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Article: A new schedule-based transit assignment model with travel strategies and supply uncertainties

TitleA new schedule-based transit assignment model with travel strategies and supply uncertainties
Authors
Issue Date2014
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/trb
Citation
Transportation Research Part B: Methodological, 2014, v. 67, p. 35-67 How to Cite?
AbstractThis paper proposes a new scheduled-based transit assignment model. Unlike other schedule-based models in the literature, we consider supply uncertainties and assume that users adopt strategies to travel from their origins to their destinations. We present an analytical formulation to ensure that on-board passengers continuing to the next stop have priority and waiting passengers are loaded on a first-come-first-serve basis. We propose an analytical model that captures the stochastic nature of the transit schedules and in-vehicle travel times due to road conditions, incidents, or adverse weather. We adopt a mean variance approach that can consider the covariance of travel time between links in a space–time graph but still lead to a robust transit network loading procedure when optimal strategies are adopted. The proposed model is formulated as a user equilibrium problem and solved by an MSA-type algorithm. Numerical results are reported to show the effects of supply uncertainties on the travel strategies and departure times of passengers.
Persistent Identifierhttp://hdl.handle.net/10722/202642
ISSN
2015 Impact Factor: 3.769
2015 SCImago Journal Rankings: 3.905

 

DC FieldValueLanguage
dc.contributor.authorHamdouch, Y-
dc.contributor.authorSzeto, WY-
dc.contributor.authorJiang, Y-
dc.date.accessioned2014-09-19T09:14:10Z-
dc.date.available2014-09-19T09:14:10Z-
dc.date.issued2014-
dc.identifier.citationTransportation Research Part B: Methodological, 2014, v. 67, p. 35-67-
dc.identifier.issn0191-2615-
dc.identifier.urihttp://hdl.handle.net/10722/202642-
dc.description.abstractThis paper proposes a new scheduled-based transit assignment model. Unlike other schedule-based models in the literature, we consider supply uncertainties and assume that users adopt strategies to travel from their origins to their destinations. We present an analytical formulation to ensure that on-board passengers continuing to the next stop have priority and waiting passengers are loaded on a first-come-first-serve basis. We propose an analytical model that captures the stochastic nature of the transit schedules and in-vehicle travel times due to road conditions, incidents, or adverse weather. We adopt a mean variance approach that can consider the covariance of travel time between links in a space–time graph but still lead to a robust transit network loading procedure when optimal strategies are adopted. The proposed model is formulated as a user equilibrium problem and solved by an MSA-type algorithm. Numerical results are reported to show the effects of supply uncertainties on the travel strategies and departure times of passengers.-
dc.languageeng-
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/trb-
dc.relation.ispartofTransportation Research Part B: Methodological-
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in Transportation Research Part B: Methodological. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Transportation Research Part B: Methodological, 2014, v. 67, p. 35-67. DOI: 10.1016/j.trb.2014.05.002-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleA new schedule-based transit assignment model with travel strategies and supply uncertainties-
dc.typeArticle-
dc.identifier.emailSzeto, WY: ceszeto@hku.hk-
dc.identifier.authoritySzeto, WY=rp01377en_US
dc.description.naturepostprint-
dc.identifier.doi10.1016/j.trb.2014.05.002-
dc.identifier.hkuros236080-
dc.identifier.volume67-
dc.identifier.spage35-
dc.identifier.epage67-
dc.publisher.placeUnited Kingdom-

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