Nonlinear model predictive control of large-scale urban road networks via average speed control

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dc.authoridYildirimoglu, Mehmet/0000-0002-6534-4053
dc.authoridSirmatel, Isik Ilber/0000-0002-3679-7635
dc.authorwosidYildirimoglu, Mehmet/F-7317-2017
dc.contributor.authorSirmatel, Isik Ilber
dc.contributor.authorYildirimoglu, Mehmet
dc.date.accessioned2024-06-12T11:07:58Z
dc.date.available2024-06-12T11:07:58Z
dc.date.issued2023
dc.departmentTrakya Üniversitesien_US
dc.description.abstractControlling traffic in large-scale urban road networks is a challenging problem. Aggregated dynamical models, based on the macroscopic fundamental diagram (MFD) of urban traffic, enable model-based control design. As an alternative to perimeter control actuation commonly used in MFD-based control, in this paper, we propose actuation over regional space-mean speeds, which we name average speed control. The method involves manipulation of regional speeds via instrumentation similar to variable speed limits in freeways, or using vehicle-to-infrastructure communication. We develop nonlinear model predictive control schemes considering actuation over average speed and perimeter control. Their performances are compared using simulations on congested scenarios, the results of which suggest potential of the method as an alternative or complementary actuation to perimeter control.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkiye (TUBITAK) through the 2232 B International Early Stage Researchers Program [121C076]; Australian Research Council (ARC) through the Discovery Early Career Researcher Award (DECRA) [DE220101320]; Australian Research Council [DE220101320] Funding Source: Australian Research Councilen_US
dc.description.sponsorshipThe first author is supported by the Scientific and Technological Research Council of Turkiye (TUBITAK) through the 2232 B International Early Stage Researchers Program (project number: 121C076) .1 The second author is supported by the Australian Research Council (ARC) through the Discovery Early Career Researcher Award (DECRA; DE220101320) .en_US
dc.identifier.doi10.1016/j.trc.2023.104338
dc.identifier.issn0968-090X
dc.identifier.issn1879-2359
dc.identifier.scopus2-s2.0-85171369137en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.trc.2023.104338
dc.identifier.urihttps://hdl.handle.net/20.500.14551/22256
dc.identifier.volume156en_US
dc.identifier.wosWOS:001081770400001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofTransportation Research Part C-Emerging Technologiesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMacroscopic Fundamental Diagramen_US
dc.subjectModel Predictive Controlen_US
dc.subjectLarge-Scale Urban Road Networksen_US
dc.subjectAverage Speed Controlen_US
dc.subjectTraffic Perimeter Controlen_US
dc.subjectMacroscopic Fundamental Diagramsen_US
dc.subjectPerimeter Controlen_US
dc.subjectHeterogeneous Networksen_US
dc.subjectTraffic Controlen_US
dc.subjectFlow-Controlen_US
dc.subjectEquilibriumen_US
dc.subjectCongestionen_US
dc.subjectAlgorithmen_US
dc.subjectLimitsen_US
dc.titleNonlinear model predictive control of large-scale urban road networks via average speed controlen_US
dc.typeArticleen_US

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