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dc.contributor.authorTaşcıkaraoğlu, Fatma Yıldızen_US
dc.contributor.authorAksoy, Gökeren_US
dc.date.accessioned2022-10-26T19:38:05Z
dc.date.available2022-10-26T19:38:05Z
dc.date.issued2022-08
dc.identifier.citationTaşcıkaraoğlu, F. Y. & Aksoy, G. (2022). Identification of sensor location and link flow reconstruction using turn ratio and flow sensors in an arterial network. Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, 1-12.doi:10.1080/15472450.2022.2119385en_US
dc.identifier.issn1547-2450
dc.identifier.issn1547-2442
dc.identifier.urihttps://hdl.handle.net/11729/5095
dc.identifier.urihttp://dx.doi.org/10.1080/15472450.2022.2119385
dc.descriptionThis work was supported by The Scientific and Technological Research Council of Turkey (TUBITAK) under Project Grant Number 117E182.en_US
dc.description.abstractIn this article, a quadratic programming problem is considered to identify all link flows in an arterial network when there are unmeasured link flows. A graphical method is provided to determine the minimum number of measurements and sensor locations required to obtain a fully observable model. It is shown that this method is also valid for the augmented graph with turn ratio measurements. If the minimum measurements required are met, a fully determined network can be obtained. If there is not enough measurement, a bound on the magnitude of the resulting inaccuracy in terms of vehicle kilometers traveled (VKT) can be calculated by the proposed linear programming method. The model is that of a queueing network; the parameters describe network geometry, saturation flow rates, turning ratios, timing plan and link flows. Three case studies are conducted to validate this approach. The first two cases are to calculate all missing flows by using a few numbers of measurements and minimum number of measurements required, respectively. Upper and lower bounds in terms of VKT are also calculated for these cases. Third case is to obtain a fully determined network with the minimum number of flow measurements when turn ratio sensors are included. Real measurements are collected from a network in Mugla including 55 links and 16 intersections. Vissim simulator is used to analyze the accuracy of the link flow calculations obtained from the proposed method. The results show that the proposed programming method can calculate the missing flows with a high accuracy and short computation time.en_US
dc.language.isoengen_US
dc.publisherTaylor and Francis Ltd.en_US
dc.relation.isversionof10.1080/15472450.2022.2119385
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFlow estimationen_US
dc.subjectSensor locationen_US
dc.subjectTurn ratio sensoren_US
dc.subjectVissim simulationen_US
dc.subjectFlow measurementen_US
dc.subjectLocationen_US
dc.subjectQuadratic programmingen_US
dc.subjectArterial networksen_US
dc.subjectFlow reconstructionen_US
dc.subjectLink-flowen_US
dc.subjectSensor locationen_US
dc.subjectTurn flowen_US
dc.subjectTurns ratiosen_US
dc.subjectVehicle-kilometer-travelleden_US
dc.subjectLinear programmingen_US
dc.subjectTraffic controlen_US
dc.subjectDemand estimationen_US
dc.subjectTraffic simulationen_US
dc.titleIdentification of sensor location and link flow reconstruction using turn ratio and flow sensors in an arterial networken_US
dc.typearticleen_US
dc.description.versionPublisher's Versionen_US
dc.relation.journalJournal of Intelligent Transportation Systems: Technology, Planning, and Operationsen_US
dc.contributor.departmentIşık Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, İnşaat Mühendisliği Bölümüen_US
dc.contributor.departmentIşık University, Faculty of Engineering and Natural Sciences, Department of Civil Engineeringen_US
dc.contributor.authorID0000-0003-4592-7048
dc.identifier.startpage1
dc.identifier.endpage11
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorAksoy, Gökeren_US
dc.relation.indexWOSen_US
dc.relation.indexScopusen_US
dc.relation.indexSocial Sciences Citation Index (SSCI)en_US
dc.relation.indexScience Citation Index Expanded (SCI-EXPANDED)
dc.description.qualityQ2
dc.description.wosidWOS:000851616300001


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