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dc.contributor.author
Wang, Pengling
dc.contributor.author
Trivella, Alessio
dc.contributor.author
Goverde, Rob M.P.
dc.contributor.author
Corman, Francesco
dc.date.accessioned
2021-06-25T06:23:40Z
dc.date.available
2020-09-05T13:18:56Z
dc.date.available
2020-09-07T07:01:50Z
dc.date.available
2021-06-25T06:23:40Z
dc.date.issued
2020-10
dc.identifier.issn
0968-090X
dc.identifier.other
10.1016/j.trc.2020.102680
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/438686
dc.identifier.doi
10.3929/ethz-b-000438686
dc.description.abstract
In this paper we study the problem of computing train trajectories in an uncertain environment in which the values of some system parameters are difficult to determine. Specifically, we consider uncertainty in traction force and train resistance, and their impact on travel time and energy consumption. Our ultimate goal is to be able to control trains such that they will arrive on-time, i.e. within the planned running time, regardless of uncertain factors affecting their dynamic or kinematic performance. We formulate the problem as a Markov decision process and solve it using a novel numerical approach which combines: (i) an off-line approximate dynamic programming (ADP) method to learn the energy and time costs over iterations, and (ii) an on-line search process to determine energy-efficient driving strategies that respect the real-time time windows, more in general expressed as train path envelope constraints. To evaluate the performance of our approach, we conducted a numerical study using real-life railway infrastructure and train data. Compared to a set of benchmark driving strategies, the trajectories from our ADP-based method reduce the probability of delayed arrival, and at the same time are able to better use the available running time for energy saving. Our results show that accounting for uncertainty is relevant when computing train trajectories and that our ADP-based method can handle this uncertainty effectively.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject
Train trajectory optimization
en_US
dc.subject
Parametric uncertainty
en_US
dc.subject
Approximate dynamic programming
en_US
dc.title
Train trajectory optimization for improved on-time arrival under parametric uncertainty
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
dc.date.published
2020-09-01
ethz.journal.title
Transportation Research Part C: Emerging Technologies
ethz.journal.volume
119
en_US
ethz.journal.abbreviated
Transp. Res., Part C Emerg. Technol.
ethz.pages.start
102680
en_US
ethz.size
20 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.grant
DADA - Dynamic data driven Approaches for stochastic Delay propagation Avoidance in railways
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Amsterdam
en_US
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
en_US
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.grant.agreementno
181210
ethz.grant.fundername
SNF
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.program
Eccellenza
ethz.date.deposited
2020-09-05T13:19:08Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-09-07T07:02:07Z
ethz.rosetta.lastUpdated
2024-02-02T14:10:10Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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