Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-27277
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dc.contributor.authorWang, Pengling-
dc.contributor.authorJeiziner, Annik-
dc.contributor.authorLuan, Xiaojie-
dc.contributor.authorDe Martinis, Valerio-
dc.contributor.authorCorman, Francesco-
dc.date.accessioned2023-03-11T12:59:13Z-
dc.date.available2023-03-11T12:59:13Z-
dc.date.issued2022-
dc.identifier.issn2042-3195de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/27277-
dc.description.abstractThe hierarchical connection of Rail Traffic Management System (TMS) and Automatic Train Operation (ATO) for mainline railways has been proposed for a while; however, few have investigated this hierarchical connection with the real field. This paper studies in detail the benefits and limitations of an integrated framework of TMS and ATO in stochastic and dynamic conditions in terms of punctuality, energy efficiency, and conflict-resolving. A simulation is built by interfacing a rescheduling tool and a stand-alone ATO tool with the realistic traffic simulation environment OpenTrack. The investigation refers to different disturbed traffic scenarios obtained by sampling train entrance delays and dwell times within a typical Monte Carlo scheme. Results obtained for the Dutch railway corridor Utrecht–Den Bosch prove the value of the approach. In case of no disruptions, the implementation of ATO systems is beneficial for maintaining timetables and saving energy costs. In case of delay disruptions, the TMS rescheduling has its full effect only if trains are able to follow TMS rescheduled timetables, while the energy-saving by using ATO can only be achieved with conflict-free schedules. A bi-directional communication between ATO and TMS is therefore beneficial for conflict-resolving and energy saving.de_CH
dc.language.isoende_CH
dc.publisherHindawide_CH
dc.relation.ispartofJournal of Advanced Transportationde_CH
dc.rightshttps://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectRailway operationde_CH
dc.subjectAutomatic train operationde_CH
dc.subjectTraffic management systemde_CH
dc.subject.ddc380: Verkehrde_CH
dc.titleAn experimental analysis of hierarchical rail traffic and train control in a stochastic environmentde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
dc.identifier.doi10.1155/2022/8674538de_CH
dc.identifier.doi10.21256/zhaw-27277-
zhaw.funding.euNode_CH
zhaw.issue8674538de_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume2022de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedTransport und Mobilitätde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen School of Engineering

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Wang, P., Jeiziner, A., Luan, X., De Martinis, V., & Corman, F. (2022). An experimental analysis of hierarchical rail traffic and train control in a stochastic environment. Journal of Advanced Transportation, 2022(8674538). https://doi.org/10.1155/2022/8674538
Wang, P. et al. (2022) ‘An experimental analysis of hierarchical rail traffic and train control in a stochastic environment’, Journal of Advanced Transportation, 2022(8674538). Available at: https://doi.org/10.1155/2022/8674538.
P. Wang, A. Jeiziner, X. Luan, V. De Martinis, and F. Corman, “An experimental analysis of hierarchical rail traffic and train control in a stochastic environment,” Journal of Advanced Transportation, vol. 2022, no. 8674538, 2022, doi: 10.1155/2022/8674538.
WANG, Pengling, Annik JEIZINER, Xiaojie LUAN, Valerio DE MARTINIS und Francesco CORMAN, 2022. An experimental analysis of hierarchical rail traffic and train control in a stochastic environment. Journal of Advanced Transportation. 2022. Bd. 2022, Nr. 8674538. DOI 10.1155/2022/8674538
Wang, Pengling, Annik Jeiziner, Xiaojie Luan, Valerio De Martinis, and Francesco Corman. 2022. “An Experimental Analysis of Hierarchical Rail Traffic and Train Control in a Stochastic Environment.” Journal of Advanced Transportation 2022 (8674538). https://doi.org/10.1155/2022/8674538.
Wang, Pengling, et al. “An Experimental Analysis of Hierarchical Rail Traffic and Train Control in a Stochastic Environment.” Journal of Advanced Transportation, vol. 2022, no. 8674538, 2022, https://doi.org/10.1155/2022/8674538.


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