ITS:UrbanMobility

Contents

• Reasonsforanopen-sourcetrafficsimulation• Neededmodels,data,anditsprocessing• SUMOOverview

OpenSourceRoadTrafficSimulationApplicationsforaroadtraffic

simulation• reproducible,computerizedevaluationof

– real-worldnetworkperformance– newconceptsfor

• moderntrafficsignalcontrol• trafficsurveillance• trafficforecasting• trafficmanagement• dynamicroutingmethods• car2car/car2infrastructurecommunication

– trafficmodels• instructivevisualization• planning

OpenSourceRoadTrafficSimulationNeededComponents

road network vehicles / flow signalling

OpenSourceRoadTrafficSimulationWhyanopensourceroadtraffic

simulation?Commonprocedure• Anacademicorganizationwantstoevaluateanaspectoftraffic• Buildsanowntrafficsimulation;needs

– Anetworkrepresentationincludingspeedlimits,right-of-way– rules,etc.

– Arepresentationofvehicles,theirmovement,routes,etc.

– Arepresentationofsignals,variablemessagesigns,etc.

…yieldsinMany(incomplete)simulationswhichresultscannotbecomparedà Solution:anextendablesimulationasabaseforowndevelopment

OpenSourceRoadTrafficSimulationDesigncriteria

• Portability– Achievedbyusingc++andportablelibrariesonly

• Performance– Highexecutionspeed– Nolimitationsinnetworksizeandnumberofsimulatedvehicles

• Extendibility• Opensource

– LicensedunderGPL– Hostedatsourceforge(http://sumo.sourceforge.net)

• Microscopic– Eachvehicleismodeledexplicitly

RoadTrafficSimulationRoadTrafficFlowDynamics(oneof)

Fundamental diagram of traffic (counted through induction loops)

As interpreted by Kerner As interpreted by Kim and Keller

RoadTrafficFlowSimulationClasses

macroscopic microscopic sub-microscopic

mesoscopic

RoadTrafficFlowSimulationMicroscopicModels

Mostly:• discreteintime• “CarFollowingModels”:

vehicle‘sspeeddependsontheprecedingvehicle

RoadTrafficFlowSimulationCarFollowingModelbyKrauß*

Features:• continuousinspace• discreteintime• accident-free• stochasticdrivermodel

Parameters:accelerationdecelerationmax. speeddriver’s imperfection

[*] “Microscopic Modelling of Traffic Flow: Investigation of Collision Free Vehicle Dynamics”, S. Krauß, DLR (Hauptabteilung Mobilität und Systemtechnik), 1998, ISSN 1434-8454

RoadTrafficFlowSimulationFurtherModelsneeded

• LaneChanging– Navigation(Ihavetoturnleftonnextjunction)– Tactical(leftlaneallowsmetomovefaster)

• Interactionwiththenetwork– Stopsatredtrafficlights– Decelerateifothervehicleshaveahigherrighttomoveon

thenextjunction• Extensions

– Vehicleclasses,suchasbusses,whichuseownlanes– Busstops

MicroscopicRoadNetworksNeededvs.givenInformation

Neededstreetattributes:• Numberoflanes• Allowedspeed• Per-lanerestrictions• Allowedcontinuations

Neededjunctionattributes:• Right-of-way• Trafficlightsprogram

Given: a graph with only few informationNumber of lanes (often vague)Allowed speed (often vague)

MicroscopicRoadNetworksSizeandComplexity

Additionalproblems:• verylargenetworks• complexjunctions

Example: computation of lane-to-lane connections:

1. for each edge: compute turnaround edges2. for each node: sort each node’s edges3. for each node: compute each node’s type4. for each node: set edge priorities5. for each edge: compute edge-to-edge

connections6. for each edge: compute lanes-to-edge

connections7. for each node: compute lane-to-lane

connections8. for each edge: recheck lanes9. for each edge: append turnarounds

MicroscopicRoadNetworksSUMOSolution:Heuristicsfor

automaticcomputationAfter 2. After 5.

After 7. After all

TrafficDemandNeededInformation

Eachvehicleismodeledexplicitly

mandatoryattributes:

– ID(name)– Vehicletype(includingKrauß-parameter)– Completeroutethroughthenetwork– Departtime

optionalattributes:

– stops<vehicle id="bus100_west_0d" type="BUS" depart="0" color="1,0,1"><route>-572658025 -572658026 -572658027 -572658024 …</route><stop bus_stop="west1" duration="20"/><stop bus_stop="west2" duration="20"/>

</vehicle>

TrafficDemandPossibleSources

– Accuratebutsparse– Noinformationaboutwhoisdrivingfromwhichplacetowhichplace,onlyhowmanyvehicleshavepassedacertainplace

– Lessaccuratethaninductionloopsandsparse,too–mainlyforsomemajorinner-cityjunctions

– Informationaboutflowspreadonjunctions

– Evenlessaccurate(estimated),butcoveracompletearea

Real (physical) measures are done at induction loops

Counts at junctions may provide flows and turning ratios

Traffic scientists estimate demands on district level

TrafficDemandPossibleSources

DFROUTER SUMO-routesinduction-loopmeasures

JTRROUTER SUMO-routesturning ratios

flows

OD2TRIPS

trips

OD-matrix

DUAROUTER SUMO-routes

Real (physical) measures are done at induction loops

Counts at junctions may provide flows and turning ratios

Traffic scientists estimate demands on district level

SUMO- ModulesIncludedApplications

• SUMO:commandlinesimulation

• GUISIM:simulationwithagraphicaluserinterface

• NETCONVERT:networkimporter

• NETGEN:networkgenerator• OD2TRIPS:converterforO/D-

matrices• JTRROUTER:routerbasedon

turningratios• DUAROUTER:routerbasedona

dynamicuserassignment• DFROUTER:routerwhichuses

detectordata

SUMOFeatures

• Microscopic:allvehiclesaremodeledexplicitly• Time-discrete,space-continuouscar-followingmodelbyS.Krauß• Multi-lanetraffic,right-of-wayrules• Around100,000carsinreal-time(withoutgraphicaloutput)• Trafficlightswithtimeschedules,othertrafficmanagementdevices• Complexnetworks/Importsupport• DynamicRoutingbasedonDynamicUserAssignment• Otherroutingmodules

[2] Christian Gawron. 1998. “Simulation-Based Traffic Assignment”. Inaugural Dissertation.

2

1

[1] “Microscopic Modelling of Traffic Flow: Investigation of Collision Free Vehicle Dynamics”, S. Krauß, DLR (Hauptabteilung Mobilität und Systemtechnik), 1998, ISSN 1434-8454

ProjectsattheDLRwhereSUMOwasused

2002-2006• INVENTImplementationandverificationoftrafficmanagementstrategiesforlargeurbanareas

• OISVerificationofbenefitsarisingfromusageofnewopticalsensors

• TrafficTowerVirtualTrafficManagementEnvironment

• WJT2005/Soccer2006Integrationofstandardandairbornedetectorsintoatrafficportalwithforecastfunctionality

• TrafficOnlineTrafficsurveillanceviain-vehicleGSMphones

WJT2005/Soccer2006à DELPHIDescription

• UsedinthecityofCologneduring– Thepope’svisit(worldyouthday2005)– Theworldsoccercup2006

• Trafficsurveillanceusing– Highwayinductionloops– Inner-cityinductionloops– Airbornetrafficrecognitionsystem(mountedonazeppelin)

• Trafficvisualization– Integrationofgainedinformationintoaviewer– Presentationforthepolice

• Trafficforecast– 30minintothefutureusingasimulation(extendedSUMO)

DELPHISystemOverview

Floating Car Data:Induction loops:ARGOS:Access via db, webserver

Simulation:

• Areal extrapolation of measured data

• Forecast generation (30min)

• Fed from db using python

Datenbank:

• MySQL with InnoDB tables

• No built-in logic

Aggregation/Correction:

• Guessing missing values

• Data fusion• Done using python

scripts

Webserver:• Tomcat Servlet Container• Visualization (Images and traffic)

Webbrowser:• JavaScript Browser• asynchronous XML-

Requests

SUMO– ExampleResultsFlowComparison

CaseStudy

• Motivation:– Constraintsonaccessingthemobileusersrelateddata

– Producingthelogs- enablingnewpossibilitiesintheresearchfield.

– Vehicle-To-Everything(V2X)communication

IntroducingCellularNetworkLayerintoSUMOforSimulatingVehicularMobileDevices’InteractionsinUrbanEnvironment

*Siim-Toomas,Marran;Artjom, Lind;Amnir,Hadachi,“Introducing Cellular NetworkLayerintoSUMOforSimulatingVehicular MobileDevices'Interactions inUrbanEnvironment”, The4thInternational Conference onVehicleTechnologyandIntelligent Transport SystemsandControl Systems,Madeira,Portugal,March,2018.

CellularNetwork

• Basestation• Basestationtransmitter• Cells- signalcoverage• Userequipment- mobile

MobilityData

• Mobiletechnologies1Gto5G• Mobilitydata:

– CDR- likelogs– GPSdata– RFID– Wirelessaccesspointrelatedlogs– etc

Manyunstandardizedtechnologies

ChallengesinanalyzingCDRlogs

• SparseEvents• UnreliableCoverageMap• ChangesinCoverageMap• Featuresof2G/3G/4Gtechnologies

Contribution

• Researchofthemicroscopicroadtrafficsimulatorandcellularnetworktechnologiestodesignandmodelcellularnetwork

• Integrationofthecellularnetworkentitiesintotheroadtrafficsimulationsoftware

• Runningcommand-lineandvisualizetrafficsimulationwithintegratedcellularnetworksimulation

Contribution

Contribution:Supportprgrams

• HexagonGen• MobilityEventSimulationGenerator-MESGEN

Contribution:Classes• GUIandmicrosim:• Cellularantenna• Signalpropagation

• Cellulartower• Cellulartowercontroller• MobileandGPSdevices• MobileEventData• Dataimportandexport

Results:GPS

• Mobilemobilitylogs– GPSdata

Results:CDR

• Mobilemobilitylogs– CDR-like

• Eventtypes:– Callinitiation– Callreceiving– SMSsending– SMSreceiving– Webcommunication

Results:GUI

• Visualization:

SUMOTasksToDo

• Checkthereadingssectionincoursewebpage• Downloadandinstalltherightversionofsumoonyourcomputer.

• Trytorunittobereadyforthelabsession