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dc.contributor.authorMerkebe Getachew Demissieen_US
dc.contributor.authorSanti Phithakkitnukoonen_US
dc.contributor.authorLina Kattanen_US
dc.date.accessioned2018-11-29T07:39:32Z-
dc.date.available2018-11-29T07:39:32Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn15249050en_US
dc.identifier.other2-s2.0-85055028513en_US
dc.identifier.other10.1109/TITS.2018.2868468en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85055028513&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/62673-
dc.description.abstractIEEE The development of a trip distribution model requires a massive data collection task, such as expensive travel surveys to identify trip makers' origin and destination zones. Intra-zonal trips are usually ignored in the development of trip distribution models because of the difficulty associated with measuring travel costs. However, ignoring intra-zonal trips leads to incomplete model estimation especially when the zone size is large, and thus, the number of intra-zonal trips is substantial. This is especially important, with the growing interest around the world on creating more walkable and bikeable cities where a high share of those trips is intra-zonal. In this paper, we use mobile phone data to derive country-wide mobility trends. A set of doubly constrained trip distribution models that integrates intra-zonal trips was estimated for 123-district-level traffic analysis zones. We present two approaches to estimate the intra-zonal travel costs measured in terms of trip distance. Our analysis reveals that the average intra-zonal trip distances obtained from the two approaches provide different levels of sensitivity to the distance-decay effect. Our result also shows that model estimation in the absence of intra-zonal trips produces biased estimates.en_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.titleTrip Distribution Modeling Using Mobile Phone Data: Emphasis on Intra-Zonal Tripsen_US
dc.typeJournalen_US
article.title.sourcetitleIEEE Transactions on Intelligent Transportation Systemsen_US
article.stream.affiliationsUniversity of Calgaryen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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