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dc.contributor.authorSalman, Muntaser A.-
dc.contributor.authorOzdemir, Suat-
dc.contributor.authorCelebi, Fatih V.-
dc.date.accessioned2022-10-20T16:38:16Z-
dc.date.available2022-10-20T16:38:16Z-
dc.date.issued2018-01-27-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/4048-
dc.description.abstractTraffic signal control (TSC) with vehicle-to everything (V2X) communication can be a very efficient solution to traffic congestion problem. Ratio of vehicles equipped with V2X communication capability in the traffic to the total number of vehicles (called penetration rate PR) is still low, thus V2X based TSC systems need to be supported by some other mechanisms. PR is the major factor that affects the quality of TSC process along with the evaluation interval. Quality of the TSC in each direction is a function of overall TSC quality of an intersection. Hence, quality evaluation of each direction should follow the evaluation of the overall intersection. Computational intelligence, more specifically swarm algorithm, has been recently used in this field in a European Framework Program FP7 supported project called COLOMBO. In this paper, using COLOMBO framework, further investigations have been done and two new methodologies using simple and fuzzy logic have been proposed. To evaluate the performance of our proposed methods, a comparison with COLOMBOs approach has been realized. The results reveal that TSC problem can be solved as a logical problem rather than an optimization problem. Performance of the proposed approaches is good enough to be suggested for future work under realistic scenarios even under low PR.en_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.relation.ispartofseriesSensors 2018, 18;368-
dc.subjecttraffic signal controlen_US
dc.subjectV2X communicationen_US
dc.subjectintersectionen_US
dc.subjectfuzzy systemen_US
dc.subjectacceleration and stopped delayen_US
dc.subjecttraffic policyen_US
dc.titleFuzzy Traffic Control with Vehicle-to-Everything Communicationen_US
dc.typeArticleen_US
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