Intelligent Transportation Systems and Infrastructure · Intelligent Transportation Systems and Infrastructure A series of briefs for smart investments March 2017, Page 5 of 11 AN

Intelligent Transportation Systems and Infrastructure

A Series of Briefs for Smart Investments

Rendering: Airspace over UC Berkeley Campus, provided by UC Berkeley’s Unmanned Autonomous Vehcles team

INTELLIGENTTRANSPORTATIONSYSTEMSANDINFRASTRUCTURE:ASERIESOFBRIEFSFORSMARTINVESTMENTSThelastdecadehaswitnessedanunprecedentedconvergenceofcommunication,control,andsensingthatcanpotentiallytransformtransportationinfrastructureanddelivery.Atthemostbasiclevel,efficientoperationandmaintenanceofournation’stransportationinfrastructurerequiresrealtimedataexchangeprovidedbyintelligenttransportationsystemtechnology.Whenimplemented,thesetechnologieshavethepotentialtorevolutionizethenation’seconomicvitalitybymovingpeopleandgoodsmorequickly,efficiently,safely,andatlowercosttoconsumers.Thefollowingbriefsoutlinekeypolicyandinvestmentopportunitiestosupportthatvision:

RoadsandVehiclesTheCaseforIntelligentTransportationSystemsforRoadsandVehicles................................2InfrastructureSupportforRoadVehicleAutomation..............................................................3NextGenerationRoadInstrumentationforHighPerformanceOperations............................4AirportsandAviationAnAirportSystemforthe21stCentury....................................................................................5InfrastructuralDesignforDronesinLowAltitudeAirspace.....................................................6ProjectManagementMajorInfrastructure:AvenuestoImproveCostEstimatesandImplementation....................7DataandBroadbandAResilientCyber-PhysicalInfrastructureforTransportation...................................................8ADataInstituteforNationalInfrastructureMonitoring..........................................................9InvestmentinBroadbandInfrastructureNecessaryforOverallInfrastructureResiliency.....10Low-LatencyBroadbandWirelessNetworksforIndustrialAutomation.................................11

ABOUTTHEINSTITUTEOFTRANSPORTATIONSTUDIESFornearly70years,sinceitsinceptionin1947,theInstituteofTransportationStudiesattheUniversityofCalifornia,Berkeley,hasbeenoneoftheworld'sleadingcentersfortransportationresearch,education,andscholarship.TheInstituteoperatesonanaverageof$25millioninresearchfundseachyear.Morethan100facultymembersandstaffresearchersandmorethan100graduatestudentstakepartinthismultidisciplinaryprogramorganizedintospecializedresearchcenterswithintheInstitute.CONTRIBUTORSAlexandreM.Bayen,Director,InstituteofTransportationStudiesShankarSastry,DeanofEngineeringJoeButlerAlessandroChiesaDavidCullerMarkHansenBenMcKeeverLauraMelendy

MichelleMoskowitzBorivojeNikolićBrandieM.NonneckeKristoferPisterJanRabaeyGireejaRanade

JasenkaRakasAnantSahaiStevenShladoverClaireTomlinKarenTrapenbergFrickTomWest

IntelligentTransportationSystemsandInfrastructure

AseriesofbriefsforsmartinvestmentsMarch2017,Page2of11

THECASEFORINTELLIGENTTRANSPORTATIONSYSTEMSFORROADSANDVEHICLESIntelligenttransportationsystemsandtechnologyprovideahighreturnoninvestment,especiallywhenincorporatedaspartofongoingconstructionactivities.EfficientoperationandmaintenanceofourtransportationinfrastructurerequiresrealtimedataexchangeprovidedbyITS(IntelligentTransportationSystem)technology.Thecosttoacquireandinstallthistechnologyisroughly5%oftheoverallconstructionbudgetifinstalledduringconstruction.TheROI(measuredinsafety,traveltimereliability,throughputandqualityoflife)takeslessthan6monthsinhighlycongestedcorridors.Inaddition,thesetransportationnetworksarenowreadytosupportadvancesinautomatedandconnectedvehiclesandinshareddemandmanagementapproaches.AllconstructionprojectsshouldberequiredtoinstallITSelements.TheseITSelements,aspecializedsubsetoftheInternetofThings(IOT),includecongestionsensors,structuralintegritymonitoring,fibercommunication,highresolutionvideo,vehicletoinfrastructuredataexchange,intelligenttrafficsignals,specialuselanemanagement,emergencyvehiclerouteclearance,safetyguidanceandmessagepresentation.ITStechnologyletsusknowwhatishappeningonourhighways,arterialsandbridgessothatwecanmanageandmaintainthem.Thistechnologyensuresmaximalreturnoninvestmentforthelargeinvestmentsrequiredtoexpand,upgradeandremediateourtransportationinfrastructure.Indetail,ITSTechnologyensuresthat:

• USinfrastructureisreadytosupportconnectedandautomatedvehicles,sharedservices,and,ifplanned,electrification.

• Thenationpracticesperformance-basedmanagement,ensuringthatcongestionisreduced,roadsare

safer,andthatallfutureconnectedandautomatedvehiclesdonotendupstuckinthesametrafficcongestionpatternsasconventionalvehiclesaretoday.

• Sufficientdataisavailabletounderstandtheactualperformanceofinfrastructureinvestmentsinorder

toensurethateveryfundedprojectlivesuptoitsadvertisedperformance.

• Infrastructureisproperlymonitoredinsupportofarobustmaintenanceprogram,sothat,movingforward,America’sinfrastructurewillneverdegradetothisextentordangerouslevels,everagain.

• DataisreadilyavailablethatallowscredibleassessmentofproposedPublic-PrivatePartnerships(PPPs),

andpropermanagementofPPPrevenuestreams.



INFRASTRUCTURESUPPORTFORROADVEHICLEAUTOMATIONMuchattentionhasbeengiventoautomationofroadvehiclesrecently,butthatattentionhasbeenalmostentirelyfocusedonthevehiclesthemselves,withoutregardtotheroadwayinfrastructureonwhichtheyoperate.Thedevelopersofautomatedvehicleshavebeenreluctanttoacknowledgetheirdependenceontheinfrastructurebecausedevelopersareconcernedabouthowtoensuredeploymentofaviablesystemifthepublicsector(i.e.publicroadsandhighways)failstodelivertheexpectedinfrastructureenhancements.Yet,theopportunitiesaregreatlyenhancedforvehicleautomationtoimprovethesafety,efficiencyandtrafficflowoftheroadnetwork(andtodeliverthoseimprovementssooner)ifthevehiclesandthepublicinfrastructurecanoperateasawell-integratedsystem.Therolloutofvehicleswithhigherautomationcapabilities(theabilitytooperatewithoutconstanthumansupervision)willalreadybegeographicallylimitedbecauseoftheneedforverydetailedandcarefullyvalidateddigitalmapsofallthelocationswheretheycanoperate.Ifthemappingofthoselocationsisaccompaniedbysuitablephysicalmodificationstotheinfrastructure,theautomationsystemswillbeabletodeliverhigherlevelsofperformanceandsafety,sooner,andwithlesscostlyin-vehicletechnology.Threedifferentcategoriesofinfrastructureenhancementsneedtobeconsidered:

• low-costelectronicandroadmarkingchangesthatcanbeappliedthroughouttheroadnetwork,• physicalchangestourbanroadstofacilitatetheirusebylow-speedautomatedvehicles;and• fullysegregatedlanesforautomatedvehiclesonhigh-speedfreeways.

Electronicandmarkingchanges.Theintegrationofvehiclesandinfrastructuredevicesintoawell-coordinatedroadtransportationsystemwillbefacilitatedbythedeploymentof5.9GHzDSRCcommunicationdevicesatkeylocationsthroughouttheroadnetwork,suchassignalizedintersectionsandfreewayinterchanges.Thesewillenabletwo-waycommunicationbetweenthevehiclesandtrafficmanagementsystemssothattheycanmaximizesafety,efficiencyandtrafficflow.Inaddition,thevisibilityofthepavementmarkingsandroadsignsneedtobeimprovedandstandardizedsothattheycanbemoreeasilyrecognizedbymachinevisionsystems(whichwillalsoimprovetheirvisibilityforhumandrivers).Physicalchangestourbanroads.Thefirstgenerationofurbanautomatedvehicleshavelimitedsensorycapabilitiesandarerestrictedtolowspeedsandenvironmentsinwhichtheirinteractionswithotherroaduserscanbephysicallyconstrained.Forthesevehiclestoprovideusefultransportationservices,theywillneedsomespecializedroadmarkings,curbs,signal-protectedcrossings,andbarrierstosafelyseparatethemfrommanuallydrivenvehicles,bicyclists,andpedestrians.High-speedfreewaychanges.Automationhasgreatpotentialtoimprovethesafety,efficiencyandtrafficflowoftrucks,busesandcarsonfreeways,butitsabilitytodeliverthesebenefitsisconstrainedbythedisruptionsandhazardsintroducedbyconventionalhuman-drivenvehicles.Providingphysicalsegregationbetweenthelanesusedbytheautomatedvehiclesandtheconventionalvehiclesovercomesthesehazards,enablingtheautomationsystemstodelivertheirbenefitsearlier,withouttheaddedcomplicationsintroducedbytheneedtosafelyaccommodatethebehaviorsofunpredictablehumandrivers.



NEXTGENERATIONROADINSTRUMENTATIONFORHIGHPERFORMANCEOPERATIONSBackground.ThecostofroadcongestioningrossGDPintheUSisinthebillionsofdollarseveryyear,mostlyduetoimpactsonservicesrelyingontransportation,andsecondaryeffectsassociatedwiththeinefficiencyofthetransportationnetwork.Mostofthetrafficoperationsonfreewayscangreatlybeimprovedwithinstrumentation.FormostcitiesintheUS,highwayinstrumentationdatesbacktothe1960s:loopdetectorsinthepavement.Mostofthesedetectorsareunreliable,andoftenfail(a40%failurerateiscommoninmostcities).Withtheexplosionofvideocamerasenhancedbytheexpansionofthemobilephoneindustry,theUSisenteringanewera,inwhichitcouldleadbyleapfroggingthecurrentstateoftheart.TheUScouldmovetofullycamera-basedoperations,asourcurrentcommunicationnetworkshavethepotentialtoprovideubiquitouscoverage.ThiswouldempowertheUSDOTandStateDOTswithunprecedentedcapabilities.Objective.WerecommendtheUSDOTprovideanewvideo-basedarchitectureforroadmonitoring.Thegoalofthearchitecturewillbetoprovideubiquitousvisualsensingofthefreewaynetwork,leveragingthealreadyexistingcommunicationnetwork(LTEandsoon5G).Byleveraginganexistingcommunicationinfrastructure,andwiththerapidlydecreasingcostsofcameras,thepotentialforrevolutionizingtrafficoperationswiththisnewmonitoringisenormous.Artificialintelligence(inparticulardeeplearning)hasprovidedprocessingcapabilitiesthatcanallowpublicagenciestobenefitfromthevastamountsofdataenabledthroughthisarchitecture.Approach.Weproposedefiningthearchitectureofanewgenerationmonitoringsystembasedonlow-costcamerasconnectedtotheexistingcellularnetwork.ThisapproachwillbuildontheverysuccessfulNGSIMpilotdevelopedbytheUSDOTmorethan10yearsago,inwhichhighfidelityvideodatawascollectedandshowntoprovidethemostinsightfulfeaturesaboutroadtrafficinthelastdecade,duetoitsrichnessandquality.Takingtheoriginal“pilot”tothenextlevel,wewillpushtheNGSIMparadigmtoubiquity,real-timeandstreamingdata.Wewillbuildtheproperreal-timeprocessingenginestosupportoperationsrelyingonthisdata.Wewillwritespecificationssothedatacanbeusedbyreal-timedecisionsupportsystemsintrafficcontrolcenters.Expectedimpact.Theimpactsofthisinfrastructurewillbe(1)moreefficientoperationsonaregularbasis;(2)increasedefficiencyofthetransportationnetworkleadingtoreductionincostsofcongestion(3)moreresilientinfrastructureinthefaceoflargescalenaturaldisruptions(hurricanes,snowstorms,floods,heavyrains),andbettermanagementofbothanticipatedandunanticipatedeventssuchascityevacuations(NewOrleansetc.);(4)nationalsecurity:withubiquitousmonitoringofthemajorfreewaysandthebackboneofthetransportationnetwork,ournationalagencieswillbebetterinformedofthreatsandresponsesinrealtime.



ANAIRPORTSYSTEMFORTHE21STCENTURYThesorrystateofAmerica’sairportshasbeenwidelyobservedbypoliticalleaders,journalists,policyanalysts,engineers,andscholars.Mostimportantly,inconveniencesareexperienceddailyby2.2milliontravelers.Renewingthenation’sairportswillatonceimprovethetravelexperience,reduceflightdelays,improvesafety,anddemonstrateourcommitmenttoaninfrastructurebefittinganadvancedeconomy.Carefullydesignedpolicies,plans,andprogramstorenewthenation’sairportinfrastructurecanaccomplishfarmorethanproducegleamingterminals,expandairfieldcapacity,andimprovegroundaccess.Ourgoalmustnotbetomatchworld-renownedbutrapidlyobsolescingairportssuchasSingaporeChangi,TokyoHaneda,orMunich,buttoleapfrogthembybuildinganairportsystemforthe21stcentury.Suchasystem,whilestillaccommodatingtheairtraveloftoday,mustalsoallowforemergingvehicletypes,newbusinessmodels,andeaseofusebyanagingpopulation.Itmustberesilienttocontemporarynaturalandmanmadethreats.Itsinfrastructuredesignmustbemore‘elastic’andeasilyre-configurableinordertoutilizelatentcapacityoftheexistingairportlayouts,giventhatmostairportsinurbanareascannotphysicallyexpandtheirinfrastructure.Ithastobebuiltinthemostcost-efficientmanner,usingconstructionmaterialsthataredurable,smart,andenergyefficient.Finally,itmustbemanagedandfinancedinamannerthatadaptsbestpracticesfromaroundtheworldtotheUSsetting.A21stcenturyairportsystemmustfullyintegrateunmannedairvehicles(akadrones).Notonlymustcurrentrestrictionsonoperationsnearairportsbeeliminated,theairportsmustalsoallowforconnectivitybetweenconventionalaircraftflyinglongerroutesanddronesprovidinglocaldelivery.Whilesuchlocaldeliverieswouldinitiallyinvolvecargo,itislikelythatoverthelifetimeoftheseairports,thetechnologywillprovesufficientlyreliabletopermitpassengeraccessaswell.Othermodelsofaccessincludingtheburgeoningride-sharesector,whichmayalsofeatureflyingcarswithinthenextdecade,mustalsobeaccommodated.Inadditiontopermittingsuchservices,thefutureairportsystemshouldbenefitfromthembyenablingflightoperatorstochangearrivalanddepartureairportsinnear-realtimeinresponsetoemergenciesordemand-capacityimbalances.RisingsealevelsposeasubstantialthreattomanyUSairports.Thirteenofthenation’slargestairportsarepronetofloodingasaresultofamoderatetoseverestormsurge.Increaseddensityandintensityoflightningstrikes,whichcausephysicaldamageanddisruptoperations,poseanotherthreat.Investmentstofortifyairportsagainstthesehazardsandinsystemsforeffectivelyrespondingwhendamagedoesoccurdeservehighpriority.Flightdiversionstrategiescanbeenabledbyahighlyadaptivesystemforairportaccessandegressthatride-shareservicescanprovide.Otherinnovativeapproaches,suchasfloatingrunwaysstabilizedbyadvancedcontrolsystems,shouldalsobeconsidered.Finally,inaddressingterroristicthreats,thefocusmustshifttothesafetyandsecurityoftheentireairportsystem,ratherthanjustterminalbuildings.A21stcenturyairportsystemcanbeprivatelyfinancedandrepaidfromuserfeesinurbanizedareas,althoughsupportfromthepublicsectormayberequiredelsewhere.Looseningofrestrictionssuchascapsonpassengerfacilitychargesandlimitsontheuseofmarketmechanismstoallocatecapacitycanincreaserevenuestreamsandsupplantobsoletechargingsystems(forexample,weight-baseduserfees).Amajorrationaleforeconomicregulationandpublicsectorcontrolofairportsisthethreatofmonopolisticbehavior,whichmaynolongerbevalidinmanyregions.ThecompetitiveLondonairportmodel,inwhicheachairportisunderseparatemanagement,isworthyofconsideration.Whilegovernmentoversighttoassuresafety,protecttheenvironment,maintainflightoperatoraccess,andpreventmonopolisticexploitationinsomeareasmaystillbeneeded,substantialderegulationwillenergizeairportdevelopment.



INFRASTRUCTURALDESIGNFORDRONESINLOWALTITUDEAIRSPACETherehasbeenanimmensesurgeofinterestinusingunmannedandmannedautonomousvehicles(UAV)forcivilapplications.ThroughprojectssuchasAmazonPrimeAir,GoogleProjectWing,andAirbus’sProjectVahana,manycompaniesareinvestingheavilyintodroneservicessuchascommercialpackagedelivery,flyingtaxiservice,aerialsurveillance,emergencysupplydelivery,videography,andsearchandrescue.OthercompaniesinvolvedindronedevelopmentincludeAirware,IrisAutomation,andUber;inaddition,thismovementtowardsdroneshasbeenhappeningworldwide,intheUS,Canada,China,andmostrecentlytheUAE.ThereiscurrentlyatremendousandrapidlygrowingcommercialmarketfordronesintheUSandglobally.Sincedronesareenvisionedtoflyinthelowaltitudespaceofabout200to500feet,theallocationofthisairspaceresourcemustbedonecarefullytomaximizesafety,privacy,efficiency,andeaseofhumanparticipation.Asaresult,newinfrastructuresareneeded.Weproposetodeveloptoolsforgovernmentagenciestoestablishsuchinfrastructuresinaprincipledway.OurtoolswillrelyonacombinationofsystemsanalysisandpubliclyavailabledatafromsourcesincludingNASA,FAA,ArcGIS,andNOAA.IncollaborationwithNASAAmesandArmstrongFlightResearchCentersinrecentyears,wehavebeendesigninglowaltitudeairspaceinfrastructure.Wehaveproposedtheconceptofairhighways,orvirtualpathwaysintheairspace.Airhighwaysprovideascalableandintuitivewayformanagingalargenumberofdrones.Thesepathscanbeupdatedinreal-timeaccordingtochangesintheairspace.Trunksandbranchesofairhighways,similartoground-basedhighwaysystems,naturallyemerge.Forregionalandcity-leveldroneinfrastructure,thenextsteptowardsacompleteandpracticalUAV,infrastructurewouldbetoconsidermultiplelevelsofairhighways,possiblyseparatedbyaltitude.Thegoalsinthedesignofthesehighwaynetworksincludeconnectivitybetweencities,efficientandsafeuseofdifferentaltitudelevels,andflexibilitywithrespecttounknownorchangingconditionsintheairspace.Manypracticaldetails,suchasthelocationsofandrulesforintersectionsandexits,needtobedesigned.For“last-mile”droneplanning,onepotentialsolutionwouldbetouseapriority-basedmethodforreservingspace-timeforeachdrone.However,unliketraditionalrouteplanningmethodsthatreservealargeblockoftheairspaceforalongperiodoftime,webelievethatadoptingafine-grainspace-timereservationwouldgreatlyimprovethroughput.Last-mileoperationswillinvolvedronesflyingincloseproximitytohumansandotherimportantassetsontheground.Therefore,real-timedatawillbeessentialforassessingrisksofflightroutes.Dataneededbydronesanddroneoperatorsforplanningincludecityzoningmaps,whichprovidepriorsforhumanoccupancy;cellulartrafficdata,whichcanbeusedtoinferhumanoccupancy;androadtrafficdata,whichisusefulforpredictingday-to-dayhumanmovement.Wewilldevelopcomputationalalgorithmsthatprovidewaysofestablishingtheselevelsofinfrastructure,alloweaseofrestructuringwhennecessary,andprovideinterfacesbetweenthedifferentlevels.Wewilltakeinspirationfromcurrentairtrafficcontrolprotocolsandroadnetworks,butdesignthelowaltitudeairspaceinfrastructureinaprincipledandautomatedwaythataccountsfordatasuchasterraindatafromNASAJPL,populationdensitydatafromArcGIS,andwinddatafromtheNOAA.Theintendedcustomersofthisinnovationandassociatedsoftwareareanyinstitutionsthatneedtoestablishlowaltitudetrafficrules,ormonitorthestatusofairtraffic,includinggovernmentagenciesaswellascompaniesusingtheinfrastructure.



MAJORINFRASTRUCTURE:AVENUESTOIMPROVECOSTESTIMATESANDIMPLEMENTATIONEmbeddedinpublicpolicyproposalsfornewinfrastructureprojectsisanoptimismthatinfrastructurecanbedeliveredquickly,ontime,andonbudget.RecenthistoryofmajorinfrastructureprojectsintheUnitedStatesandworldwide—oftencalled“megaprojects”—tellsusthatthiscouldnotbefurtherfromthetruth.Projectstakelongerthanexpectedandconstructioncostsarehigherthananticipated,evenforprojectsthatappear“shovelready.”Projectsponsorsalsoestimatefinancingcostsdecadesinadvanceofprojectcompletionandtypicallydonotadequatelypublicizethesecosts,whichcandoubleestimates.Large-scaleinfrastructureendeavorsoftenhavecharacteristicsidentifiedbyKarenTrapenbergFrickinherrecentbookonthenewSanFrancisco-OaklandBayBridgeasthe“7C’sofMegaprojects.”1Theytendtobecolossal,costly,captivating,controversial,complex,ladenwithissuesofcontrolbetweenkeyactors,andinmuchneedofcommunicationbetweenkeyactors,themediaandthepublic.Thesecharacteristicscomplicateprojecttimelines,costestimates,andotheroutcomes.Avenuesforperformanceimprovementareto:

• Improvecostestimatingmethodsbycomparingtheprojectunderconsiderationstatisticallytonumeroussimilarprojects,particularlytheircostanddeliverytimelines;and,includingsufficientcontingencyestimates.GovernmentsandresearchersintheUnitedKingdom,EuropeanUnion,AustraliaandtheAsia-Pacific,looktothismethodcalled“referenceclassforecasting.”2Augmentthisanalysiswithdetailedcomparisonsoftransactioncosts,suchasfinancing,legal,right-ofway,andenvironmentalprocesses.

• WorkwiththeStatestoevaluatethepotentialforcentralizinginfrastructuredeliveryand

financing.Intandem,thefederalgovernmentshouldevaluateadditionalstepstoimproveuseofriskanalysis,independentexternaloversight,andpeerreviewofprojectsacrossinfrastructuretypesoratleastwithinonesectorsuchastransportation.

• Establishaclearinghousewithdetailedinformationthatwouldallowforrigorouscomparative

analysisofindividualprojectcosts,riskmanagement,peerreviewprocesses,andprojectdeliverymethodsofforthcomingprojects.Then,theUnitedStatescouldlearnfromitsexperienceswithmajorinfrastructureinvestmentandimproveandinnovateinfutureefforts.

• Considerapilotprogramtoincentivizetheestablishmentof“innovationdevelopmentcenters”

withinprojectsandleadershipacademies.Thesewouldfocusonspurringinnovationsandimprovingpublicagencystaffcapabilitiestoefficientlydeliverprojects,inpartnershipwithprivatesectorinvestors.Fundinginpartcouldcomefromindustrypartners,ashasoccurredwithLondon’sCrossrailmegaproject.

1TrapenbergFrick,K.2016.RemakingtheSanFrancisco–OaklandBayBridge:ACaseofShadowboxingwithNature.Oxfordshire:Routledge;forotherexamples,seePoole,R.andP.Samuel.2011.TransportationMega-ProjectsandRisk.ReasonFoundationPolicyBrief,February2011.2Cantarelli,C.C.andFlyvbjerg,B.,2013.Mega-Projects'CostPerformanceandLock-In:ProblemsandSolutions.InPriemus,H.andvanWee,B.TheInternationalHandbookonMega-Projects.Cheltanham,UK:EdwardElgar.



ARESILIENTCYBER-PHYSICALINFRASTRUCTUREFORTRANSPORTATIONBackground.Inthelasttenyears,allkindsofinfrastructureandproductshavetremendouslyincreaseduseofembeddedwirelesssensordevices,oftenreferredtoastheInternetofThings(IoT)orNetworkEmbeddedSensorsTechnology(NEST).Streamingdatacollectedbythesesensorscanbeanalyzed“inthecloud”usingadvancesin“machinelearning”toprovideanalyticsfornewservices,suchasridesharing,routeandtrafficmanagement,autonomousandsemi-autonomouscarsandtrucks,andfleetmanagement.Thedevelopmentofthis“cyber”heartofthetransportationinfrastructureisoneofthemainsocietalchallengesofourday.Itisalsotheenablerofthe“sharingeconomy”fortransportation,whichhasalreadycreatedinnovativecompanies,suchasWaze,Uber,Lyft,andLyft.Objective.Whilewearealreadyseeingpartsofthecyber-physicalinfrastructurecombininganalyticsinthecloudwithIoTsensorbigdata,thereareseveralchallengesasitrelatestothesafetyofsocietal-scaletransportationsystems:1. Difficulttobuildandconfigure.Large-scalecyber-physicalsystemsneedtobebuiltbyhandandthen

testedlaboriouslyforcorrectness.Weneedmoreautomatedmethodsforbuilding“correct-by-construction”large-scaletransportationsystems.

2. Faulttolerance.Withlargenumbersofsensorsinthewild,itistobeexpectedthatsomeofthemwillfail.Weneed,nonetheless,toguaranteethatthepropertiesandextractedanalyticsareaccurateevenunderfaultedconditions.Inparticular,weneedthetransportationinfrastructuretofunctioneveninthefaceofnaturaldisasterssuchaspartialflooding,andotherinclementweather.

3. Cybersurvivability.Eachnewcyberinfrastructureintroducesnewpotentialvulnerabilitiestocyber-attack.Bybuildingataxonomyofattacksanddefenses,wecancreateatransportationcyberinfrastructurethatisnotonlycapableofwithstandingattacks,butalsohasstrongsecurityandintrusiondetectionsystemstodeterattacks.

4. Learning.Withanumberofartificialintelligence,deeplearning,andadaptivelearningalgorithmsinvariouselementsofthetransportationinfrastructure,wewillneedtoprovidehumanuserswithaconsistentviewoftheautomation,whilesimultaneouslyprovidingtheautomationwithaconsistentviewofhumanbehavior.

Approach.Theapproachwerecommendismulti-disciplinary,combiningthebestofinformationandcommunicationtechnology,withcybersecurityandhighconfidencedesignattributes.“Highconfidencedesign”istheabilitytobuildsystemsthatarecorrectbyconstruction,faulttolerant,andresistanttocyberattack.Amodel-baseddesignmethodologytodevelopdesigntoolsandsoftwareiscriticalforallstakeholderstodevelopandevaluatenewdesignsinaso-called“softwarewindtunnel.”Buildinghighconfidenceintotheoperationoflearningisanothermajordesignchallengeforsystemsdesign,whichspansmodel-basedanddata-drivenapproachesofdeeplearning.Intheconstructionofsocietal-scalecyber-physicalsystems,thedesignofmechanismstotakeadvantageofnewanalytics(e.g.,exampleGoogleMapsornewparkingappsonsmartphones)iscriticaltoguaranteefairness,transparency,andaccessibilitybysocietalstakeholdersforevaluation.Inparticular,wewillneedtoprovideopt-inprivacymetricstoallowindividualuserstochoosetheirlevelsofcomfort.Mechanismdesign,includingreal-timepricing,isasophisticatedprocessinvolvinganassessmentofsocialjusticeandotherqualitativeissues(ofakindwhicharealreadyencounteredwithsimplecongestionpricing).Expectedimpact.Acyber-physicalinfrastructureisthekeyenablerfordeterminingthefutureofmobility,usingridesharing,semi-automatedcars,parking,andothernewservicesthatsupportsocietalefficiencywhileenablingprivacy,securityandresiliencyoftheinfrastructure.Thedevelopmentofthiscyberinfrastructurewillalsofostercreationofnumerousstart-upsandsmallbusinessesbothonaregionalandnationallevel.Hugemultipliersfromrobustandsmartfederalinvestmentcanresultinaresilientinfrastructurethatwillbebothefficientandaneconomicsparkplugforthenation.



ADATAINSTITUTEFORNATIONALINFRASTRUCTUREMONITORINGBackground.Globally,thelastdecadehaswitnessedanunprecedentedconvergenceofcommunication,control,andsensinginsingleplatformssuchassmartphones,sensornetworkstoequipvariousfacilities,andvehicles.WithnewparadigmssuchastheInternetofThings,“theswarm,”precisionmonitoringofnationalinfrastructureisnowpossible,asnewinfrastructureisbuilt,orexistinginfrastructureisupgraded.Inmanycases,thisdataiscollectedalready,andinothers,thecostofdeployinginfrastructuretoperformmonitoringcomesatafractionofthecostofconstruction.TheUScouldgreatlybenefitfromtheleadershipofanationalinfrastructuremonitoringinstitute,withthemissionofleadingthenation’seffortstomanageitsinfrastructurebetter.Objective.TheInstituteforNationalInfrastructureMonitoringwouldhaveseveralmissions.Itwouldassembletheleadingengineers,policymakers,electedofficials,operationalagenciesintheUSaroundanambitiousagenda:(1)definetomorrow’smonitoringinfrastructureforbridges,dams,buildings,roads,tunnelsandotherassetsofvaluetothenation;(2)writeimplementationplansforhowthisnewlayerofinfrastructureshouldbedeployedaswerebuildournation;(3)devisedataanalyticsstrategiestoequipthebackendcomputersystemsthatwillmanagetheinfrastructuredata;(4)inventthetoolsthatwillenablepolicymakerstomakemoreefficientdecisionsbasedondata,forexamplewhentoreplaceapartofabridge,whentoinspectinfrastructureafternatural(orman-made)disruptions,etc.Approach.TheproposedInstitutewillbeledbytopengineersintheUSwhohaveatrackrecordofbuildinglarge-scalemonitoringsystems(i.e.engineersfromsuccessfulUScompanies,civilengineers,systemsengineers,etc.).Theseexpertswilldefineatechnologyagendatomakeournation’sinfrastructure“smart.”Theywillbuildaroadmapofpriorityassetsthatshouldbeinstrumented,andguidethepublicagenciesinrecruitingtheproperexpertstodoit.Itwillassistwiththedirectionsthedataanalyticsshouldtaketoprovidethemaximalvaluetothepublicagenciesinchargeofoperationsfortheseassets.Expectedimpact.TheimpactoftheInstitutewillbemanifold.Itwillprovidecriticalguidancetopublicagenciesandelectedofficialswhenexpertiseisneeded(e.g.,testimony,decisiononapproachestotakeforinfrastructure).Itwillprovidepolicyrecommendationswithconcretequantificationofrisk-benefitstradeoffs(“howmuchfinancialbenefitisgainedbytheagencytoupgradeoneassetvs.another,andatwhatrisk?”).TheInstitutewillprovideaglobalviewofthestateofourinfrastructuretoourleadersinreal-time.Itwillprovidetheproperanalyticstoolssoanticipatorypolicycanbedevised,i.e.,usingforecastmodels,tounderstandwhenactionsshouldbetakeninthefutureforinfrastructuremanagement.



INVESTMENTINBROADBANDINFRASTRUCTURENECESSARYFOROVERALLINFRASTRUCTURERESILIENCYBackground.Advancesininformationandcommunicationtechnologies(ICTs)holdgreatpromisetoenableefficient,cost-effectiveinfrastructuresystemsandservicesthatresultinlong-termresiliency.IntelligentinfrastructureenabledthroughincorporationoftheInternetofThings(IoT)--softwareandsensorsembeddedinphysicalinfrastructure(e.g.,bridges,roads,railways,dams,electricalgrids)andconnectedtoanetwork--arecentraltoournation’sabilitytohandlecurrentandfutureinfrastructuredemands.High-speedwirelineandwirelessbroadbandinfrastructureiscriticaltotheperformanceandimpactofthesedata-centricsystems.Assuch,itshouldbeconsideredacorecomponentofUSinfrastructure,vitaltooverallresiliency.Objective.IntelligentinfrastructureutilizesICTstomonitor,predict,andrespondtochangingdemands,environmentalimpacts,andstructuraldegradation.Proactiveandpredictiveinsightsgleanedthroughdatacollectionandanalysisleadtounprecedentedefficiencygains.Forexample,researchersatUCBerkeleydesigned,tested,andvalidateduseofawirelesssensornetworktocollectambientstructuralvibrationsontheGoldenGateBridgetomonitorstructuralchangesofthebridgeunobtrusivelyandatalowercost.EfficiencygainsarenotonlyfoundfromapplicationofICTswithinasector,butcanalsobeidentifiedacrosssectors.Infrastructuresystemsareinterconnected.Sustainablecommunitiesareenabledwheninsightsfromtransportationdemandsareusedtodetermineenergyconsumptionneedsandrenewablealternatives.Healthycommunitiesareenabledwhenwatercanbeconservativelyallocatedwhilemaximizingagriculturalproductivity.Thesecross-sectorinsightsrequireempiricalandappliedresearchenabledthroughtheinstrumentationofinfrastructure,datainteroperability,andaccesstohigh-speednetworks.Approach.Intelligentinfrastructureenablesreal-timemonitoringofthestructuralhealth,changingdemands,andenvironmentalimpactsofpublicinfrastructure.Weproposethatfederalinfrastructureinvestmentsincludewirelineandwirelessbroadbandinfrastructureandsupportcross-sectorresearchtovalidateintelligentinfrastructurestrategies,tools,models,anddatacollectionandsharingprocesses.Additionally,researchontaxincentivesandmodelsforcity-levelreadiness(e.g.,permitstructures,accessrightstoconduits/poles,broadbandconduitinstallationinhighways,instrumentationofinfrastructure)shouldbesupportedinordertobetterensureresilientinfrastructuredevelopmentnationwide.Expectedimpact.Intelligentinfrastructureenabledthroughthenationwidebuildoutofhigh-speedwirelineandwirelessbroadbandnetworkswillstreamlineinfrastructuredevelopmentandmaintenance,reducedeleteriousenvironmentaleffects,andpromoteeconomicgrowthandthesafetyandwellbeingofcommunities.Mostimportantly,itwillstretchandmaximizethebenefitsofeachfederaldollarinvestedinneworimprovedinfrastructure.



LOW-LATENCYBROADBANDWIRELESSNETWORKSFORINDUSTRIALAUTOMATIONBackground.Modernautomaticcontrolsystems,suchasintra-vehiclecommunicationsandimmersivecomputingapplications,requirethecommunicationdelaysbetweenthestimulusandtheresponsetobeontheorderofmilliseconds.Thisrequirementcomesfromthestabilityofcontrolloopsandhumanperception.Industrialsystemsarelargelyimplementedusingphysicallywiredsystemstoachieveanultrahighreliability(1in109errors)specificationalongwiththelow-latency.However,wireshaveproblemsoftheirown—theyandtheirassociatedconnectorspresentrobustnessissuesinindustrialenvironments,andaddweighttocars,airplanesandrobots.Objective.Weproposethedevelopmentofascalableandsecurenetworkofwirelessmotesthatsupporthighreliabilityandguaranteedmillisecondlatencies.Theproposednetworkemploysrelayingstrategiestoprovidemultiplepathsfordatatomakeitswayfromthecontrollertotheactuators,increasingreliability.Thesenetworkscanenablecommunicationandcontrolbetweenvehiclesinplatoons,aswellasotherdevicessuchasautonomousdrones.Furthermore,theintroductionoffastandrobustwirelessconnectivitywillincreasetheflexibilityforinnovativemanufacturerstointroducenewproductsoradaptexistingdesigns.Weproposedevelopingprotocolsthatcanharvestdiversity,time-synchronizednetworking,localcaching,efficientandfasterror-correcting,code-baseddiscovery,andnetworkcodingtomeettherequiredlatency.Theresultingshortdatapackets,containingreadingsfromsensorsorcommandstotheactuators,suchaspositionandvelocitywillreachthedestinationinguaranteedsub-millisecondtime.Approach.Therearemultiplelayerstothedevelopmentanddeploymentofthesenetworks.First,weproposeadoptingspecificationsfromwiredindustrialnetworksandautonomousdrivingasbenchmarks,andtodevelopwirelessprotocolstomeetthem.Wewillmimictheend-to-endperformanceofawirednetwork(suchasindustry-dominatingSERCOSIII)intermsoflatencyandreliability.Theproposedsystemisbasedonaninformation-centricswarmofdevicesatthefringethatutilizeascheduled(TDMA)MACwithsimultaneousrelayingtorealizedeterministiclatencies.Theenvisioneddistributedsynchronizationisresilienttonetworkoutagesbyleveragingwirelessredundancy.Thenetworkwilladdressdynamicconfiguration,includingrapiddiscovery,byrelyingonnetworkcodingasamechanismforreliablecontentdeliverywithouttheneedforfragileroutingtables.Wewilladaptstate-of-the-artmachinelearningandartificialintelligencetechnologiestobecompatiblewiththecommunicationandcontrolframeworks.Thiswillrequireare-thinkofthetraditionalarchitecturesforcommunicationnetworks—thecontrolandreal-timenatureoftheapplicationwillhavetobeconsidered,andcross-layerdesignmayprovebeneficial.Wewillfurtheraimtoprovideprovableguaranteesontheperformanceofthenetworkandprotocol.Todemonstratethefeasibilityofourapproach,wewillbuildanetworkofmotes,builtonourownopen-sourceprocessorsrunningareal-timeoperatingsystem,augmentedwithcustomradiobasebandsthatenablelowlatencywithrelayingcapabilities.Expectedimpact.Withtheriseofincreasinglyintelligentvehiclesandtransportationinfrastructure,thereisaverylargemarketfortechnologiesthatspeedupthedevelopmentanddeploymentofsuchintelligentlyinteractingsystems.Industrialcontrolisanotherverylargemarket,andforbothofthese,communicationiscritical.Makingcommunicationwirelessdramaticallysimplifiesdeploymentofintelligenceintomanufacturingandtransportation.Forexample,low-latencywirelessnetworksenabledramaticweightreductioninaerialandlandvehiclesandtheirinteractionwiththetrafficinfrastructure.Theyalsoenableoperationofsystemswithahumanintheloop,embeddedinareal-timesystem,withnoperceivedlagbytheuser.Beyondtransportationandmanufacturing,thisisimportantinenablingdiverseareassuchastelemedicine,telepresence,entertainment,andgaming.

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Intelligent Transportation Systems and Infrastructure · Intelligent Transportation Systems and Infrastructure A series of briefs for smart investments March 2017, Page 5 of 11 AN