大陆汽车-AI 赋能零事故愿景-汽车安全的未来- Quo Vadis Vision Zero The future of vehicle safety – Can AI enable“Vision Zero”2024

TheFutureinMotion

QuoVadisVisionZero

Thefutureofvehiclesafety–CanAIenable“VisionZero”?

Dr.CorinaApachiţe,Dr.PiaDreiseitel

ContinentalAutomotiveTechnologiesGmbH

ContinentalAutomotive

AIandVisionZero-Overview

Introduction

Ishumanerrorstillthemainreasonofaccidents?!

AIapproachesforADASandADtoovercomehumanfailure ButcanwetrustAImodelsandtheirsafetyandsecurity? Keytakeawaysandoutlook

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AIIsTransformingTheAutomotiveIndustry…

…notsurprisingly…butprofoundly…andnecessarily

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ArtificialIntelligence@Continental

Continental’svisiononAI:TheAI-empoweredCompany

Increaseproductivitythrough

AIautomationanddatadrivendecisions

AI-empoweredEmployee

KeepandincreaserevenuesthroughAI-enabledproductsandservices

AI-empoweredMobility

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TransformationasModusOperandi

IntegratingAIinallareasofactivity

Transformationin

BUSINESS

Transformationin

PRODUCTS

Transformationin

PROCESSES

Transformationin

CULTURE

,SW-definedVehicle,Valueshift

,Speed,agilityandefficiencyarekey

,Valuecreationasdriver!

,Complexity,Interface

,Horizontal/Vertical

AI-empoweredCompany

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DevelopmentofAITowardsAutomatedDriving(AD)

ContinentaI’sExperience

,2012:1stTier1

AutonomousDrivinglicenseinNevada

,2017:Multi-FunctionCameraMFC500;DeepLearningin

,2020:

,2023:ChildPresenceDetection;extensionofDigitalAccess

SolutionCoSmA(2021)

,2023:AuroraCollaborationL4AutonomousTrucking

,GuidelinesforEthicalAI,AIClusterinFrankfurt

,2016:DriverlessShuttleCUbE(ContinentalUrbanMobilityExperience)

production

2012

2015

2018

2024

2021

,2016:AI&RoboticsLabsfounded

,2016:ResearchCollaborationwithUniversityOxfordinAI

,2022:AILabinBerlin

,2018:AICenterBudapest,2020:CorporateLab

@NTUSingapore

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VisionZeroreferstovariousapproaches

thatcombinethegoalofpreventing

accidentsandinjuriesaswellashumanillnesses.

ImageContinentalAG

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ArtificialIntelligence-aDefinition

“Acomputerwoulddeservetobecalledintelligentifitcouldtrickahumanintobelievingthathe

himselfisahuman."

AlanTuring

Englishcomputerscientist(1912-1954)

ImageWikipedia

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HistoryofVisionZero

ProgressbasedontheexampleofGermany

Technologicalinnovationsincreasedroadsafety

›Introductionofseatbeltsandairbags:reducingtheconsequencesofaccidents.

›Crashtesttechnology:Advancesinvehicledesign

havesignificantlyimprovedoccupantsafety.

›SystemssuchasESC(ElectronicStabilityControl)andAEB(AutomaticEmergencyBrakingSystem)helptoavoidcriticalsituationsandreduce

accidents.

›Regulatorychanges(speedlimit,alcoholmisuse)helptoavoidaccidents.

WithAI,roadsafetycanbeimprovedinanetworkDriver–Vehicle–Environment.

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ABS

Airbag

ESC

AEB

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AIBuildingBlocksTowardsAccident-freeMobility

Humanerroristhemainreasonforsevereaccidents

RootcausesforaccidentsinGerman2023(*

›Errorswhenturningorenteringaroad(15.3%)›Failuretorespecttherightofway(13.4%)

›Insufficientsafetydistance(12.9%)

›Inappropriatespeed(11.4%)›Incorrectroaduse(6.9%)

›Influenceofalcohol(4.5%)

›Misconducttowardspedestrians(4.3%)›Overtakingerrors(3.5%)

›Other(27,9%)

Humanerroristheleadingcauseofseriousaccidents–technologiessuchasdriverassistancesystemsarecrucialtominimizetheserisks.

(*StatistischesBundesamt,„TrafficAccidents,“2024.[Online].Available:

https://www.destatis.de/EN/Themes/Society-Environment/Traffic-Accidents/_node.html.[Zugriffam

25August2024].

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SafetyDependingonRoadUsage

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FailuresADASandCurrentADSystemscanAddress

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AIApproachesforADASandADtoOvercome

HumanFailure

(Examples)

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AIModulesforanAccident-freeMobility

Empowerdriver–vehicle–environmentthroughAI

AIfordrivermonitoring,cabinsurveillanceandbetteruserexperience.

AIforsafeassistedand

autonomousdriving

functions.

AIforamoreintelligent

infrastructure.

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PoseDetection&PedestrianPrediction

Overview:tracking,pose/gazedetection,pathprediction

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BehaviorPredictionforPedestrians

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PoseDetection&PedestrianPrediction

Longtermtracking

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CaseStudy:3DObjectDetectioninDataLoop

HowcanweimproveourAImodelinahighly-automatedway?

〉ADVehiclehastoperceiveandunderstanditsenvironment:

〉Whereisitsafetodrive?

〉Wherearetheothertrafficparticipantsandwhatistheirintent?

〉MagnificentprogressoverrecentyearsusingAImodels

〉Forthisstudywefocusedonan3DObjectDetectionModel(DETR3D)

〉PresentedResultsdirectlytranslateintofullADsystemarchitecturesandserialdevelopment

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FailuresADASandCurrentADSystemscanAddress

Rarecasesarenotrare!

Sohowcanwegetthatdata?

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Highly-AutomatedRetrainingPipeline

Efficientlyinjectreal-worlddataintotheAImodel

Annotation

EdgeCaseSelection

ModelRetraining

AdaptiontheAImodeltospecificrequirementsneeded:

›differentsensors

›changingODD(inalldimensions)

›limitedbyavailabilityofhigh-qualitylabeleddata.

Goals:

•Reduceamountofdataneededtoimprovemodel

•Reducecost-intensivelabellingeffort

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Highly-AutomatedRetrainingPipeline

Efficientlyinjectreal-worlddataintotheAImodel

CorePrinciples:

〉Selectmostinformativedata(subset)fromlargeamountofdatainanunsupervisedmanner(ActiveLearning)

〉OfflineProcessingofdatafromvarioussensors,alsoovertime,allowsforsophisticateddetectorapplication,producingpseudoground

truthlabels

〉CompareAuto-AnnotationagainstModelPredictions〉Collectedgecasesbasedonscoringfunctions

〉Automatedtriggeringofmodelretraining(e.g.,with2500collectedframes)

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ButWhatifThisStillisnotEnough?

https://www.oconnorpersonalinjury.com/car-accident-injury-road-debris/

https://www.oconnorperso

/car-

accident-injury-road-debris/

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ButWhatifThisStillisnotEnough?

oconnorpersonalinjurydebris/

Canwesystematicallygeneratenewtrainingandtestdata?

https://wwwoconnorperso

nalinjurycom/car-

accidentinjuryroaddebris/

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CreationofEndlessScenarioBasedData

Imageandscenariocreationwithconstraints

PROMPT:

“Createasituationwith3vehicles”

PROMPT:

“Amancrossingthe

street”

Images:Continental

www.nxtaim.de

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FirstProofofConcept-FirstControlNetTrained

RealWorldSample“EnvironmentModel”GeneratedSample

Images:Continental

Credit:JonasNeuhöfer,ErwinKraft

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FailuresADASandCurrentADSystemscanAddress

Sincetheworldchanges,theAIalsoneedsto

change!

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ButcanweTrustAIModelsandTheirSecurity?

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CurrentSecurityRisksofAI-basedPerception

〉ManyAImodelsaresensitivetoadversarialattacks.

〉Effectisknownforalongtime:

〉Rathersmallchangesinimagecanleadtomisinterpretations.

[1904.08653]Foolingautomatedsurveillancecameras:adversarialpatchestoattackpersondetection()

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CurrentSecurityRisksofAI-basedPerception

〉Speedlimitwasdetectedas85mph.〉Caracceleratedwithinthecity.

Singlesourceof