File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: A cell-based logit-opportunity taxi customer-search model

TitleA cell-based logit-opportunity taxi customer-search model
Authors
Issue Date2014
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/trc
Citation
Transportation Research Part C: Emerging Technologies, 2014, v. 48, p. 84-96 How to Cite?
AbstractThis paper proposes a cell-based model to predict local customer-search movements of vacant taxi drivers, which incorporates the modeling principles of the logit-based search model and the intervening opportunity model. The local customer-search movements were extracted from the global positioning system data of 460 Hong Kong urban taxis and inputted into a cell-based taxi operating network to calibrate the model and validate the modeling concepts. The model results reveal that the taxi drivers’ local search decisions are significantly affected by the (cumulative) probability of successfully picking up a customer along the search route, and that the drivers do not search their customers under the random walk principle. The proposed model helps predict the effects of the implementation of the policies in adjusting the taxi fleet size and the changes in passenger demand on the customer-search distance and time of taxi drivers.
Persistent Identifierhttp://hdl.handle.net/10722/207715
ISSN
2015 Impact Factor: 3.075
2015 SCImago Journal Rankings: 2.062

 

DC FieldValueLanguage
dc.contributor.authorWong, RCP-
dc.contributor.authorSzeto, WY-
dc.contributor.authorWong, SC-
dc.date.accessioned2015-01-19T09:18:28Z-
dc.date.available2015-01-19T09:18:28Z-
dc.date.issued2014-
dc.identifier.citationTransportation Research Part C: Emerging Technologies, 2014, v. 48, p. 84-96-
dc.identifier.issn0968-090X-
dc.identifier.urihttp://hdl.handle.net/10722/207715-
dc.description.abstractThis paper proposes a cell-based model to predict local customer-search movements of vacant taxi drivers, which incorporates the modeling principles of the logit-based search model and the intervening opportunity model. The local customer-search movements were extracted from the global positioning system data of 460 Hong Kong urban taxis and inputted into a cell-based taxi operating network to calibrate the model and validate the modeling concepts. The model results reveal that the taxi drivers’ local search decisions are significantly affected by the (cumulative) probability of successfully picking up a customer along the search route, and that the drivers do not search their customers under the random walk principle. The proposed model helps predict the effects of the implementation of the policies in adjusting the taxi fleet size and the changes in passenger demand on the customer-search distance and time of taxi drivers.-
dc.languageeng-
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/trc-
dc.relation.ispartofTransportation Research Part C: Emerging Technologies-
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in Transportation Research Part C: Emerging Technologies. 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 C: Emerging Technologies, 2014, v. 48, p. 84-96. DOI: 10.1016/j.trc.2014.08.010-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleA cell-based logit-opportunity taxi customer-search model-
dc.typeArticle-
dc.identifier.emailSzeto, WY: ceszeto@hku.hk-
dc.identifier.emailWong, SC: hhecwsc@hku.hk-
dc.identifier.authoritySzeto, WY=rp01377-
dc.identifier.authorityWong, SC=rp00191-
dc.identifier.doi10.1016/j.trc.2014.08.010-
dc.identifier.scopuseid_2-s2.0-84907487360-
dc.identifier.hkuros242200-
dc.identifier.volume48-
dc.identifier.spage84-
dc.identifier.epage96-
dc.publisher.placeUnited Kingdom-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats