地铁乘车需求的影响因素外文文献翻译Word下载.docx
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地铁乘车需求的影响因素外文文献翻译Word下载.docx
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TheNortheastUnitedStates,particularlyNewYorkStatehasexperiencedanincreaseinextremedailyprecipitationduringthepast50years.Recenteventssuchas
Hurricane
IreneandSuperstormSandy,haverevealedvulnerabilitytotheintenseprecipitationwithinthetransportationsector.InthescaleofNewYorkCity,wheretransitsystemisthemostdominantmodeoftransportationanddailymobilityofmillionsofpassengersdependsonit,anydisruptioninthetransitservicewouldresultingridlocksandmassivedelays.Toassesstheimpactsofrainfallonthesubwayridership,wemergedhighresolutionradarrainfallandsubwayridershipdatatoconductadetailedanalysisforeachofthe116subwaystationsattheboroughofManhattan.Theanalysisiscarriedoutonbothhourlyanddailyresolutionlevel,whereaspatial-temporalBayesianmulti-levelregressionmodelisusedtocapturetheunderlyingdependencybetweentheparameters.Theestimationresultsareobtainedthrough
MarkovChainMonteCarlo
samplingmethod.Theresultsfordailyanalysisindicatethatduringweekdays,transitridershipinthestationslocatedincommercialzonesarelesssensitivetotherainfallcomparedtotheonesinresidentialzones.
Keywords:
Bayesianmulti-levelregressionmodel,Subwayridership,MCMCsampling,Radarrainfall
Largecitiesaroundtheworldrelyonpublictransportationinfrastructuretomaintainagoodlevelofserviceandtoincreasemobilityandeconomicproductivity.Inyear2015,morethan10.7billiontransittripswerereportedintheUnitedStates(Matthew
Dickens,2016).AccordingtotheAmericanPublicTransportationAssociation(APTA)every$1investedinpublictransportationgeneratesapproximately$4ineconomicreturnsthroughincreasedemploymentrate,businesssales,andenhancedpropertyvalues.Thefullreturnoninvestmentfortransportationsystemscanonlybeachievedwhencitiesoptimizeandplanthemaintenanceandgrowthoftheirpublictransportationsystemsthroughbetterrealizationofthedemandlevelfortransportationalongwiththeidentificationofotherinfluentialparameters.Transportationsystemperformancedependsonthegeometryofthenetwork,aswellasotherexternalfactorssuchasaccidents,operationaltearandwear,disruptionsondependentsystems(e.g.thepowergridforsubways),effectiveautomobileregulation,weather,etc.(DeGrangeetal.,2012).TheobjectiveoftheworkpresentedhereistoprogressfurthertheunderstandingofimpactsofrainfalleventsonthesubwayridershiplevelinManhattan,NewYork.
Duringthepast50years,NewYorkStatehasexperiencedanincreaseinextremedailyprecipitation(Hortonetal.,2011)alsoithasbeenheavilyaffectedbyunusualweatherpatternssuchas
IreneandSuperstormSandy.InNewYorkCity,withover4Milliondailycommutetrips(MossandQing,2012),theevidenceintheaftermathofextremeweatherpatternshaverevealedvulnerabilitiestointenseprecipitationwithinthetransportationnetwork,yieldingenormouseconomiclossesfortheCity(Brian
Tumulty,2012).Abetteranalysistoquantifytheeffectsofvariousweatherconditionsonthetransportationnetworkwouldresultinwell-informedandefficientpolicy-makingdecisions.Literatureinrecognitionofweatherinfluenceontransportationandmobilitycanbeclassifiedintotwogroups.Thefirstgroupoftheliteraturemeasurestheinfluenceofweatherontheperformanceoftransportsystems,whilethesecondgroupstudiesitsbehavioralimpactsoncommunities.Studiesontheinfluenceofweatherovertheperformanceoftransportationnetworksbrushoverlargespectrumoftopicsincludingtrafficflowandroadcapacity(e.g.
Kyteetal.,2001;
Mashrosetal.,2014;
Mazeetal.,2006),infrastructureperformance(e.g.
KoetseandRietveld,2009),trafficsafety(e.g.
AndreescuandFrost,1998;
KoetseandRietveld,2009)andchangesinthequalityofservice(e.g.
Coolsetal.,2010;
KhattakandDePalma,1997).Thesestudieshaveshedsomelightonthemostimportantaspectsoftransportationsystemsandserviceaffectedbyweather,whicharevaluableinformationforcityadministrators.Ingeneral,traveldemand,trafficsafety,andthetrafficflowarethethreedominantfactorsimpactedbyadverseweather(Mazeetal.,2006;
Mashrosetal.,2014).AccordingtoastudyconductedinManchestercityby
JaroszweskiandMcNamara(2014),duringrainfallstherateofroadaccidentsincreasesby50%.Meanwhile,throughamorecomprehensivestudycarriedoutbyHofmannandO'
Mahonyonvariousperformancemeasuresoftransitsystems,itisrevealedthatbadweatherconditionsdegradethelevelofserviceoftransportationsystems(HofmannandO'
Mahony,2005).
Behavioralimpactsofadverseweatherconditionsarestudiedthroughmeasuringitsimpactsonpublictransportdemand(e.g.
Guoetal.,2003;
Singhaletal.,2014;
Zhouetal.,2017),modalshift(e.g.
KhattakandDePalma,1997;
KoetseandRietveld,2009),androuteanddestinationchoice(e.g.
Guoetal.,2003).Astudyshowstheadverseweatherconditionschangesmodechoice,routechoice,anddeparturetimeofautomobilecommutersinBrussels(KhattakandDePalma,1997).Dependingonthetrippurpose,thechangeinthemobilitybehaviorduringdifferentweatherconditionssuchasrain,snow,temperatureandfogwouldvary(Coolsetal.,2010).
Ourstudyfocusesontheinfluenceofrainfallconditionsonsubwayridership.Despiteitsimportance,thedependencybetweenweatherconditionsandtransitridershiphasseldombeeninvestigated,especiallyatafinerresolutionusingspatiallydistributedrainfalldata.Existingstudieshavelimitedtheirattentiontomeasuringtheeffectsofweatherconditionsontheridershipdemandoftransitsystemonaggregatelevel(daily)(e.g.,
Aranaetal.,2013;
Changon,1996;
Kashfietal.,2013;
StoverandMccormack,2012).Thesestudieseithermeasurethedirectandindirectimpactsofextremeweatherevents(e.g.,increaseintraveltime,waitingtime,operationaldelaysinthesystem)ontransitusers(Guoetal.,2003;
HofmannandO'
Mahony,2005).
Aranaetal.,2013,analyzedchangesinthenumberofdiscretionarytrips(measuredviadailybusridershipovertheweekends)inresponsetoweatherconditions,wheretheanalysisdemonstratesdecreaseintransitridershipinrainyandwindydaysandincreaseduringhotdays.Trippurposeplaysacrucialroleinridershipdemandunderadverseweathercondition;
travelersaremorelikelytopostponeleisuretripswhilemandatoryandworktripsarelesslikelytobedeferred(Coolsetal.,2010;
Mazeetal.,2006).
KhattakandDePalma(1997)
foundthattransitridershipmayincreaseduringextremeweatherconditionsduetoshiftsfromothermodesoftransportationsuchasautomobiles,walking,andbiking.
Table1
presentsmoredetailsonsomeotherstudiesfocusedonassessingtheimpactsofweatherinstabilitiesontransitridership.Amongstthesestudies,itisworthnotingthat
StoverandMccormack(2012)
foundrainfalltobethemostinfluentialweatherfactor(amongwind,temperature,rainandsnow)leadingtoridershipdecrease.
Kashfietal.(2013)
conductedadailyanalysisandfoundastrongnegativerelationshipbetweenrainfallandridershipdemand.
Allthesestudiespresentimportantqualitativeandquantitativeinformationontheimpactofweatheronridership,buttheanalysisweremostlyconductedatalargespatialscale-e.g.citylevelaggregatescale-whichisnotnecessarilyaproperscaleforpredictingtransitdemand.Itispreferablefortransitplannerstoanalyzetransitdemandanalysisatthetransitstoplevel,asitisthespatialscalebywhichtransitusersusethesystem(Dilletal.,2013).Usingspatialpointscalelevelisalsousefultoconnecttransitdemandwithlandusecharacteristicsofthestations.Fewstudieswereconductedatadetailedspatialortemporalresolution.Forexample,
Singhaletal.(2014),utilizedhourlyridershipdatatoevaluatethesystem-levelridershipinManhattan.However,theydidnotincludespatiallydetailedweatherdataintheiranalyses.Similarly,
Zhouetal.(2017)
employeddisaggregatelevelsmart-cardinformationtoinvestigatetheimpactofweatherontransitridershipinShenzhen,China,reportingthatrainfallhasanegativeimpactonridershipduringoff-peakhoursandduringweekends.Majorityofthestudiespresentedin
appliedstepwiselinearregressionsmodelsorsimilarstatisticalmodelstoestimateridershipindifferentweatherconditions(e.g.
Sabiretal.,2008;
Singhaletal.,2014).Furthermore,mostexistingstudiesusedsurvey-baseddatawithrelativelysmallsamplesizeasanexample.
Coolsetal.(2010)conductedasurveyovertwoyearswith586respondentsfocusedondailyaggregateridershipwithaggregatedweatherconditionsdatacollectedfromfewweatherstationsinthestudyareaofinterest.Forinstance
Singhaletal.(2014),utilizedinformationcollectedfromoneweatherstationintheiranalysis.While
Zhouetal.,2017
useddisaggregatelevelsmart-cardinformationandtheirdatasourcewaslimitedtoonemonth.
Afullyfunctionalmodelofweatherpatternsovertransitridershiprequiresanunderstandingofdetailedspatialtemporaldemandvariabilitytopredictfutureridershipdemandinvariousweatherconditions.Thecurrentstudyisastepinthisdirection.ThemaingoalofthispaperistofindouthowsubwayridershipinManhattanischangingduringrainfalleventsandisitbeingimpactedbythetimingofserviceandspatial
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