高速公路收费标准制定方法研究

华中科技大学硕士学位论文高速公路收费标准制定方法研究姓名：王雁申请学位级别：硕士专业：管理科学与工程指导教师：李世其;付艳20060401I2080IIAbstractFreewayconstructioninChinawasinitiatedinthelate1980s,butuptonowfreewaytollstandard,ismainlydecidedbysubjectiveexperienceandlackofsciencebasis.Asweknow,onlytollstandardisproperlydesigned,thehighwaycouldattractmoreandmoreconsumerswithitsrapidness,convenienceandhighqualityofservice.Inthatway,theresourceofhighwayalloverthecountrycouldbeusedsufficientlyandbeworthyofitsinvestments.Howtosetareasonableandequitablefreewaytollstandardwiththedomesticrealityandtheoverseas’experience,isanimportantworknow.Notonlytheinteriorandexteriorfactorswhatwouldinfluencethefreewaytollstandardareconsidered,butalsothebasiceconomicprinciple,valueoftimetheoryandtransportationbehaviortheoryaretakenintoaccountwhenwedescribedthefreewaytollstandarddecidingprocess.Thecharacteristicsofbi-levelprogrammingmodelarepresentedatfirst,withthecharacteristiccomparisonofthealgorithmswhichtosolvethosemodels.Thentheconclusionisgivenoutthatbi-levelprogrammingismoresuitablefortheproblemoffreewaytollstandard’sdecidingmethod.Thispaperstudiesthepresentdefectsinthemethodstodeterminethefreewaytollstandard,andfromthepointoftheroadusers,setsupbi-levelprogrammingmodelbasedonvalueoftimeanalysisandproposestheheuristicsolutionalgorithm.Notonlythebenefitsoffreewayinvestors,administersandthecustomersaretakenintoaccountinthismodel,butalsothelimitation,thatonlyconsideronesectionofhighwayandignoretherelationshipofseveralsections’trafficflowwhenweputuptollresearch,isovercome.Atthesametime,asimplifiedheuristicalgorithmwhichcangetapproximateresultsisdesignedwhichneednottocalculatederivative.Thealgorithmmakesupforthelimitationofsensitivityanalysismethodthatisusuallyusedforsolvingbi-levelIIIprogrammingproblem.Atlast,inordertoevaluatefreewaytollstandardmoreaccuratelyandshowthehighway’sgeneralbenefitunderdifferenttollcasesmoredirectly,weintroducethe“simulate”conceptandestablishthehighwayoperationsimulationsystem.Thispapercontainsthedescriptionofthewholeframeofthissystem.Onthebasisofsystem’sprogramming,wecompletethesolutionandanalysismoduleforbi-levelprogrammingmodel.Finally,anactualexampleisgiventoshowthevalidityofthemodelandalgorithmbyapplyingthismodule.Keywords:FreewaytollstandardValueoftimeNetworkbi-levelprogrammingSystemsimulation_____111.1[1]197810373.4km()198820022.5km14,[2]2[3]demandpriceelasticity[4]tollelasticity[5][6][7]31.2[8]12344551.3[9][10]61.3.1FTCTCM+∗+=[11]MCT()TC,/F()[]βαCVtt/10∗+×=[12]t0tV/C/αβ15.0=α4=βWardropUser-Optimized-EquilibriumSystem-Optimized-Equilibrium[13]71.3.2158[14]1.3.3BLABGBLABDNP[15]1.4192NPBLABGBLABD31022.12050Stackelberg60DantzigWolfe70[16]1112[17][18]2.22.2.1[19]P1P1U1min(,)xFxy(2-1)..(,)0stGxy≤(2-2)()YYx=L1min(,)yfxy(2-3)s.t.(,)0gxy≤(2-4)32322211,,:,:,nnnnnnmxEyEFEEEGEEE∈∈∈×→∈×→121221:,:nnnnmfEEEgEEE∈×→∈×→P1U1(2-1)(2-2)L1(2-3)(2-4)x13yxY=Y(x)2.2.2NP-hardBen-AyedBlairJeroslowNP-hard()[20]ExtremePointSearchMethodKarush-Kuhn-TuckerMethodK-TDescentMethodDirectSearchMethod12K-TKarush-Kuhn-Tucker21[21]22[22]143Dempe23[23]24[24][25]4AbdulaalLeBlancHooke-Jeeves51989Anandalingam1996GendreauKT/KimSunduckSuh1989BDA(Bi-levelDescentAlgorithm)MINOS1998,BLABG(Bi-levelLinearApproximationBasedonGradient):15BLABG:2.3BLABG163,,,[26][27][28][29][30-33]173.13.1.1Pc18ft3.1.2VOTζζ()ζ∗++=fctP29VOTVOT1=ζ3.21519100kN25kN)iPinPN25.421100Σ=iiPnCCN(3-1):iP----25kN()kNin----/1C----2C----40%480%13iPinsN2016100Σ=iiisPNNα(3-2):iP----kNiα----1=α3767.051046.1−−×=iiPαiN----/40kN()80kN()40%21860%18453.3[34]3.3.1()ANG,=NA'AG21afaqacaaFaaVaQ1aC2aCaaiPa25KNaNaata-4a()(0)[1+0.15(q/)]aaatqtv=×VOTζ()aaatfG,aP3.3.2aaAaqf∗Σ∈aAaN'∈Σ25.421'100∗∗∗Σ∈aiaaaAaPqCC()25.421100q,fMaxZ'∗∗∗−∗=∑∑∈∈aiaaAaaaAaaPqCCqf(3-3)aaVq0s.t.(3-4)()P,≥∑∈AaaaaqfG(3-5)223.3.3Wardrop()ζ∗++=fctP()()aaAaaAaq0aqcdq(q)tqPMinaζ∗∗++=∑∑∫∈∈af(3-6)QAa=∑∈aqs.t.(3-7)0qa≥(3-8)3.4BLABDBLABG[35-38]Bi-levelLinearApproximationBasedonGradientaq23()abffq∆∆()abffq∂∂BLABGBLABG1aaf∆UEUserEquilibriumaaf∆bbq∆()abffq∂∂()abffq∆∆iif∆j()fqi∆()ijffq∂∂()ijffq∆∆2∗f()∗fq()()()()()***aaffAaaaaaffffqfqfq−∆∆+≈=∈∑(3-9)()24n12niaaf∆UEaaf∆bbq∆()ijffq∂∂()ijffq∆∆n-1n-1UEjjf∆kkq∆k()jkffq∂∂()jkffq∆∆*f*()qfk0a*()aqf()ijffq∆∆39391+kf1max||kkaaffξ+−≤Aξ∀∈ξ1+kfkk131aq253-13.52644.14.1.14-14-14.1.21272API34284.1.34-24-24-3294-34-3[39]304.24.2.14-44-44-44-531NULL4-64-6YXZXZ442DXZYAI32AIU/AI4.2.2AI[40][41]4-63D34-7AINavigationAIRegisterRouteDriveRouteID33RegisterRouteRegisterRouteDriveRouteAI4.2.3[42]4-84-8344.2.44.2.5[43-45]3D3D3D3D1LOD23453D354.2.6windows4-94-104-124-94-10364.34-11AB3123Q=199791aC=2aC=21aP=50KN,2aP=110KN1c=2c=110RMB3c=60RMBζ=44-11--])100/(15.01[300)(411qwt+⋅=(4-1)])100/(15.01[350)(422qwt+⋅=(4-2)])50/(15.01[550)(433qwt+⋅=(4-3)1f=0.572f=0.691f=0.372f=0.45∗f∗f0.5100.5ε=0.014-14-21:(1.332:(1.6743.68374-124-34-124-1/kmq1q2q3f1f211864.5324689.774517424.69310.58240.704423252.73242020.423514705.84410.56500.68754-2/kmq1q2q3f1f213092.16441237.725115573.81290.38310.464525352.80144657.72809968.19850.36620.452838[46][47]14-44-34.44-3/kmffff1