城市道路交通数据可视分析综述_姜晓睿

0454TP391A1006-8961201504-0454-14JiangXＲTianYJiangLLiangＲH．VisualanalyticsofurbanroadtransportationdataasurveyJ．JournalofImageandGraphics20152040454-0467．．J．20152040454-0467．DOI10．11834/jig．201504012014-09-012014-11-10Ｒ14F0200052013Ｒ100542014C33071983—2013、、。[e-mail]12211.3100232.310023。。。。、。。、。。PC。GPSVisualanalyticsofurbanroadtransportationdataasurveyJiangXiaorui1TianYa2JiangLi2LiangＲonghua11.CollegeofInformaitonEngineeringZhejiangUniversityofTechnologyHangzhou310023China2.SchoolofComputerScienceandTechnologyZhejiangUniversityofTechnologyHangzhou310023ChinaAbstractObjectiveUrbantransportationhasbecomeaglobalchallengethatplaguesallglobalmetropolises．Visualana-lyticstechniqueshaverecentlybecomeanimportantintelligenttransportationtechnologythatiscrucialtotheanalysisandutilizationofbigtransportationdata．Thisstudyattemptstoreviewthestate-of-the-artofvisualanalyticstechniquesinurbantransportationdatacomprehensively．Thesetechniqueshavebeendevelopedsincetheproliferationofinformationvisualiza-tionandvisualanalytics．MethodThediscussionmainlyfocusesontwobroadaspectsroadtrafficanalysisproblemsandotherintelligenttransportation-relatedproblems．Adetailedpresentationofthevisualizationtechniquesandvisualanalyticssystemsisorganizedaccordingtothetransportationdatatypeandtransportationproblemcategory．Ｒecentresearchtrendsaresuccinctlysummarized．ＲesultManyearlystudieshavefocusedondesigningtechniquessuchasarrowgraphmosaicmapandtrafficwalltovisualizeroadtraffic．Withthesetechniquescurrentresearchonroadtrafficanalysishasplaced20/4/20154/0455emphasisontrafficevents．Howeverthedefinitionoftrafficeventsremainslimitedtotrafficcongestion．Otherapplicationareasofvisualanalyticsintheintelligenttransportationdomainincludepublictransportationtrafficaccidentsandhumanmobility．Inrecentyearsanewresearchtrendofminingandutilizingthesocialdimensionsorsocialcontextualinformationofvehicletrajectoriesortrafficeventshasemerged．ConclusionFromtrafficflowvisualizationtovisualanalysistrafficinci-dentsfromanalyzingroadtrafficstatustootherurbantransportation-relatedsocialproblemsfromanalyzingsingle-sourcetransportationdatatomulti-sourcedatathatarerichinsocialsemanticsandfromthetraditionalinteractivevisualizationparadigmatthePCendtonovelmediaanddevicesforvisualpresentationthedepthandbreadthofresearchontransporta-tiondatavisualizationhavesignificantlybroadened．Theresearchtrendofthisdomainisalsoevident．KeywordsurbantransportationproblemsvisualanalyticsGPStrajectorydatatrafficflowanalysistrafficincidentanalysis0。、、。GPS。GPS、。。2005。。。。GPS。1。GPSGPS。GPS。GPS、。。GPS。1.1GPS。。。、、1。、2。2。1.2GPS。GPS。GPS。1GPS。3GPS0.0023、0.0047。1GPS2Vol．20No．4Apr.20150456GPS。。、4。5。。S-Tmatching67GPS。Liu8WI-matching。1.3GPS。GPS510sGPS。GPS“”//1。22.1。Andrienko9、。。OPTICS10visualclutter。1。11。。2。1Fig.1Arrowgraphforroadtrafficflow2Fig.2Trafficflowfromsingleresort12。“”traffic-oriented“”trajectory-orien-ted。“”、、、、“”。S-Taggregation3。/。。。Tominski132/32D/3D、。。20/4/20154/04573Fig.3Mosaicmapforthespatio-temporalcharacteristicsoftrafficflowsthroughcertainregions。。trajecto-rywall24。2/3。132timelens4。timelinktimescale。、。42D/3DFig.4Trafficwallandtimelensthatintegrate2D/3Dmethods314。14space-timecube。。1335。5Fig.5Space-timecubeforvisualizingspatio-temporalclustersoftrajectories13Pu15T-Watcher。1215visualfingerprint6。。Liu8VAITvisualanalyticsforintelligenttransportation。T-WatcherVAIT。VAIT24h7/。6T-WatcherFig.6Ｒing-stylevisualfingerprintingforvisualizingregionaltrafficintheT-WatcherSystemVol．20No．4Apr.20150458Feirerra16、、TaxiVis。TaxiVis158。、7aSQL。pointcloud、、densitymapgridmaplevel-of-detail7b。TaxiVis、。7TaxiVisFig.7ThevisualqueryinginterfaceandqueryresultvisualizationintheTaxiVissystemGPSTripVista17。。TripVista、themeriver38a—c。6。、、、。arrowglyph。。8TripVistaFig.8TheTripVistavisualanalyticssystemformicroscopictrafficpatternsintrajectoriesatroadintersections2.2。。、。。“”。vonLandesberger18DCDV、。DCDV9。。。DCDV。9Fig.9Dynamiccategoricdataviewforvisualizingtrajectorystatetransition。Andrienko19-20m-20/4/20154/0459m-。1410。10a。10b3。Wang2。GPSWang11。。1212a12b。cell。10Fig.10Trafficcongestionclusteringandvisualization11Fig.11Informationcardofthecongestionpointandtheambientcongestionpointandtheambientcongestionpropagationnetwork12Fig.12Thepixelmapforvisualizingthetimedistributionoftrafficjams33.1Mai21Marey。Marey188513。21Marey、。Vol．20No．4Apr.20150460。14a。Marey14b。。MareyHranac2215。15。131885MareyFig.13TheMareygraphvisualizationofthetrainschedulefromParistoLyonsin18851421MareyFig.14TheextendedMareygraphbyrefrence2120/4/20154/04611522MareyFig.15TheextendedMareygraphbyrefrence22Du23MetroVis。21-22、、。MetroVizstop/station、routetrip33。16ab。16c、、。16MetroVizFig.16ThevisualinterfaceoftheMetroVizsystem3.2Itoh2428。。。heatMapview、17a。。routeview17b。。3.3。。。Vol．20No．4Apr.2015046217Fig.17VisualanalysisofchangesinmetropassengerflowsGao25。choice-of-locationgraph/wait/movestrategictree18。。Beizer。/、。25。18Fig.18Visualanalysisoftaxidrivers’movingintelligenceLiu26。、3。19Fig.19Visualanalysisofroutediversity19a。tripview19b19b。20/4/20154/0463、。3.4VanDanikerTIMEt