Short-term Travel-time Prediction on Highway: A Review on Model-based Approach

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dc.contributor.authorOh, Simonko
dc.contributor.authorByon, Young-jiko
dc.contributor.authorJang, Kitaeko
dc.contributor.authorYeo, Hwasooko
dc.date.accessioned2018-01-30T04:15:54Z-
dc.date.available2018-01-30T04:15:54Z-
dc.date.created2017-01-29-
dc.date.created2017-01-29-
dc.date.issued2018-01-
dc.identifier.citationKSCE JOURNAL OF CIVIL ENGINEERING, v.22, no.1, pp.298 - 310-
dc.identifier.issn1226-7988-
dc.identifier.urihttp://hdl.handle.net/10203/238758-
dc.description.abstractEmerging technologies provide a venue on which on-line traffic controls and management systems can be implemented. For such applications, having access to accurate predictions on travel-times are mandatory for their successful operations. Transportation engineers have developed numerous approaches including model-based approaches. The model-based approaches consider underlying traffic mechanisms and behaviors in developing the prediction procedures and they are logically intuitive unlike datadriven approaches. Because of this explanation power, the model-based approaches have been developed for the on-line control purposes. For departments of transportation (DOTs), it is still a challenge to choose a specific approach that meets their requirements. In efforts to develop a unique guideline for transportation engineers and decision makers when considering for implementing modelbased approaches for highways, this paper reviews model-based travel-time prediction approaches by classifying them into four categories according to the level of details involved in the model: Macroscopic, Mesoscopic, CA-based, and Microscopic. Then each method is evaluated from five main perspectives: Prediction range, Accuracy, Efficiency, Applicability, and Robustness. Finally, this paper concludes with evaluations of model-based approaches in general and discusses them in relation to data-driven approaches along with future research directions.-
dc.languageEnglish-
dc.publisherKOREAN SOCIETY OF CIVIL ENGINEERS-KSCE-
dc.subjectCELL TRANSMISSION MODEL-
dc.subjectTRAFFIC FLOW-
dc.subjectNEURAL-NETWORKS-
dc.subjectMISSING DATA-
dc.subjectSIMULATION-
dc.subjectFRAMEWORK-
dc.subjectAUTOMATA-
dc.subjectMETANET-
dc.subjectSYSTEM-
dc.subjectWAVES-
dc.titleShort-term Travel-time Prediction on Highway: A Review on Model-based Approach-
dc.typeArticle-
dc.identifier.wosid000418391200034-
dc.identifier.scopusid2-s2.0-85018351657-
dc.type.rimsART-
dc.citation.volume22-
dc.citation.issue1-
dc.citation.beginningpage298-
dc.citation.endingpage310-
dc.citation.publicationnameKSCE JOURNAL OF CIVIL ENGINEERING-
dc.identifier.doi10.1007/s12205-017-0535-8-
dc.contributor.localauthorJang, Kitae-
dc.contributor.localauthorYeo, Hwasoo-
dc.contributor.nonIdAuthorByon, Young-ji-
dc.description.isOpenAccessN-
dc.type.journalArticleReview-
dc.subject.keywordAuthorhighway travel-time prediction-
dc.subject.keywordAuthormodel-based approach-
dc.subject.keywordAuthortraffic simulation-
dc.subject.keywordAuthorTraffic Management System (TMS)-
dc.subject.keywordAuthorIntelligent Transportation System (ITS)-
dc.subject.keywordAuthorOn-line simulation-
dc.subject.keywordPlusCELL TRANSMISSION MODEL-
dc.subject.keywordPlusTRAFFIC FLOW-
dc.subject.keywordPlusNEURAL-NETWORKS-
dc.subject.keywordPlusMISSING DATA-
dc.subject.keywordPlusSIMULATION-
dc.subject.keywordPlusFRAMEWORK-
dc.subject.keywordPlusAUTOMATA-
dc.subject.keywordPlusMETANET-
dc.subject.keywordPlusSYSTEM-
dc.subject.keywordPlusWAVES-
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