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HUBERTREHBORN
MICHAKOLLER
STEFANKAUFMANN
Elsevier
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Preciselymeasuredtrafficdatafromallroadshaverecentlybecomeubiquitousintransportationandtrafficsciences.Therefore,theempiricalandcomprehensivebasisfortheanalysisandunderstandingofallfeaturesoftrafficis availablenowadays.Wetrytoexplainthelargevarietyandcomplexityof measuredtrafficdataandthosefeaturesonfreewaysaswellasinurbanareas. Manytrafficapplicationswillbesupportedbasedontheavailabledata.
Almost20yearsaftertheinventionofthethree-phasetraffictheoryby BorisKerner,itistimetohaveacloselookatitsconsequencesfortransportationengineeringaswellasitspracticalapplications.Thisbookwillhelp transportationengineersandtechnicianstounderstandboththeapplications andapplicabilityofKerner’sthree-phasetraffictheoryinavarietyofscenarios.Itstartswithmeasurementsoftrafficphenomena,bothwithstationary loopdetectorsandwithconnectedvehicledata.Then,atheoreticalaswellas historicalexplanationofthethree-phasetraffictheoryfollows.Basedonthis theoreticalfundament,anumberofthetheories’conclusionsofferideasfor newapproachesintrafficcontrolaswellasnewvehicularapplicationssuch asdriverinformationanddriverassistance.Moderntrafficengineering methodsarecloselyrelatedtoinformationtechnologyandcomputerscience.Therefore,algorithmsandmethodswillbedescribedwiththeirapplicabilityassoftwareinbothcollectivetrafficmanagementandindividual vehicles.
Today,moreandmorepeoplehaveabandonedprintedmapsinvehicles forrouteguidance.Instead,electronicnavigationhasbecomestateoftheart inallvehicles.Congestedtrafficinfluencesthosenavigationsystemsand theirrelateddynamicroutechoices.BasedonKerner’sthree-phasetraffic theory,weareabletodefinetherequirementsandtestingmethodsfor high-qualitytrafficmessagesusedinnavigationsystems.
Wehopeabroaderaudienceisinterestedinscientificexplanationsforthe emergence,propagation,anddissolutionoftrafficcongestion.Inaddition, theaspectsoftrafficphase-dependentfuelconsumption,theinfluenceof weatherontraffic,andaspectsofautomateddrivinginrealtrafficshould attractreaderswhenthesetopicsarediscussedtechnicallyinthescopeof thethree-phasetraffictheory.
Empiricalmeasurementsindifferentcountriesandofdifferentkindsillustratethevarietyofcongestedphenomenaintraffic.AhistoryofKerner’s three-phasetraffictheorywillexplainsomehistoricstepsfromthefoundationsofthistraffictheoryanditsconsequencesuntiltoday.Startingfrom trafficmodelingintheearly1990,theintensiveworkwithempiricalmeasuredtrafficdataleadstoadeepunderstandingofthecomplexdynamicprocessesonfreeways.Additionalconsequencesofthethree-phasetraffic theory’sstatementshavebeenboththeproposalofpracticalapplications andtheinventionofimprovedtrafficmodels.
Thisbookwilloutlinethedevelopmentofthethree-phasetraffictheory aswellasexplaintherelevantmilestonesandsteps.Itstartswithahistorical viewontrafficmodelinginthree-phasetraffictheoryandproceedswith thefundamentsofthetheory.ThehistoryofthemodelsASDA/FOTO andsomeotherapplicationsaresummarizedfurtheron.Jamtailwarnings andonboardtrafficstatedetectionmethodsdescribeanapproachthat includesmoreprecisetrafficinformationinvehiclesystems.Thevehicles’ navigationsystemshavetointegratetrafficmessagesinaproperway,and thequalityofthosecongestionmessageshavetobeevaluatedinthescope ofKerner’stheory.
Everymorning,thecommutersinmanyurbanareasoftheworldsufferfrom timedelayscausedbytrafficcongestion.Thecongestionisregular,recurring,andpermanentatcertainlocationsoftheroadnetwork.Therefore, beginningfromabetterunderstandingoftheunderlyingphysicalprocesses intraffic,thewishforpreciseandreliabletrafficanalysisarisesformultiple trafficmanagementpurposes,bothcollective(e.g.,trafficcontrol)orindividual(e.g.,dynamicrouteguidanceinnavigationsystems).Toreachthese goals,empiricalcongestionpatternsmustfirstbeanalyzedandunderstood correctly.Thiscanbedoneonlyifsufficientmeasuredtrafficdataareavailable.Today,connectedvehiclessendingtheirpositiondata(i.e.,probevehicledata)areonekeyelementofcollectingtrafficdataoneachroadsegment throughoutthewholeroadnetwork.
Ourbookintroducesmanydifferentcongestedtrafficsituationsmeasuredwithconnectedvehiclefleetsanddiscussesseveralaspectsofpossible trafficapplications.Theinvestigatedvehiclefleetcontainsmorethanone millionvehiclesthathavegiventheirpositiondatatoimprovethequality ofthetrafficservice.Aswewillshowinthebook,about2%ofthetotalflow rateonaroadsectiongivesenoughinformationtoreconstructtherelated trafficsituationwithhigh-enoughquality:onathree-lanefreewaywith about6000vehiclesperhour,about120connectedvehiclesand/ordevices sendingtheirpositiondatatoacentralserverallowatrafficservicewith about500–1000mgranularityofthepositionsofanytrafficcongestion. Thecomplexityofthedifferentcongestedtrafficpatternsatdifferentbottlenecksisillustratedforseveralroadsectionsinseveralcountries.Themeasuredtrafficdatashowthevarietyinmanyheterogeneoussituationsthat emergeduetoourdrivingbehavior:theindividualbreakingandaccelerationleadtocollectiveeffectsthatcanpropagateseveralkilometersupstream. Inaddition,weinvestigateandanalyzemicroscopictrafficwiththehighest possibledetail:droneobservationsallowmeasuringthedrivingofeachindividualvehicleovertime(i.e.,inatimeintervalofabout20min)andspace (i.e.,about400mwithonecamera)simultaneously. Fig.1 illustratessucha dronemeasurementonafreewaysegment,observingallvehiclesbyacameraanddetectingallobjectsonthefreeway.
2 Data-driventrafficengineering
ThetheoreticalfoundationofthisworkisgivenbyBorisKerner’sthreephasetraffictheory(seeWikipedia [1] andthebooks [2–4]).Trafficcanbe distinguishedintothreedistinctphases:(i)freeflow,(ii)synchronizedflow, and(iii)widemovingjam.Infree-flowingtraffic,eachdrivercanchoosehis individualspeedandcanovertakeonpurpose;insynchronizedflow,there arealmostnopossibilitiestoovertakeandthespeedhasatendencytobe synchronizedamongthedifferentlanesofthesamedrivingdirection;and inthewidemovingjamphase,thevehicleshavecometoanearstandstill andthetrafficflowisinterrupted.Thetrafficbreakdownisassociatedwith aphasetransitionfromfreetosynchronizedflow.Insidethesynchronized flowregion,duetodriverbehaviorwidemovingjamscanprobablyemerge thatthenpropagatefurtherupstreamwithavelocityof 15km/hon average.
Thebookwillfollowtheprincipleofdiscussingalldata-drivenfactsand featuresbasedonmeasuredtrafficdataonly.Manyvarioustrafficcongestions onfreewaysandinurbanareasarepresentedin Chapter2:time-space diagramsofmeasuredfleetdatafromconnectedvehiclesillustratethecomplexityoftrafficcongestion. Chapters3 (dedicatedtothehistoryofthe three-phasetraffictheoryandcongestedtrafficpatternsonfreeways)and 4 (discussingcongestioninurbanareaswithsignalizedintersections)try togiveacomprehensiveoverviewofallkeyelementsofthethree-phase traffictheoryastheyarerelevantforunderstandingallempiricalexamples.
Fig.1 Snapshotofcameraobservationandobjectdetectionprovidedbyadrone measurementofafreewaysegment.
Thisbackgroundgivesthefoundationofthedifferentapplicationsintransportation;withoutthisbackgroundwecannotdistinguishbetweenpossible andimpossibleapplicationsandwhysomeapplicationsarepossiblewhile othersfailcompletely.
Chapter5 withapplicationsintransportationbeginswithareviewofthe ASDA/FOTOmodelsdevelopedbasedonthethree-phasetraffictheory andimplementedinsoftwaremodules.Wewillshowinadditionthedependencyofthetrafficparametersontheweatherconditions.
Whatthenfollowsisageneralstatisticalanalysisofthedatafromalarge fleetofconnectedvehicles:whatarethemobilityparameterssuchasaverage triptimes,speeds,etc.,andtherefore,howdopeopleusevehiclesinsome differentcountries?Inaddition,whatistheroutechoicebehavioriftraffic informationisusedinnavigationsystems?Dopeoplefollowadvice?Also,in whichtrafficsituationscanatimedelaybesavedwithalternativeroutesin theoccurrenceoftrafficcongestiononthemainroad?Andhowmuchtime canbesaved?
Ifenoughandprecisevehicledataareavailableonaroad,anactivejam tailwarningwillbecomefeasible.Thisannouncessuchaneventinadvance toeachdriver:thepositionovertimeof,forexample,awidemovingjam withasuddenbreakdownfromfreeflowtoacompletestandstillcanbe reconstructedwithin500–1000maccuracy.
Furthermore,detailedmeasurementsinvehiclesallowdiscussingtraffic phasedependentfuelconsumption:duetodecelerationandaccelerationin congestedtraffic,thefuel/energyconsumptionincreases.Wecanrevealfactorsofincreasedaverageconsumptionindependencyoftherelated trafficphase.
Automateddrivingisoneoftherelevantresearchtopicsoftheautomotiveindustryanditcomeswithhighexpectationsforourmobility.Wewill concentratethetechnicaldiscussionofonespecificdifficultexampleforan automatedvehicle:whatarethetimegapsinrealtrafficandhowcansuchan automatedvehiclemergeontoahighwaythroughanon-ramp?
Forvehiclemanufacturerswithembeddednavigationsystemscompetingwithmobiledevicesregardingapplicationsandfeatures,oneremaining possiblefieldofvehicularapplicationisthevehicleitself.Themanufacturer canusethedynamicinformationofthetrafficserviceinthevehicleby,for example,usingupcomingcongestionaheadtotriggerthebehaviorofacontrolunit(e.g.,withabreakingassistsystem)inacertainway.Asanother example,anupcomingjamfrontcanbeusedtoactivelyreducethevehicle speedadvisedtothedriver.
Finally, Chapter5 willdiscusssomeexamplesandaspectsoftrafficservicesfornavigationsystemsandillustratesomeexamplesofcomplextraffic situations.
Allthetheoreticalworkandthetrafficdataanalysisworkhavebeensupportedbyseveralcolleagueswhomwewanttothank:BorisKernerandSergeyKlenovfortheirsupportonalltheoreticalandapplicationquestions; JochenPalmerforhisalgorithmicworkonASDA/FOTOwithprobevehicledata;PeterHemmerleforhisworkwithurbantrafficdataanddrone experiments;MarkusAuerforhisanalysisofthemobilitydataofthevehicle fleet;Sven-EricMolzahnforhisinvestigationofjamtailwarningapplications;andYildirimD € ulgarforhisanalysisoftimegapsofvehiclesandthe preparationofdiagramsforfleetdata.Thisbookwouldnotbepossible withoutsomefundedpublicresearchprojectsoverseveralyears(e.g., “MECView—ObjectdetectionforautonomousdrivingbasedonMobile EdgeComputing”and“LUKAS—Localmodelforcooperativeandautonomousdrivingincomplextrafficsituations”fundedbytheGermanFederal MinistryofEconomicAffairsandEnergy)aswellasthesupportofthe Mercedes-Benzresearchanddevelopmentfacilities.
[1]Anon, https://en.wikipedia.org/wiki/Three-phase_traffic_theory
[2] KernerBS.Thephysicsoftraffic.Berlin,NewYork:Springer;2004.
[3] KernerBS.Introductiontomoderntrafficflowtheoryandcontrol.Berlin,NewYork: Springer;2009.
[4] KernerBS.Breakdownintrafficnetworks:fundamentalsoftransportationscience.Berlin:Springer;2017.
Westructurethedescriptionofthemostcommontechnologiesformeasuringtrafficdataonroadsintothreeseparatesections: Section2.1 describesthe historicallyandcurrentlystillwidelyusedmeasurementswithfixedinstalled sensorsintheroadnetwork.Trafficdatafrommovingobjectsintrafficflow, called“probevehicledata,”areincreasingnowadayswithconnectedvehiclesandothermobiledevices;thisisexplainedin Section2.2.Dueto recentlyavailabledronetechnologiesandobjectreconstruction,theaerial observationoftrafficflowisanewlyreinventedandinterestingapproach togetcomprehensivespatial-temporaltrafficdatasets(Section2.3).
Empiricaltrafficmeasurementsaretodaystillverycommonlyperformed withfixedinductiveloopdetectorsinstalledonlanes,bothonfreeways andinurbannetworks.Typically,theyhavefixedmeasurementintervals of1minandaggregatetwotrafficflowvariables:(i)theaveragespeedof allpassingvehiclesinkilometresperhour,and(ii)thetrafficflowrate countedinvehiclesperhour.Infreeflowconditions,typicalflowrates ononefreewaylanegoupto2500vehiclesperhourandtheaveragespeed isapproximately100km/hormore.Fortrafficcontrolpurposes,thespeed andflowratebreakdownofthemeasuredvariablesisusedtoidentifycongestion.Inaddition,doubleloopsensorscandistinguishamongdifferent vehicletypessuchaslongvehicles,passengercars,andtrailers.
Anexamplefortypicalempiricalmeasurementswithalocalloopdetectorisillustratedin Fig.1.Onfreewaysegmentswithvariablemessagesigns (VMS),thecontrolofthespeedsshowntodriversisderivedfromdatameasuredbytheloopdetectorscoveringeachlane(oneofthemmeasuresbelow eachVMS). Fig.1Apresentstheschemeofthefreewayandthepositionsof loopdetectors.Incolour,twodifferentkindsofverycommonbreakdowns aremarked:(i)inaspeedandflowdiagram,thered(darkgreyinprintversion)markedtimeintervalischaracterizedbyasuddendropinbothspeed andflowmeasurements,and(ii)in Fig.1B–C,theyellow(lightgreyinprint
Data-DrivenTrafficEngineering ©
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Fig.1 (A)schemeofafreewaywithloopdetectors,(B)averagedvehiclespeedatthe leftlaneofdetectorD1,(C)flowrateattheleftlaneofdetectorD1. (AdaptedfromKerner BS,RehbornH.Experimentalpropertiesofphasetransitionsintrafficflow.PhysRevLett, 1997;79:4030.)
version)markedtimeintervalshowsadropinthevehiclespeedwhilethe flowrateremainsabove1200vehiclesperhour(fordetailsee[12]).
Adetailedpictureofloopdetectormeasurementsshowingeachindividuallaneisillustratedin Fig.2:themeasurementsforeachlaneofthefreeway indicatethehigherspeedontheleftlaneandthelowestspeedontheright lane(inGermanyduetotherightdrivinglawafterovertakingandlong vehiclesontherightlanes).Anuparrowshowsthetimemomentwhen attheloopdetector,thespeeddecreasesandbecomessimilarinalllanes (atdetectorsD1toD4).
Fig.2Ashowsaclearsynchronizationofthevehicle speedsonthethreelanesafter7:16a.m.Incontrasttofreeflow,overtakingis thennolongerpossibleatthereducedspeedofabout60km/h.Froma driver’sperspective,thismightbecalledslowand/orqueuingtraffic.The correspondingflowrateatdetectorsD3andD4(Fig.2E)showshighvalues ofabout2400vehiclesperhour.Inaddition,theinvestigationoftheD2 on-rampmeasurementsrevealsabreakdownintheaveragespeedsonthe rampbetween7:12a.m.and9:12a.m.(Fig.2G)whileafterashort
Fig.2 (A)–(D)Vehiclespeedsatloopdetectorsfromafreewaysegmentshownin Fig.1Aforeachlane;(E,F)correspondingflowratesatD3,D4,andD2on-ramps;(G, H)D2on-rampmeasurementsforalargertimeinterval. (AdaptedfromKernerBS, RehbornH.Experimentalpropertiesofphasetransitionsintrafficflow.PhysRevLett, 1997;79:4030.)
breakdownintheflowrateatapprox.7:40a.m.(Fig.2F),theflowrateatthis on-rampremainsonahighlevelatabout500vehiclesperhourmerging ontothefreeway.
Inadditiontofreeways,loopdetectorsareusedinurbanareastomeasure vehiclespeedsandflowrates.AnexampleforanurbanroadinD € usseldorf, Germany,isgivenin Fig.3:630maheadofthetrafficsignal“TS,”thefixed detector“D”measuresaggregatedtrafficvariables.Similartothetimeintervalsmarkedin Fig.1B–C,thedropinvehiclespeedandflowratecanbe observedattheurbandetectoraswell(fordetailsee[11]).Between 7:45a.m.and9:15a.m.onApril10,2013(andfrom8:00a.m.to9:15a.m. onFeb.5,2013),thereisasignificantspeeddropwithalmostnodropin