00 have the largest impact; (3) lockdowns during COVID-19 outbreak in Jan-Feb 2020 led to 14.5% reduction in overall network efficiency. The results generate insights into further development of the HSR network and provide policy support for HSR resilience-enhancing strategies.
DescriptionHybrid open access
Persistent Identifierhttp://hdl.handle.net/10722/295451
ISSN
2021 Impact Factor: 7.041
2020 SCImago Journal Rankings: 1.600
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorJiao, J-
dc.contributor.authorZhang, F-
dc.contributor.authorLiu, J-
dc.date.accessioned2021-01-25T11:15:07Z-
dc.date.available2021-01-25T11:15:07Z-
dc.date.issued2020-
dc.identifier.citationTransportation Research Part D: Transport and Environment, 2020, v. 89, p. article no. 102584-
dc.identifier.issn1361-9209-
dc.identifier.urihttp://hdl.handle.net/10722/295451-
dc.descriptionHybrid open access-
dc.description.abstractMost studies on the robustness of high-speed rail (HSR) network examine the issue at the aggregate level and consider a fixed period (e.g., a day or a month), regardless of when and where the disruption occurs. This study proposes a holistic framework of assessing the impact of node cascading disruptions in HSR network considering different affected times-of-day and geographic regions. A weighted network efficiency metric is proposed to assess network performance considering both travel time and train frequency along the topological shortest path. Analysis of China’s HSR finds that (1) the network is less robust to disruptions occurring in East China or along the Harbin-Hong Kong corridor; (2) Disruptions during 10:00–15:00 have the largest impact; (3) lockdowns during COVID-19 outbreak in Jan-Feb 2020 led to 14.5% reduction in overall network efficiency. The results generate insights into further development of the HSR network and provide policy support for HSR resilience-enhancing strategies.-
dc.languageeng-
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/trd-
dc.relation.ispartofTransportation Research Part D: Transport and Environment-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectHigh-speed railNetwork capacity-
dc.subjectWeighted network efficiency-
dc.subjectRobustness-
dc.subjectSpatiotemporal variation-
dc.titleA spatiotemporal analysis of the robustness of high-speed rail network in China-
dc.typeArticle-
dc.identifier.emailZhang, F: fnzhang@hku.hk-
dc.identifier.authorityZhang, F=rp02657-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1016/j.trd.2020.102584-
dc.identifier.scopuseid_2-s2.0-85094959143-
dc.identifier.hkuros320976-
dc.identifier.volume89-
dc.identifier.spagearticle no. 102584-
dc.identifier.epagearticle no. 102584-
dc.identifier.isiWOS:000597379000004-
dc.publisher.placeUnited Kingdom-

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