ITSCongressfinalpapertemplatexxITS1956finalpdf智能交通世界大会ITS智慧城市社区人工智能AI物联网IT报告课件教案

ITSCongressfinalpapertemplatexxITS1956finalpdf智能交通世界大会ITS智慧城市社区人工智能AI物联网IT报告课件教案 22nd ITSWorld Congress,Bordeaux,France,59OctoberxxPaper numberITS-1956Provision ofExpressway InformationUsing ProbeData*1Shigeki Yagi1,Hiroyuki Hasegawa2,Makoto Goto3,Masami Fukuda4,Shinjiro Nagasaki51.Project Creation and PlanningDepartment,East NipponExpressway CompanyLimited(NEXCO East)3-3-2,Kasumigaseki,Chiyoda-ku,Tokyo,100-8979,Japan,Tel:+81-3-3506-0391,e-mail:s.yagi.aae-nexco.co.jp2.Project Creation and PlanningDepartment,East NipponExpressway CompanyLimited(NEXCO East)3-3-2,Kasumigaseki,Chiyoda-ku,Tokyo,100-8979,Japan,Tel:+81-3-5425-2200,e-mail:h.hasegawa.ske-nexco.co.jp3.Transport OperationSection,East NipponExpressway CompanyLimited(NEXCO East)3-3-2,Kasumigaseki,Chiyoda-ku,Tokyo,100-8979,Japan,Tel:+81-3-3506-0229,e-mail:m.goto.ace-nexco.co.jp4.Mobile BusinessDepartment,ZENRIN DataComCo.,Ltd.,Shinagawa IntercityTower C6F,2-15-3Konan,Minato-ku,Tokyo108-6206,Japan,Tel:+81-3-6860-7421,e-mail:m_fukudazenrin-data.5.Mobile BusinessDepartment,ZENRIN DataComCo.,Ltd.,Shinagawa IntercityTower C6F,2-15-3Konan,Minato-ku,Tokyo108-6206,Japan,Tel:+81-3-6860-7421,e-mail:s_nagasakizenrin-data. AbstractEast NipponExpressway Co.,Ltd.,(NEXCO East),which constructsand managesexpressways in the easternJapan areacovering fromTokyo toHokkaido,and ZENRIN DataCom,which specializesin geographicinformation services(GIS)and location-based services(LBS),jointly developed and operatethe smartphone application(app)DraPla,which is designed to provide variousinformation to expressway users.NEXCO East Japan startedresearch on the provision of informationthrough the DraPla appjointly with ZENRIN DataComlast year,in anattempt to (1)educate expressway users aboutsafe driving,and (2)improve the precision of congestion information.This paperintroduces caseexamples of information provision by the DraPla appusing location information,which isone of the effortsin ourjoint research,and explainsthe status of ourreview regardingthe futureuse of probe data.Paper title2KEYWORDS:probe data,locationinformation,traffic congestion.1.Introduction Applications(apps)that usethe GPSof a smartphone andprovide informationdepending on the locationof the user(such asnavigation apps)have recentlye to be widelyused.Probe dataobtained through these appsare statisticallyprocessed asbig dataand utilizedin variousways to enhance userconvenience.2.Current Statusof JapaneseExpressways Japaneseexpressways arecharacterized byreduced punctualityarising fromtraffic congestiondue tolocal traffioncentration,such asmuting timeperiods onweekdays,recreation onholidays andtravel tosightseeing spots,or thehomeing rushduring longvacations.In addition,about70%of theland surfaceof Japan is mountainous,and the ratio ofmountains in the East Japan regionis particularlyhigh.This iswhy thereare manyroad sections with slopesand curves.The northernpart ofJapan andmountainous areasexperience snowfallin thewinter season,and therate of aident ourrenceeventually increasesdue todeteriorating roadsurface conditions.As oneof thesolutions for these conditions,the DraPla website operatedby NEXCO East Japan provides expresswayusers withvarious kindsof information to improvedriving safety and convenience.3.About theDraPla AppThe DraPla app isa smartphone app based on theDraPlawebsite,which providesvarious kindsof informationtoexpresswayusers.This websiteis operatedby NEXCO East Japan,which buildsand managesexpressways in the EastJapan regioncovering fromTokyo toHokkaido.The developmentand operationof the app areconducted jointlywithZENRIN DataCom,which specializesin geographicinformation services(GIS)and locationinformation services(LBS).The DraPla app wasreleased inAugustxxand hasbeen downloadedabout550,000times asof Mayxx.It mainlyprovides the following informationrelated toexpressways:A)Information oncongestion prediction,B)Information ontolls androutes,C)Information onrest areas and facilities,D)Weather information and roadsurface imageinformation(live camera),*only duringwinter and in theEastJapanarea,and E)A close-call notification function(new function).Paper title3Rest areaLive cameraPrice androute CongestionpredictionDate designationAutoPlay(Every hour)Departure:October11,xx8:00Distance:137.5kmRequired traveltime:1hour46minutesOrdinary toll:3,710yenETC discounttoll:2,850yenFROM:URAWA(TO:)New arrivalinformationSearch resultsStoreinformationTO:TOMIOKAURAWARestaurant information,Information fromConciergeRemended information from theshop46minutes41.2kmTohokuExpressway Searchcondition settingTohokuExpressway December11,xx8:00Live cameralocationLive cameralocation:YUDONOLive cameraarea:YASHIROFigure1-Screenshot of theDraPla app4.Current InformationProvision IssuesThe DraPla app wasonce operatedasapull-type informationprovision service,which meantthat usershad toobtain informationby themselves.Therefore,even thoughcontent supportingsafe drivingwas providedto usersthroughtheDraPla app,it didnot necessarilymean the right informationwas providedto the right usersat the right time.The conventional type of congestion informationwas basedonasystem ofcongestion detectionusing sensorsinstalled on expressways.However,it isdifficult toinstall thesedevices onall roads,and thusthe sensorsare preferentiallyinstalled onsections with a largetraffic volume.Considering thisfact,it standsto reasonthat congestioninformation onsectionswitha smallertraffic volumeis poorerin precision.5.Actions toTackle theIssues NEXCO EastJapanand ZENRIN DataCom starteda joint research projectin Aprilxxto solvethe problemsmentioned above.NEXCO EastJapanprovidestraffic informationnecessary forjoint researchand a field fordemonstration experiments,while ZENRINDataCom providesmap dataand varioustechnologies thathelp solvethe problems.In thejointresearch,we reviewedthe conventionalpull-type provisionofinformation,and decidedto solvethe problemsposed bythis methodby developinga push-type informationprovision service that providesDraPla app users withtherightinformation that matches their location at therighttime.When informationis providedbasedona push-type methoddepending on the locationof the user,it isnecessary toregularly obtainpositional informationof usersfrom theirsmartphones.As aresult,probe data(big data)are aumulated.It wasthen assumedthat statisticalprocessing ofsuch gathereddata wouldenable us to provideusers withtherightinformation thatplements theconventionaltypeofcongestioninformation.Paper title46.Outline of the functionof expressway close-call notificationWe studieda push-type informationservicethatprovides informationto usersdepending on theirlocationso as to ensurethe safetyand securityof users.As afirst step,we decidedto provideAndroid andiOS userswithanew functioncalled the“close-call spotnotification function.”This functionprovides awarning messageintheform of a smartphonepush notificationand simultaneousaudio warningmessage to the driverof a vehicle headingtoward alocation onan expresswaythat requiresthe drivers specialattention,such asa longslope ora steepcurve.(Provision startedin Aprilxx.)Figure2-Screenshot of“expresswayclose-call notification”7.Mechanism of the expresswayclose-call notificationfunction Wedevelopedalibrary*2that periodicallymeasures positionalinformation evenif theapp is inthe background in order to allow activationof the close-call spotnotificationfunctioneven when theuseris notoperating theapp.Next,a geofence*3is placed in front ofa close-call spotto determineif avehicle isapproaching it.The positioninformation on theclose-call spotand thealert informationwill begiven bya push notification on theDraPlaapp.Furthermore,toenhancetheprecisionof thepushnotification,the locationalrelationship between the longitudeand latitudeof the probe dataposition and the expressway is clarifiedby mapmatching soastoidentify onlyterminals moving on expressways.A demonstrationexperiment wasconducted toverify thesetechniques.8.Demonstration ExperimentA demonstrationtest wasconducted onan expresswaymanaged byNEXCOEastJapan asafieldtest tomercialize the smartphoneappused fortesting.Paper title5The followingconditions are used for a pushnotification ofa close-call spot:?The vehicle is travelingat a speed of60km/h ormore,?The vehicle is traveling onan expressway,and?The vehicleis travelingtoward aclose-call spot.i)Positioning libraryWe testeda positioninglibrary capableof providinginformation atthe optimaltiming whilereducing smartphonebattery consumption.Specifically,a certain speed isset asa thresholdvalue,and the positioning timinginterval orpositioning methodsare changeddepending on the travelingspeed of the vehicleorthepower supplycondition of the smartphone.In theexperiment,the travelingspeed ofa terminalis calculatedfrom the probe data,aspeedof60km/h orhigher isset asthe thresholdvalue,the positioninginterval isshortened forAndroid terminals,and the positioning methodis shiftedfrom stationpositioning toGPS positioningfor iOSterminals.The operationalintegrity dependingonthepower chargingstatus of thesmartphonewas alsochecked.Specifically,when asmartphone isin a power supply state,the positioninginterval timeis designedto beshortened.When thesmartphone isnot inapowersupplystateand thebattery remainingcapacity fallsbelow acertain threshold,GPS positioningisdesignedto bestopped.Figure3-Switching ofpositioning ii)Geofence Anexperiment wasconducted to determine theoptimal geofencearea and appropriate notificationconditions in order torealize pushnotification toterminals approachingaclose-call spot.The geofenceshape wasdeveloped asa binationofacircle andan Paper title6arbitrary shape(polygon).The experimentresults indicatedthat,when theGPS receivingprecision islow,there werecases in which a probe wasnot positionedonan expressway,andinwhich theposition ofaprobewas sometimesmeasured ona sideroad abouta fewmeters todozens ofmeters awayfrom an expressway.Therefore,it wasdecided that the geofencearea shouldbe determinedas anarea largerthan theroad width,rather thana sizethatmatchesthe widthof the expressway.Circular Arbitraryshape(polygon)Figure4-Shape ofgeofence Itis alsonecessary togive awarning onlyto vehiclesapproaching close-call spots,so twogeofences wereplacedinfrontofeach close-call spottodetermine the movementdirection ofvehicles.iii)Judgment of means of movement Anexperiment wasconducted todetermihe means of movement inorder torealize theprovisionofinformation onlyto thosewho aretraveling onexpressways.Specifically,inorderto judgethat avehicleistraveling onan expressway,the positioning points obtained from thevehicle asit movesfrom pointA toB arematched withexpressways,ordinary roads,railroad tracks,etc.,along the time series.Data ondistance error,speed,and otherfactors arealso considered,andaprehensive judgmentis thenmade regardingwhether thevehicleismoving alongan expressway.The means of movementwere mostlyjudged correctlyaording to the resultsof theexperiment.However,it wasrevealed thatwhen anexpressway iscongested,it isdifficult todifferentiate vehiclestraveling ona roadthat runsparallel toanexpresswayfrom thoseonthe expressway,aording to the currentlevel ofGPS auracy.We decidedto usethe judgmentonthemeans ofmovement toascertain thestatusofcongestion basedonthe acquisition andaumulation of probe datafrom theDraPlaapp.Paper title79.Review ofuse of the probe data Probe data canbe obtained from theDraPlaappby providingthe expresswayclose-call notificationfunction.Probe dataare acquired from DraPlaapp userswith theirconsent,and transformedinto prehensivestatistical datathat donot containinformation that allows theidentification ofindividuals.The dataareused in servicequality improvementand forother purposesconsidered usefulor appropriate.An opt-out systemis available,inwhichtheacquisitionofthe probe data foraspecific personis stoppedwhen theperson requestsit.NEXCOEastJapanisstudying waystoprovidefurther informationto roadusers inthe futureby usingthe data analysis technologyowned byZENRINDataCom.Specifically,the ideais toconduct big-data processingofthe probe dataaumulated inthe server,as wellas otherprobe datasuch astraffic counterdata orITS spot data,and toapply suchbig data toanew informationprovision servicefor roadusers.We arenow workingon analysis ofthe probe data acquired from theappand itsvisualization asa preparatorystep forthat futureplan.The processofprobe data analysisconsists ofthe stepsoutlined below.A)Upload thepositioningpoint datatothe server.(Data1)B)Sum upthepositiondata foreach smartphoerminal IDalong thetime series.The positioningpointdataare dividedinto timezones wherevehicles are moving andthose wherevehicles arestationary.The stayhistory andmovement historyare piledinto adatabase aording totheterminal ID.(Data2)C)Conduct mapmatching ofthepositioning points thatbelong tothetimezones judgedtobewhen vehiclesare movingto estimatetheusehistory aording tothemeans of transport.The means of transportare dividedinto fourcategories:“moving alonganexpresswayby car,etc.,”“moving alongan ordinaryroad by car,etc.,”“moving bytrain,”and“moving onfoot orby bicycle.”When the movement historyfor“movingonanexpresswaybycar,etc.”is created,the movementhistory characterizedaordingtothe estimatedroutes,such asthe entrypoint(interchange)or transitpoint(junction),is alsocreated.(Data3)Using Data1to3above allowsustoascertain theitems notedbelow.(Data1)Time whenavehiclepassed anarbitrary point,change inmoving speed,and pointwhere congestion ourred.(Data2)Distance ofeach movementand timetaken forthat movement,the locationand durationof stay,the relationshipbetweentheorigin anddestination(OD),and thearea ofdeparture anddestination ofa terminalthat stayedataSAPA.(Data3)Duration oftime whenthe expresswayis used,theratioof expresswayuse,the numberof usersaordingtothe inter-IC section,and thetendency ofroute usePaper title8(binations ofentry interchangesor junctionsused).10.Example ofprobe data analysis Whatfollows isan exampleofthe analysisofprobe dataactually obtainedfrom theDraPlaapp.Note that theprobe data samplesusedintheanalysisreported inthis paperare thoseacquiredfrom (1)patrol carsmanaged byNEXCOEastJapan,and (2)employees ofZENRINDataCom.(Probe dataobtainedfromactual usersoftheapp werenot used.)i)Judgment ofmeansofmovement Forthemovementhistory oftheprobedata,whether ornot the data representthose movingonthe expresswayisjudged bymap-matching thepositioningpoints.When wecheck thehistory ofthe sample data formovement onthe expresswaysontheprobedataanalysis viewer,we canmake ajudgment thatthedataactually representmovement ontheexpressway.The interchangesused,the distancestraveled,and theaverage speedsare summedup.Judgment resultofprobedataanalysisviewerOrdinary road00:28:33Expressway01:50:48Stay00:22:54NOType:Passage oftimePeriod:IC nameSpeed:DistanceHigashi-Kanto Expressway(WanganIchikawa-Itako),WanganIchikawa IC,Tokyo Bay Aqua-Line UmihotaruPAup lineJudgment ofthemeansoftransportPositioning pointTokyoBayAqua-LineUmihotaruPAHigashi-Kanto ExpresswayTokyoBay TokyoDisneyland Figure5-Judgment onthemeansoftransportii)Determination ofcongestion Thetraveling speedsare calculatedfrom theprobedata,and changesinspeedare shownin differentcolors.We identifiedtheprobedata fortravelingonthe KeiyoRoad outofthesampledataand checkedthem ontheprobedataanalysisviewer,and foundthatthedata showedslowing-down tobelow20km/h beforereaching theHanawa IC.This meansthattheanalysis suessfullyvisualizes speedreduction ontheexpressway.For reference,we checkedtheexpressway sen