Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6134
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dc.contributor.authorAksaç, Alper-
dc.contributor.authorUzun, Erkam-
dc.contributor.authorÖzyer, Tansel-
dc.date.accessioned2021-09-11T15:35:02Z-
dc.date.available2021-09-11T15:35:02Z-
dc.date.issued2012en_US
dc.identifier.issn0924-669X-
dc.identifier.issn1573-7497-
dc.identifier.urihttps://doi.org/10.1007/s10489-011-0290-3-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6134-
dc.description.abstractTraffic lights are installed at intersections mostly for traffic management. Traffic signals turn on during the amount of time determined. Intelligent traffic management systems emerge as a need to handle the dynamicity of traffic. These systems are first implemented on simulators in order to mimic the real life situations before realization. Yet, we have implemented a real time traffic simulator with an adaptive fuzzy inference algorithm that arranges the foreseen light signal duration. It changes the time duration of lights depending on waiting vehicles behind green and red lights at crossroad. The simulation has also been supported with real time graphical visualization. Given a scenario, it creates random traffic flows according to specified parameters. Next, obtained results have been interpreted in the simulation environment. According to inferences from adaptive environment, TSK (Takagi-Sugeno-Kang) and Mamdani models have also been implemented to give baselines for verification. Several experiments have been conducted and compared against classical techniques such as Webster (1958) Road research technical paper No 39 and HCM (2000) TRB, special report 209, statistically to demonstrate the effectiveness of the proposed method.en_US
dc.description.sponsorshipTUBITAK-Scientific and Technical Research Council of TurkeyTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [EEEAG 109E241]en_US
dc.description.sponsorshipThis study was supported by TUBITAK-Scientific and Technical Research Council of Turkey (Grant number EEEAG 109E241). We would like to thank anonymous referees for their insightful comments. In addition, we would like to thank Akif Barbak for his effort at the early stage of implementation.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofApplied Intelligenceen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectTraffic managementen_US
dc.subjectAdaptive fuzzy inference mechanismen_US
dc.subjectFuzzy ruleen_US
dc.subjectFuzzy setsen_US
dc.subjectTraffic signal systemen_US
dc.titleA real time traffic simulator utilizing an adaptive fuzzy inference mechanism by tuning fuzzy parametersen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.identifier.volume36en_US
dc.identifier.issue3en_US
dc.identifier.startpage698en_US
dc.identifier.endpage720en_US
dc.authorid0000-0001-5185-7723-
dc.identifier.wosWOS:000303479800013en_US
dc.identifier.scopus2-s2.0-84862129583en_US
dc.institutionauthorÖzyer, Tansel-
dc.identifier.doi10.1007/s10489-011-0290-3-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.cerifentitytypePublications-
item.languageiso639-1en-
crisitem.author.dept02.1. Department of Artificial Intelligence Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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