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Using genetic algorithm for traffic light control system with a pedestrian crossing

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dc.citedby25
dc.contributor.authorTurky A.M.en_US
dc.contributor.authorAhmad M.S.en_US
dc.contributor.authorYusoff M.Z.M.en_US
dc.contributor.authorHammad B.T.en_US
dc.contributor.authorid25825717300en_US
dc.contributor.authorid7402895985en_US
dc.contributor.authorid22636590200en_US
dc.contributor.authorid57193327622en_US
dc.date.accessioned2023-12-29T07:55:06Z
dc.date.available2023-12-29T07:55:06Z
dc.date.issued2009
dc.description.abstractIn this paper, we explore the use of genetic algorithm and implementing the technology to improve the performance of traffic light and pedestrian crossing control in a four-way, two-lane traffic junction. The algorithm resolves the limitations of traditional fixed-time control for passing vehicles and pedestrians. It employs a dynamic system to control the traffic light and pedestrian crossing that monitors two sets of parameters: the vehicle and pedestrian queues behind a red light and the number of vehicles and pedestrians that passes through a green light. The algorithm dynamically optimizes the red and green times to control the flow of both the vehicles and the pedestrians. Performance comparisons between the genetic algorithm controller and a fixed-time controller reveal that the genetic algorithm controller performs significantly better. � 2009 Springer Berlin Heidelberg.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/978-3-642-02962-2_65
dc.identifier.epage519
dc.identifier.scopus2-s2.0-69049111101
dc.identifier.spage512
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-69049111101&doi=10.1007%2f978-3-642-02962-2_65&partnerID=40&md5=576f90f235b915b0cf0993d25b3a891c
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/30873
dc.identifier.volume5589 LNAI
dc.pagecount7
dc.sourceScopus
dc.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.subjectCellular Automata
dc.subjectGenetic Algorithm
dc.subjectTraffic Control Systems
dc.subjectCellular automata
dc.subjectControl system analysis
dc.subjectControl systems
dc.subjectControllers
dc.subjectCrossings (pipe and cable)
dc.subjectDynamical systems
dc.subjectFootbridges
dc.subjectFuzzy sets
dc.subjectGenetic algorithms
dc.subjectLight transmission
dc.subjectPattern recognition systems
dc.subjectPedestrian safety
dc.subjectRough set theory
dc.subjectTraffic control
dc.subjectTranslation (languages)
dc.subjectVehicles
dc.subjectDynamic Systems
dc.subjectGreen light
dc.subjectNumber of vehicles
dc.subjectPedestrian crossing
dc.subjectPerformance comparison
dc.subjectRed light
dc.subjectTime control
dc.subjectTime controller
dc.subjectTraffic light
dc.subjectTraffic light control systems
dc.subjectTwo-lane traffic
dc.subjectGenetic engineering
dc.titleUsing genetic algorithm for traffic light control system with a pedestrian crossingen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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