Modeling the influence of disturbances in high-speed railway systems
dc.contributor.author
Huang, Ping
dc.contributor.author
Wen, Chao
dc.contributor.author
Peng, Qiyuan
dc.contributor.author
Jiang, Chaozhe
dc.contributor.author
Yang, Yuxiang
dc.contributor.author
Fu, Zhuan
dc.date.accessioned
2021-05-27T05:16:34Z
dc.date.available
2021-05-26T12:50:14Z
dc.date.available
2021-05-27T05:16:34Z
dc.date.issued
2019
dc.identifier.issn
1979-2016
dc.identifier.issn
2042-3195
dc.identifier.other
10.1155/2019/8639589
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/486657
dc.identifier.doi
10.3929/ethz-b-000486657
dc.description.abstract
Accurately forecasting the influence of disturbances in High-Speed Railways (HSR) has great significance for improving real-time train dispatching and operation management. In this paper, we show how to use historical train operation records to estimate the influence of high-speed train disturbances (HSTD), including the number of affected trains (NAT) and total delayed time (TDT), considering the timetable and disturbance characteristics. We first extracted data about the disturbances and their affected train groups from historical train operation records of Wuhan-Guangzhou (W-G) HSR in China. Then, in order to recognize the concatenations and differences of disturbances, we used a K-Means clustering algorithm to classify them into four categories. Next, parametric and nonparametric density estimation approaches were applied to fit the distributions of NAT and TDT of each clustered category, and the goodness-of-fit testing results showed that Log-normal and Gamma distribution probability densities are the best functions to approximate the distribution of NAT and TDT of different disturbance clusters. Specifically, the validation results show that the proposed models accurately revealed the characteristics of HSTD and that these models can be used in real-time dispatch to predict the NAT and TDT, once the basic features of disturbances are known.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Hindawi
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.title
Modeling the influence of disturbances in high-speed railway systems
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.journal.title
Journal of Advanced Transportation
ethz.journal.volume
2019
en_US
ethz.journal.abbreviated
J Advanced Transp
ethz.pages.start
8639589
en_US
ethz.size
13 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.publication.place
London
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02610 - Inst. f. Verkehrspl. u. Transportsyst. / Inst. Transport Planning and Systems::09611 - Corman, Francesco / Corman, Francesco
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02655 - Netzwerk Stadt u. Landschaft ARCH u BAUG / Network City and Landscape ARCH and BAUG
*
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02610 - Inst. f. Verkehrspl. u. Transportsyst. / Inst. Transport Planning and Systems::09611 - Corman, Francesco / Corman, Francesco
en_US
ethz.date.deposited
2021-05-26T12:50:20Z
ethz.source
FORM
ethz.eth
no
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2021-05-27T05:16:43Z
ethz.rosetta.lastUpdated
2025-02-13T23:33:06Z
ethz.rosetta.versionExported
true
ethz.COinS
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