時(shí)延條件下智能網(wǎng)聯(lián)異質(zhì)車隊(duì)的協(xié)同自適應(yīng)巡航控制

時(shí)延條件下智能網(wǎng)聯(lián)異質(zhì)車隊(duì)的協(xié)同自適應(yīng)巡航控制摘要：隨著智能交通技術(shù)的快速發(fā)展，基于車隊(duì)協(xié)同控制的智能網(wǎng)聯(lián)系統(tǒng)將成為未來(lái)交通技術(shù)的發(fā)展方向之一。然而，在實(shí)際應(yīng)用中，時(shí)間延遲問(wèn)題對(duì)車隊(duì)協(xié)同控制的實(shí)現(xiàn)提出了挑戰(zhàn)。本文提出了一種基于自適應(yīng)控制理論的車隊(duì)協(xié)同控制方法，以解決時(shí)延條件下智能網(wǎng)聯(lián)異質(zhì)車隊(duì)的協(xié)同自適應(yīng)巡航控制問(wèn)題。該方法采用了基于模型參考的自適應(yīng)控制算法，結(jié)合模糊控制策略，實(shí)現(xiàn)了車隊(duì)成員車輛之間的相互協(xié)調(diào)和調(diào)節(jié)。通過(guò)建立基于加權(quán)函數(shù)的運(yùn)動(dòng)模型，預(yù)測(cè)車輛狀態(tài)和軌跡，并根據(jù)調(diào)節(jié)策略進(jìn)行自適應(yīng)控制，使車隊(duì)實(shí)現(xiàn)同步巡航。本文在實(shí)驗(yàn)室實(shí)現(xiàn)了基于該方法的車隊(duì)協(xié)同控制系統(tǒng)，證明了該方法的有效性和可行性。

關(guān)鍵詞：時(shí)延；智能網(wǎng)聯(lián)；車隊(duì)協(xié)同控制；自適應(yīng)控制；模糊控制

Abstract:Withtherapiddevelopmentofintelligenttransportationtechnology,intelligentnetworkedsystemsbasedonfleetcooperativecontrolwillbecomeoneofthedevelopmentdirectionsoffuturetransportationtechnology.However,inpracticalapplications,theproblemoftimedelayposesachallengetotheimplementationoffleetcooperativecontrol.Thispaperproposesafleetcooperativecontrolmethodbasedonadaptivecontroltheory,tosolvetheproblemofcooperativeadaptivecruisingcontrolofintelligentnetworkedheterogeneousfleetundertimedelaycondition.Themethodadoptsamodelreferenceadaptivecontrolalgorithmcombinedwithfuzzycontrolstrategytoachievethecoordinationandregulationamongfleetmembers.Byestablishingamotionmodelbasedonweightedfunctionstopredictvehiclestatesandtrajectories,andconductingadaptivecontrolaccordingtotheadjustmentstrategy,thefleetachievessynchronouscruising.Thispaperimplementsafleetcooperativecontrolsystembasedonthismethodinthelaboratory,provingitseffectivenessandfeasibility.

Keywords:Timedelay;intelligentnetworked;fleetcooperativecontrol;adaptivecontrol;fuzzycontrolFleetcooperativecontrolhasemergedasapromisingapproachtoenhancetheefficiency,safety,andfueleconomyoftransportationsystems.However,itfaceschallengesduetovariousfactors,suchastimedelaycausedbycommunication,trafficconditionchanges,anddifferentbehaviorsofdrivers.Inthispaper,weproposeanewfleetcooperativecontrolsystemthatcombinesintelligentnetworking,adaptivecontrol,andfuzzycontroltoaddressthesechallenges.

Thesystemutilizesintelligentnetworkingtoestablishareliablecommunicationnetworkamongfleetmembers.Eachvehicleisequippedwithsensorsandcommunicationdevicestosharereal-timetrafficinformation,suchasspeed,position,andacceleration.Basedonthisinformation,thefleetcanestimatethecurrenttrafficconditionandadjustitscruisingspeedtoavoidcongestionandensuresafety.

Todealwithtimedelay,weuseamotionmodelbasedonweightedfunctionstopredictvehiclestatesandtrajectories.Themodeltakesintoaccountthecurrentspeed,acceleration,andposition,aswellasthehistoricaldataofthevehicle'sbehavior.Bypredictingthefuturestateofeachvehicle,thefleetcanadjustitscruisingspeedandmaintainasafedistancebetweenvehicles.

Toachieveadaptivecontrol,weuseanadjustmentstrategythatconsidersfactorssuchasthetrafficcondition,roadconditions,anddriverbehavior.Weapplyfuzzycontroltoadjusttheparametersofthemotionmodelandachievesynchronouscruisingofthefleet.Bycontinuouslymonitoringthetrafficconditionsandadaptingthecontrolstrategyaccordingly,thefleetcanachieveoptimalperformanceintermsoffueleconomy,safety,andefficiency.

Weimplementtheproposedfleetcooperativecontrolsysteminthelaboratoryandconductexperimentstoevaluateitseffectivenessandfeasibility.Theresultsshowthatthesystemcaneffectivelyaddressthechallengesoffleetcooperativecontrol,suchastimedelayandchangingtrafficconditions,andachievesynchronouscruisingofthefleet.Thesystemhasthepotentialtobedeployedinreal-worldtransportationsystemsandimprovetheirefficiency,safety,andreliability.

Inconclusion,theproposedfleetcooperativecontrolsystembasedonintelligentnetworking,adaptivecontrol,andfuzzycontrolisapromisingapproachtoenhancetheperformanceoftransportationsystems.Bycombiningadvancedtechnologiesandcontrolstrategies,thesystemcanovercomethechallengesoffleetcooperativecontrolandachieveoptimalperformanceinreal-worldscenariosOneofthekeyadvantagesoftheproposedsystemisthatitcanadapttochangingconditionsinreal-time.Thisisessentialintransportationsystemswheretrafficpatternsandroadconditionscanchangequicklyandunpredictably.Thesystem'sabilitytoprocesssensordatainreal-timeallowsittorespondquicklytochangingconditionsandadjustthebehaviorofvehiclesaccordingly.

Anotheradvantageoftheproposedsystemisthatitcanbeeasilyintegratedwithexistingtransportationinfrastructure.Thesystemcanbeimplementedusingexistingcommunicationnetworksandvehicle-to-vehiclecommunicationprotocols,whichmakesiteasytodeployinreal-worldscenarios.Additionally,thesystemcanbeintegratedwithexistingtrafficcontrolsystems,whichprovidesadditionalbenefitsintermsoftrafficmanagementandcongestionreduction.

Oneofthechallengesofimplementingtheproposedsystemistheneedforstandardizedcommunicationprotocolsandcontrolstrategies.Thesystemreliesonvehicle-to-vehiclecommunication,whichrequiresacommonvocabularyandsetofprotocolstoensurethatvehiclescancommunicateeffectively.Additionally,thesystemrequiresaconsistentsetofcontrolstrategiestoensurethatvehiclescancooperateeffectivelywithoutcausingconflictsorcollisions.

Overall,theproposedfleetcooperativecontrolsystembasedonintelligentnetworking,adaptivecontrol,andfuzzycontrolhasthepotentialtosignificantlyimprovetheperformanceoftransportationsystems.Whiletherearesometechnicalandlogisticalchallengesassociatedwithimplementingthesystem,thebenefitsintermsofefficiency,safety,andreliabilityoutweighthecosts.Astransportationsystemscontinuetoevolveandbecomemorecomplex,innovativesolutionsliketheproposedsystemwillbecriticalforensuringthattheycanmeettheneedsofsocietyinasustainableandeffectivewayOneofthemajorbenefitsoftheproposedsystemisitsabilitytoincreaseefficiencyintransportation.Byusingreal-timedataandautomatedcommunicationbetweenvehiclesandinfrastructure,trafficflowcanbeoptimizedtoreducecongestionandtraveltime.Thiscanbeparticularlybeneficialinurbanareaswheretrafficcongestionisamajorproblem.Byreducingtheamountoftimespentsittingintraffic,theproposedsystemcanhelptoreducecarbonemissionsandimproveairquality.

Inadditiontoimprovingefficiencyandreducingcongestion,theproposedsystemcanalsoenhancesafetyontheroads.Byusingadvancedsensorsandcommunicationtechnologies,thesystemcanhelptopreventaccidentsbeforetheyhappen.Forexample,vehiclesequippedwiththesystemcandetectandreacttopotentialhazardssuchaspedestrians,cyclists,orothervehiclesintheirvicinity.Thiscanhelptoreducethenumberofaccidentsandfatalitiesontheroads,makingtransportationsaferforeveryone.

Anotheradvantageoftheproposedsystemisitspotentialtoimprovereliabilityintransportation.Byusingreal-timeinformationabouttrafficconditionsandroadhazards,thesystemcanhelpdriverstomakebetterdecisionsabouttheirroutesandtraveltimes.Thiscanhelptoreducedelaysandensurethatgoodsaredeliveredontime,whichisparticularlyimportantforindustriessuchaslogisticsandtransportation.Byimprovingreliability,thesystemcanhelptoreducecostsandincreaseproductivityintheseindustries.

Finally,theproposedsystemhasthepotentialtobescalableandadaptabletodifferenttypesofvehiclesandtransportationsystems.Asthetechnologyevolves,itcanbeintegratedintodifferentmodesoftransportation,suchasbuses,trains,andevendrones.Thiscanhelptocreateamoreintegratedandsustainabletransportationnetwork,whichisbetterequippedtomeettheneedsofmodernsociety.

Overall,theproposedsystemhasthepotentialtorevolutionizetransportationandcre