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1、外文文献翻译IntelligentTrafficLightControlMarcoWiering,JellevanVeenen,JillesVreeken,andArneKoopmanIntelligentSystemsGroupInstituteofInformationandComputingSciencesUtrechtUniversityPadualaan14,3508TBUtrecht,TheNetherlandsAbstractVehiculartravelisincreasingthroughoutthewo
2、rld,particularlyinlargeurbanareas.Thereforetheneedarisesforsimulatingandoptimizingtrafficcontrolalgorithmstobetteraccommodatethisincreasingdemand.Inthispaperwestudythesimulationandoptimizationoftrafficlightcontrollersinacityandpresentanadaptiveoptimizationalgorith
3、mbasedonreinforcementlearning.Wehaveimplementedatrafficlightsimulator,GreenLightDistrict,thatallowsustoexperimentwithdifferentinfrastructuresandtocomparedifferenttrafficlightcontrollers.Experimentalresultsindicatethatouradaptivetrafficlightcontrollersoutperformoth
4、erfixedcontrollersonallstudiedinfrastructures.Keywords:IntelligentTrafficLightControl,ReinforcementLearning,Multi-AgentSystems(MAS),SmartInfrastructures,TransportationResearch1IntroductionTransportationresearchhasthegoaltooptimizetransportationflowofpeopleandgoods
5、.Asthenumberofroadusersconstantlyincreases,andresourcesprovidedbycurrentinfrastructuresarelimited,intelligentcontroloftrafficwillbecomeaveryimportantissueinthefuture.However,somelimitationstotheusageofintelligenttrafficcontrolexist.Avoidingtrafficjamsforexampleist
6、houghttobebeneficialtobothenvironmentandeconomy,butimprovedtraffic-flowmayalsoleadtoanincreaseindemand[Levinson,2003].Thereareseveralmodelsfortrafficsimulation.Inourresearchwefocusonmicroscopicmodelsthatmodelthebehaviorofindividualvehicles,andtherebycansimulatedyn
7、amicsofgroupsofvehicles.Researchhasshownthatsuchmodelsyieldrealisticbehavior[NagelandSchreckenberg,1992,WahleandSchreckenberg,2001].Carsinurbantrafficcanexperiencelongtraveltimesduetoinefficienttrafficlightcontrol.Optimalcontroloftrafficlightsusingsophisticatedsen
8、sorsandintelligentoptimizationalgorithmsmightthereforebeverybeneficial.Optimizationoftrafficlightswitchingincreasesroadcapacityandtrafficflow,andcanprev
