Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorShen, Yindongen_UK
dc.contributor.authorXu, Jiaen_UK
dc.contributor.authorLi, Jingpengen_UK
dc.description.abstractVehicle scheduling plays a profound role in public transit planning. Traditional approaches for the Vehicle Scheduling Problem (VSP) are based on a set of predetermined trips in a given timetable. Each trip contains a departure point/time and an arrival point/time whilst the trip time (i.e. the time duration of a trip) is fixed. Based on fixed durations, the resulting schedule is hard to comply with in practice due to the variability of traffic and driving conditions. To enhance the robustness of the schedule to be compiled, the VSP based on stochastic trip times instead of fixed ones is studied. The trip times follow the probability distributions obtained from the data captured by Automatic Vehicle Locating (AVL) systems. A network flow model featuring the stochastic trips is devised to better represent this problem, meanwhile the compatibility of any pair of trips is redefined based on trip time distributions instead of fixed values as traditionally done. A novel probabilistic model of the VSP is proposed with the objectives of minimizing the total cost and maximizing the on-time performance. Experiments show that the probabilistic model may lead to more robust schedules without increasing fleet size.en_UK
dc.relationShen Y, Xu J & Li J (2016) A Probabilistic Model for Vehicle Scheduling Based on Stochastic Trip Times. Transportation Research - Part B - Methodological, 85, pp. 19-31.
dc.rightsThe publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.en_UK
dc.subjectVehicle schedulingen_UK
dc.subjectProbabilistic modelen_UK
dc.subjectStochastic trip timeen_UK
dc.subjectDelay propagationen_UK
dc.titleA Probabilistic Model for Vehicle Scheduling Based on Stochastic Trip Timesen_UK
dc.typeJournal Articleen_UK
dc.rights.embargoreason[TRB2016.pdf] The publisher does not allow this work to be made publicly available in this Repository therefore there is an embargo on the full text of the work.en_UK
dc.citation.jtitleTransportation Research Part B: Methodologicalen_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.affiliationHuazhong University of Science and Technologyen_UK
dc.contributor.affiliationHuazhong University of Science and Technologyen_UK
dc.contributor.affiliationComputing Scienceen_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
local.rioxx.authorShen, Yindong|en_UK
local.rioxx.authorXu, Jia|en_UK
local.rioxx.authorLi, Jingpeng|0000-0002-6758-0084en_UK
local.rioxx.projectInternal Project|University of Stirling|
Appears in Collections:Computing Science and Mathematics Journal Articles

Files in This Item:
File Description SizeFormat 
TRB2016.pdfFulltext - Published Version589.83 kBAdobe PDFUnder Embargo until 2999-12-16    Request a copy

This item is protected by original copyright

Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved

If you believe that any material held in STORRE infringes copyright, please contact providing details and we will remove the Work from public display in STORRE and investigate your claim.