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Origin-destination trip table estimation based on subarea network OD flow and vehicle trajectory data

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dc.contributor.authorKim, Hyunmyung-
dc.contributor.authorNam, Daisik-
dc.contributor.authorSuh, Wonho-
dc.contributor.authorCheon, Seung Hoon-
dc.date.accessioned2021-06-22T13:03:40Z-
dc.date.available2021-06-22T13:03:40Z-
dc.date.issued2018-04-
dc.identifier.issn0308-1060-
dc.identifier.issn1029-0354-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/7989-
dc.description.abstractIdentifying accurate origin-destination (O-D) travel demand is one of the most important and challenging tasks in the transportation planning field. Recently, a wide range of traffic data has been made available. This paper proposes an O-D estimation model using multiple field data. This study takes advantage of emerging technologies- car navigation systems, highway toll collecting systems and link traffic counts- to determine O-D demand. The proposed method is unique since these multiple data are combined to improve the accuracy of O-D estimation for an entire network. We tested our model on a sample network and found great potential for using multiple data as a means of O-D estimation. The errors of a single input data source do not critically affect the model's overall accuracy, meaning that combining multiple data provides resilience to these errors. It is suggested that the model is a feasible means for more reliable O-D estimation.-
dc.format.extent21-
dc.language영어-
dc.language.isoENG-
dc.publisherTAYLOR & FRANCIS LTD-
dc.titleOrigin-destination trip table estimation based on subarea network OD flow and vehicle trajectory data-
dc.typeArticle-
dc.publisher.location영국-
dc.identifier.doi10.1080/03081060.2018.1435437-
dc.identifier.scopusid2-s2.0-85041580373-
dc.identifier.wosid000426957500003-
dc.identifier.bibliographicCitationTRANSPORTATION PLANNING AND TECHNOLOGY, v.41, no.3, pp 265 - 285-
dc.citation.titleTRANSPORTATION PLANNING AND TECHNOLOGY-
dc.citation.volume41-
dc.citation.number3-
dc.citation.startPage265-
dc.citation.endPage285-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaTransportation-
dc.relation.journalWebOfScienceCategoryTransportation Science & Technology-
dc.subject.keywordPlusELECTRONIC TOLL COLLECTION-
dc.subject.keywordPlusTRAFFIC COUNT INCONSISTENCIES-
dc.subject.keywordPlusMATRIX ESTIMATION PROBLEM-
dc.subject.keywordPlusREAL-TIME ESTIMATION-
dc.subject.keywordPlusPROGRAMMING APPROACH-
dc.subject.keywordPlusRECURSIVE ESTIMATION-
dc.subject.keywordPlusLINK FLOWS-
dc.subject.keywordPlusVOLUMES-
dc.subject.keywordPlusMODEL-
dc.subject.keywordAuthorTravel demand-
dc.subject.keywordAuthorO-D trip table estimation-
dc.subject.keywordAuthorvehicle trajectory-
dc.subject.keywordAuthorsubarea O-D-
dc.subject.keywordAuthormultiple field data-
dc.subject.keywordAuthormodel-
dc.identifier.urlhttps://www.tandfonline.com/doi/full/10.1080/03081060.2018.1435437-
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