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1、Driverseat:CrowdstrappingLearningTasksforAutonomousDrivingPranavRajpurkarPRANAVSR@CS.STANFORD.EDUTokiMigimatsuTAKATOKI@CS.STANFORD.EDUJeffKiskeJKISKE@STANFORD.EDUStanfordUniversityComputerScienceDept.,353SerraMall,Stanford,CA94305USARoyceCheng-YueRCHENGYUE@GMAIL.COM3265FalernoWay,SanJose,CA95135US
2、ASameepTandonSAMEEP@STANFORD.EDUTaoWangTWANGCAT@STANFORD.EDUAndrewNgANG@CS.STANFORD.EDUStanfordUniversityComputerScienceDept.,353SerraMall,Stanford,CA94305USAAbstractWhileemergingdeep-learningsystemshaveout-classedknowledge-basedapproachesinmanytasks,theirapplicationtodetectiontasksforau-tonomoust
3、echnologiesremainsanopenfieldforscientificexploration.Broadly,therearetwomajordevelopmentalbottlenecks:theunavail-Figure1.Embeddingthecrowdaroundlearningsystemsforbothabilityofcomprehensivelylabeleddatasetsandtrainingandevaluation,wecanleveragethepowerfulcombina-ofexpressiveevaluationstrategies.Appr
4、oachestionofhumanandcomputerintelligence.forlabelingdatasetshavereliedonintensivehand-engineering,andstrategiesforevaluatinglearningsystemshavebeenunabletoidentify1.Introductionfailure-casescenarios.Humanintelligenceof-fersanuntappedapproachforbreakingthroughAutonomousdrivingisamissioncriticaltech
5、nologyofthethesebottlenecks.ThispaperintroducesDri-future.Roadtrafficaccidentsareresponsiblefornearly1.3verseat,atechnologyforembeddingcrowdsmilliondeathsgloballyeachyear,andaretheleadingcausearoundlearningsystemsforautonomousdriv-ofdeathamongyoungpeopleaged15-29(WorldHealthing.Driverseatutilizescr
6、owdcontributionsforOrganization,2013).Inthequesttomakingroadsaccident-(a)collectingcomplex3Dlabelsand(b)taggingfree,AdvancedDriverAssistanceSystems(ADAS)arearXiv:1512.01872v1[cs.HC]7Dec2015diversescenariosforreadyevaluationoflearn-makingsignificantmilestones:AdaptiveCruiseControlingsystems.Wedemons
7、tratehowDriverseatcansystemsadjustvehiclespeedtomaintainsafedistancefromcrowdstrapaconvolutionalneuralnetworkonvehiclesahead,andAutomaticBrakingsystemsreacttothelane-detectiontask.Moregenerally,crowd-imminentcoll
