DOC

Research_0 (2)

By Brent Hunt,2014-07-18 23:32
8 views 0
Research_0 (2)Resear

    Research

    .()ur,lnfofHarbinlnstituteofTech,lfJ1ogY(NewSeries),Vo1.12,No.3,2005 ;Researchontrafficcongestionmechanismandcountermeasures

    ;basedondynamictrafficassignment

    ;PEIn,一long.L4,vGshltn

    ;裴玉龙,郎益顺

    ;(InstituteofTranspofiationResearch.HarbinInstituteofTeehnolugy,Harbin150090,China) ;Abstract:Trafficcongestioniswidelydist,‟ibutedaroundanetwork.Generally,toanalyzetraffi(congestion,

    ;staftctramccapacitvisadopted.Butdynamiceharacterisff.csmustbestudiedbecausecongestionisadynamic

    ;process.ADvnamicTrafficAssignmentmodelingfundamentalcombinedwithanurbancongestionanalysis

    ;metho(1isstudiedinthispaper.rhreemethodsarebasedoncongestionanalysis.andthesic(hasti(-USel‟o

    pti

    ;realD.‟1Amodelsareespeciallyconsidered.Correspondingly.adynamicsystemoptimalmodelissuggestedfol

    ;respondingcongestioneounternleasuresandanidealuseroptlnmlmodelforpredi(„tedcongestioncnItutel‟llle~lsnl‟e

    ;respectively.

    ;Keywords:dynamictrafficassignment;trafficcongestion;dynamicUSel‟optimal;dynami(„systemoptimal

    ;CLCnumber:U49lDocumentcode:AArticleID:10059l13(2005)034)2354)4

    ;Tramccongestiongreatlyinfluem‟escitydevelop—

    ;mentandactivityefficiencv.Itseriouslyinterfereswith

    ;theresidents‟workan(1lire.Toundel?standthelawof

    ;trafficcongestion.twocausesshouh1I)econsidered.

    ;Firstcauseoftrafficcongestionisirrationalplanningof

    ;thecityanditsroad‟snetwork.Improperfacilityusage

    ;withdeficientcapacityaccompaniedwithunbalanced

    ;flowdistributioncausessomefacilities‟tosupersatu—

    ;rate.AlsounsuitableTMC(Trafficnlanagementand

    ;contro1)strategy,notmeetingthedemandof”Static

    ;Management”and”DynamicControl”.1cadstoiJJ

    ;trafficstructureandwasteoftimeandspaceresources.

    ;Settingnewtrafficfacilitiesisverydiffi(uhinthecity

    ;becauseofaccountingforurbanareausage,compact

    ;layout.humanityan(1landscapes.Newfacilities‟plan—

    ;ningisalongtennactionandthereforeisnotableto

    ;repaircurrenttrafficcrisis.ComparativelyTMCstrategy

    ;ismoreflexibleandadaptedtodynamictramc.Thedy ;namictrafficnetworkandTDM(trafficdemandman

    ;agement)method,aswellasthecorrespondingTRG ;(trafficrouteguidance)system,havethepriorit)of ;tramflowoptimalityintheshot/tel?Il1.

    ;Thegeneralcongestionanalysismethodsare}rased ;onHCMornetworkcapacityconcepts..Thereforethe ;definitionof”traffic(?(ingestion”isina(?eordaneewith

    ;theserviceleve1.whichisgeneralb,rstati(?andrelated ;tothefacilities.Tlie(„ongcstionisl,e(?ausethestatic

    ;trafficdemandsexceedthefac/lities‟servicecapacity

    ;andflowwhenthevreachinstahiIitv.Inthismetho(1. ;facilitiesaretheanalysisitems.l‟heI”acilitvusei?sbe—

    ;haviorandrea(?tionareignm?e(1(vellItthe(?apa(?ifv ;Recei~(12003()407

    ;simulationmethod.So.evelltheI)estTMCfun(tamen

    ;talsareiBefficientbygeneralHCMOl?networkcapacity ;analysis.especiallyfol‟real—timeusage.

    ;TheDTAfdynamictrafficassignment)metho(1is ;themainmethodofdynamietram(networkanalysis. ;BecausetheATMS/ATISconceptisrealtimetrafficin

    ;formationserviceandTMCimplemente(1.thedynamic ;trafficmodeliStheonlychoice.ThereforetheDTAis ;greatlyemphasized.Thenewtransportationplanning ;theoryisbeingdevelopedintheUSAImsedonthe ;DTA.

    ;Comparedtothestaticmode1.theDTArelieson ;itsdynamicfacets.Thestaticmodel(?0neption.while ;networkstructureisadeterminate.resultsinadefinite ;necksectionwithcongestionoccurring.TheDTAlnod

    ;elanalyzescongestioninthreemethods.TheDfA ;modelhasalsoenabledcongesti(mmanagementby ;modeling.whichwillI)ediscussedlater.

    ;1TrafficCongestionMechanisimAnalysis

    ;rheDTAmodelingmetho(1analyzestt?afficconges ;tioninthreeways,traffiload,I/0(input/output)of ;theintersection.an(1intportantroutesele(?tion. ;1.1TrafficLoadandSectionCongestion

    ;Thetrafficlca(1consistsofalltheexistingvehi(?les ;ahmgastudiedsecti(,nCongestionhappenswhelltllP ;trafficloa(1exceedsthemaximum[)ermitte(1loa(1.AlSO. ;stochasticdisturbance.SU(?hasatraffi(?a(?(?identwhich ;resuhsinabnommlfraffi(?Ilowleadingto(„ongesti()nor

    ;oversaturation,canbea(„auseot‟set?tion(„ongestion.

;?

    ;235?

    ;

    ;JournalofHarbinInstituteofTechnology(NewSeries),Vo1.12,No.3,2005

    ;Trafficcongestioncausedbyaccidentsshould ;lyzedbvtrafficsimulationmodels‟.suchas

    ;(Input/Output)mode1.Theassignmentphase ;bythecongestionanalyzingmodelis:

    ;Q(t)=,(t)x(t)Vt,

    ;beana.

    ;theI/O

    ;inferred

    ;whereQ(t)istrafficload,,(t)andX(t)areinput ;outputtrafficvolumerespectively(asshowninFig. ;一一一一一一

    ;Q(一一一一一.

    ;X(t)

    ;Fig.1IllustrationofI/otrafficflowmodel ;(1)

    ;and

    ;1).

    ;ThefuInctionreferstothetrafficflowattimete. ;qualtothedifferencebetweeninputandoutputflow. ;Thishappensonthesuppositionthatthesectionisa ;closedsystem.Thissituationmaybedescribedasa ;strictclosedsystemwithnonewtraffic.Italsomatches ;thestatictrafficstateasweanalyzethenetworkonthe ;suppositionofinputandoutputflowequalitythereby ;ignoringtheformofthetrafficassignmentmode1.How

    ;everthisisincorrect.asweanalyzethenetworkbythe ;dynamictrafficmodel,thatisIVOimbalance:Q(t) ;o.evenintheformofdiscretetimemode1.Firstthis ;expressesthedifferencebetweendynamicandstatica. ;nalysis,andsecondthisshowsthecontrollablefactorof ;inputandoutputflowunderthedynamictrafficmode1. ;1.2I/ofinput/output)FlowandCongestion ;Normally.congestionwillnotoccurinthesitua. ;tionwheretheinputflowislessthanoutputflow.The ;vehicleflowentersthesectionwithvelocityV,andits ;outputflowequalstheinputflow,sothepossibilityof ;congestionislimited.Becausetheinput/outputrestric

    ;tionofurbantrafficismostlycausedbyoutput,weon. ;1yconsideroutputflowhere.Thetraveltimeofthedy. ;namictrafficnetworkisnotonlyrelatedtosection

    ;load.butalsorelatedtoinputandoutputflow.Itis ;notnecessarytodefineroutetrafficstatebyasingle ;section.RothrockandKeeferhaveresearchedtravel ;time.flowrelationbyobservation.Theyfoundthat ;smalltrafficflowsandlongtraveltimealsoconcur ;whentakingshortobservationintervals.Ifwedefine ;congestionastimeconsummation,wemaybuildthe ;followingfunction:

    ;Ts(t)=F.{Q(t)}+F:{I(t),X(t)}or

    ;Ts(t)=F{Q(t)}+F2{I(t))}+F3:X(t)),(2)

    ;whereF1denotessectiontraveltime,F,andF1denote ;intersectiondelays.

    ;Thethreeelementsarethecausesofcongestion. ;Sectiontravelisthedirectcauseandtheintersectionis ;theindirectcause.Wealsocananalyzethetrafficflow ;bydividingtraveltimeintotwoparts:sectionandin

    ;tersectiontraveltimedrespectivelytoexpresstrafficdy. ;?

    ;236?

    ;namiccharacteristies.

    ;Theoccurrenceofcongestiononsectiontravelis ;relatedtotheheavytrafficnetwork.Whentheloadof ;roadtramcisuptothemaximumtolerance.congestion ;willhappen.Thecongestiondistributionoflocation ;andtimeonadayisbasicallyfixed.Congestioncaused ;byanintersectiondelayhasregularfactorsandstochas. ;ticfactors:theregulationisthesamewiththeregula

    ;tionofthesection:therandomnessisbecauseofdense ;confictpoints.Ifthetrafficconflictcausessecond ;stopsoratrafficaccident,congestionmayhappen.If ;thelevelofintersectionmanagementisadvanced.this ;typeofcongestioncanbeavoidedandthedispersingof ;thecongestionwillbefaster.Thecongestioncausedby ;anintersectioncapacitydeficitwilllengthenthevehicle ;queue.andwillevencausetrafficflowtobackupmore ;andmore.Thistypeofcongestioncanonlybesolved ;bychangingtheroute.Therea1.timeinformationof ;trafficaccidentsandtramccongestionisusuallybroad

    ;castthroughFMradioindomesticcities.Thesecities ;haveemphasizedtheadoptionofTRG(TrafficRoute ;Guiding)systemsandVMS(VaryingMessageSys

    ;tems).

    ;1.3RouteSelectionandCongestion

    ;Trafficcongestionrevealstheactualtramcflow

    ;distribution.Aself-decisionandexperience--efiectar. ;chitectureareformedinthetripperwithoutthesystem ;strategyimpact:asthetrippercan‟treachthecoordi—

    ;nationstatewithoutthesystemprescription.Theva. ;chieverouteselectionbyself-decisionorexperience. ;effectaccordingtoadjacentnetworkload.Thismotion ;ismostusers‟decisionandkeepstothesecondWard.

    ;ropdiscipline.Whentoomanyusersselecttheroute. ;congestionoccurs.Sotheusers‟routeselectionshould

    ;bethekeycauseofformingcongestionandthemain ;factorthataffectsflowtime.spacedistribution. ;Wewouldliketoadopttheroutetimeasanele. ;mentinbuildingtrafficmodels.Theuseroptimizing

    ;modelhastwofoITI1S:

    ;1)InstantaneousUserOptimizingTime:Thetrip

    ;perswhohavethesamedestinationselecttherouteac. ;cordingtotheshortesttimeaftertheirstart.andthisis ;calledInstantaneousUserOptimizingstate.Wecana1. ;soexplainthistobethattheusersselecttheirroutes ;accordingtoInstantaneousnetworkload.

    ;2)ActualUserOptimizingTime:Thetripperswho ;havethesamedestinationselecttherouteaccordingto ;theshortesttimebeforetheyactuallyarriveattheir ;destination.Wedefinethetimeasactualuseroptimi. ;zingtime.

    ;Actually,mosttrippers‟decisionoftheirroute

    ;selectionisaccordingtothefirsttimestandard.Wea1. ;socansupposethatthetrippers‟decisionfitsforthe

    ;secondtimestandard.Butasweconsidertheeffectof ;thedifferenceofthetrippers‟estimatedtime.itisran.

    ;

    ;JournalofHarbinInstituteofTechnology(NewSeries),Vo1.12,No.3,2005

    ;domorwecallitstochasticdistributioninmodeling.In ;consideringthis.wemayusethestochasticmodelin ;ouranalysis.

    ;Asthenetworklcadisnorma1.thedifferencebe

    ;tweenthetwotypesoftimeshouldbesmal1.Otherwise ;thedifferencewillbecomedistinctasthenetworklcad ;becomesheavyorabnorma1.Itisbecausethisdistinct ;differencecausesthenetworkcongestion.Weusethe ;assignmentmodeltoillustratethetramcnetworklcad: ;rainf(Q,,,x)dw,|,x,e.EJFTd,?Jo

    ;T:y(Q,,,)denotesstochastictraveltimeestimation ;forODpairwhentakingrouter.Generallytheestima

    ;tionvaluehasanexpectation,andifwecandecidethe ;routeselectionrate,thentheODpairusingrouterat ;timetissettledby:

    ;(t)=f(t)?P(t),(4)

    ;whereZ(t)isanODpairthatselectsrouterattimet. ;p~r(t)istheselectionprobabilityofrouterbythe ;same0Dattimet.

    ;po(t)asthevalueisconfirmed.theotheranaly

    ;siselementscanbecalculatedinthesamewaywiththe ;determinateuseroptimizingassignmentmode1. ;2ApplicationofDynamicTrafficAssignmentin ;TrafficCongestionCountermeasure

    ;Besidesusingtheapplicationinanalyzingtraffic ;congestionasthemainmethodofanalyzingdynamic ;trcnetwork.thedynamictramcassignmentroodelis ;alsoresearchedintheestablishmentofcongestion ;countermeasures.

    ;Thecountermeasureofanurbantrafficnetworkis ;dividedintotwotypes:theresponsemodelandthe ;forecastmode1.Thesetwomodelsareusuallycombined ;inurbantrafficnetworks.Nextwewilldefinethesetwo ;modelsanddiscussthedynamicassignmentmode1. ;2.1ResponseCongestionCountermeasurewith ;CongestionChargeandDSOAssignment

    ;Theresponsecongestioncountermeasurelooksat ;theareathathashighfrequentcongestionorhasheavv ;congestion.Thistypeofcountermeasureiswidelva

    ;dopted.Themainpracticaltechniqueofcountermeas

    ;ureiscongestioncharge.Thistechniqueisbasedon

    ;trafficmanagement,dependingonthedegreeofcon

    ;gestion,expectingtooptimizethetrafficsysteminthe ;directlyimpactedarea.whosemaintheorybasisisthe ;dynamicsystemoptimumassignmentmode1.

    ;Sincecostisusedasafactortoadjustthedistri

    ;butionoftramcflow.theobjectfunctionmustbetrans

    ;formedintoacostform,namelytotransformtraveltime ;ordelayintocost.Aftertakingthesystemoptimumas

    ;signment,wecanacquirethetramccostintheopti

    ;mizedsystem.Referringtothecostinthecongestion ;system,wecandeterminethetaxrate.TheobjectiSto ;reducefrequentfacilityusagethroughtaxandtoadjust ;thesystemstate.Thechargerateshouhlbechanged ;accordingtotime,soitisnecessarytousethedynamic ;assignmentmode1.

    ;Themathematiccostformulaforoptimizingthe ;objectfunctionconsideringtaxiSlistedbelow: ;Cs(t)=s+[Ts(t)+(t)],(5)

    ;Hereo/isafixedcost,melythecostofsectionsunder ;thesituationoffreeflow;isthetime(?()sttransform ;rate,whichisindependentoftime;T(t)isthediffer

    ;enceofinstantaneoususeroptimumassignmentand ;systemoptimumassignment,sodynamicsystemopti

    ;mumassignmentiscarrie(1outtwice.Thefirstistode

    ;termines(t)throughthesystemassignment,these(.

    ;ondistodeterminethesmallesttotalcostthroughthe ;dynamicsystemoptimumtrafficassignment,all(]use ;thesetwotodeterminetheaveragetaxrate. ;2.2ForecastingCongestionCountermeasurewith ;TrafficGuidingandForecastingDUoAs?

    ;signment

    ;Themoreemcientmanagementmethodtosolxe ;citytrafficcongestionisadoptingaDriverRouteGuM

    ;ingSystem(DRG).DRGisthroughobservingand ;forecastingthetimeandthelocationofcongestion)?

    ;currence,offeringtheoptimumrouteandtriptimeto ;thetripper,whoseobjectistodispersecongestionand ;toimprovetheefficiencyofthetraf6s,rstem..DRG ;isanadvancedtramcmanagementmethodan(1the ;mainpartofATMS/ATIS.Trafficguiding.especially ;theguidingofspecialvehiclesisadoptedwidelyallo

    ;vertheworld.FMforecastingisitsprima~status.an(1 ;moreadvancedstatusesarebasedonGPS.vehi(.1ecar

    ;riedsystemsandelectronicinformation.whichiswidP

    ;lyusedinciviltrafficsystemsabroad.TakingthPad

    ;vantageoftrafficguiding,manyvehi(„lemanufa(?turers

    ;andtransportationorganizationsstrengthentheirre

    ;searchprograms.suchastheJapaneseToyotaandUS ;GMcorporations.

    ;Theforecastingcongestioncountermeasureisfo

    ;cusedonrealtimeinformationcollectionanddisposa1. ;forecastingthetramcflowdistributionintervals.and ;determiningthelocationandtimethatcongestionwill ;occur.Moreover,throughoptimumassignmentofthe ;usersactualtraveltime,suggestingtheusersadopted ;routeandacquiringtheminimumtraveltime.this ;countermeasureisconsideredasanloreadvan(?e(1con

    ;gestioncountermeasuremode1.an(1t?andispersethe ;congestion.Becausetraveltimeisatorecastedindex.

    ;theforecastingDUOassignmentmodelisadopted. ;Thetraveltimeoffi)recastingtheDU0assignment ;isf1)recastedorusestheactua1trave1time.whichis ;differentfromtheDSOassignment.Inthefore(„dsting

    ;DUOassignmentmode1.supposingthattheUSCl‟Sae—

    ;tualtraveltimeonaselectedrouteismat(hedtothe ;?

    ;237?

    ;

    ;JournalofHarbinInstituteTechnology(NewSeries),Vo1.12,No.3,2005

    ;forecastedtime.notcurrenttrafficdistribution,moreo

    ;vertheuserscanacquireeachminimumtraveltime ;throughacorrespondingtriproute.Theforecastedmin

    ;imumtraveltimemayberevealedwiththerecursivee

    ;quationbelow:

    ;(t)=(t)+[t+(t)],(6)

    ;where(t)denotesactualtraveltimefromstartpoint ;tosectioniattimet:ll‟(t)denotesactualtravel

    ;timefromstartpointtosection,一lattimet;77lt+

    ;“(t)]isactualtraveltimeonsectiona.

    ;Theobjectofrouteguidingistomakealltrippers ;achievetheactualDUOstatus.Theprincipleofroute ;selectionalsocanbedefinedasbelow:ToallODpairs ;thathavethesamedestination,onanytime,thetravel ;timeequalstotheshortestpredictedtimefornodesa

    ;longtheselectedroute.Wecallthistypeofflowdistri

    ;butionasadynamicuseroptimizingstatebasedonroad ;section.Thedefinitionisthemainprincipleofdynamic ;trafficguiding.

    ;3ExperimentofSmallRoadNetwork

    ;Asmallroadnetwork

    ;,

    ;isdesignedwithtwelveroad

    ;sectionsandninenodes(asshowninFig.2).The ;dynamictrafficassignmentoftwoOD‟sonseven

    ;periodsoftimeislisted(asshowninTab.1).Inthe ;assignment,itisassumedthattheinitialtrafficloadof ;eachroadsectioniszero.all(1therearefun(?tionsbe

    ;tweenthetraveltimeandtheinputandoutputofthe ;trafficvolume.

    ;Fig.2Smallexperimentnetwork

    ;Tab.1DynamicODtableofeachperiodoftime ;Theassignmentresultissh0wninTat).2.Itanbe

    ;seenfromthetablethat<lynamictraffi<?assignnientisrea

    ;sonableanditisadvantageousforobtainingakey. ;Tab.2RouteassignmentresultsofinstantaneousDUO ;4Conclusion

    ;[3:

    ;Asweallknow,thecausesoftrafficcongestionr.] ;arenotlimitedtothefactorswehavediscussed.0ther ;causesaredeficientparkingspacesandpedestrian ;walkways.aswellasv

Report this document

For any questions or suggestions please email
cust-service@docsford.com