Report on google driverless car

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1.Introduction:
Theinventionsoftheintegratedcircuitandlater,themicrocomputer,weremajor
factorsinthedevelopmentofelectroniccontrolinautomobiles.Theim-portance
ofthemicrocomputercannotbeoveremphasizedasitisthebrainthatcontrols
manysystemsintodayscars.Forexample,inacruisecontrolsystem,thedriver
setsthedesiredspeedandenablesthesystem bypushingabutton.A micro-
computerthenmonitorstheactualspeedofthevehicleusingdatafrom velocity
sensors.Theactualspeediscomparedtothedesiredspeedandthecontroller
adjuststhethrottleasnecessary.
A completelyautonomousvehicleisoneinwhichacomputerperformsallthe
tasksthatthehumandrivernormallywould.Ultimately,thiswouldmeangetting
inacar,enteringthedestinationintoacomputer,andenablingthesystem.From
there,thecarwouldtakeoveranddrivetothedestinationwithnohumaninput.
Thecarwouldbeabletosenseitsenvironmentandmakesteeringandspeed
changesasnecessary.Thisscenario would require allofthe automotive
technologiesmentionedabove:lanedetectiontoaidinpassingslowervehiclesor
exitingahighway;obstacledetectiontolocateothercars,pedestrians,animals,
etc.;adaptivecruisecontroltomaintainasafespeed;collisionavoidancetoavoid
hittingobstaclesintheroadway;andlateralcontroltomaintainthecarsposition
ontheroadway.
Inaddition,sensorswouldbeneededtoalertthecartoroadorweathercon-
ditionstoensuresafetravelingspeeds.Forexample,thecarwouldneedtoslow
downinsnowyoricyconditions.Weperform manytaskswhiledrivingwithout
eventhinkingaboutit.Completelyautomatingthecarisachallengingtaskandis
a long way off.However,advances have been made in the individual
systems.Googlesroboticcarisafullyautonomousvehiclewhichisequippedwith
radarandLIDARandsuchcantakeinmuchmoreinformation,processitmuch
morequicklyandreliably,makeacorrectdecisionaboutacomplexsituation,and
thenimplementthatdecisionfarbetterthanahumancan.Googleanticipatesthat
theincreasedaccuracyofitsautomateddrivingsystem couldhelpreducethe

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numberoftraffic-relatedinjuriesanddeaths.
TheGooglecarsystem combinesinformationgatheredforGoogleStreetView
withartificialintelligencesoftwarethatcombinesinputfromvideocamerasinside
thecar,aLIDARsensorontopofthevehicle,radarsensorsonthefrontofthe
vehicleandapositionsensorattachedtooneoftherearwheelsthathelpslocate
thecar’spositiononthemap.Asof2010,Googlehastestedseveralvehicles
equippedwiththesystem,driving140,000miles(230,000km)withoutanyhuman
intervention,theonlyaccidentoccurringwhenoneofthecarswasrear-ended
whilestoppedataredlight.Googleanticipatesthattheincreasedaccuracyofits
automateddrivingsystemcouldhelpreducethenumberoftraffic-relatedinjuries
anddeaths,whileusingenergyandspaceonroadwaysmoreefficiently.
Figure1.1GoogleCar
Thecombinationofthesetechnologiesandothersystemssuchasvideobasedlane
analysis,steeringandbrakeactuationsystems,andtheprogramsnecessaryto
controlallofthecomponentswillbecomeafullyautonomoussystem.The
problemiswinningthetrustofthepeopletoallowacomputertodriveavehicle
forthem,becauseofthis,theremustberesearchandtestingdoneoverandover
againtoassureanearfoolprooffinalproduct.Theproductwillnotbeaccepted
instantly,butovertimeasthesystemsbecomemorewidelyusedpeoplewill

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realizethebenefitsofit.
2.BLOCKDIAGRAM:
2.1BACKGROUND:
Theblockdiagram ofGooglesdriverlesscarisshownbelow.Itincludessensor
section,processorsectionanddrivebywiretechnology.
Figure2.1Blockdiagramofthesystem
Themaincontrollerofthevehicleisthemicroprocessorsection.Therearetwo
processors;oneisforthegeneralworkingandoneforhandlingthesensoryinputs
whichisrealtime.
Figure2.2GoogleCar

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Therearetwocoprocessorsforhandlingthesteeringandthebrake.Acceleratoris
directlycontrolledbythegeneralpurposeprocessor.Thesensoryinputsinclude
inputsfrom thelidar,radar,positionestimatorandstreetview images.Lidar
createsa3-D imagesplatform formountingtheobstaclesandmap.Thecamera
visualsareusedfordetectingthecolourofthetrafficsignalbasedonwhichthe
vehicle moveson the road.The generalpurpose processorisconstantly
communicatingwiththeenginecontrolunit
3.CONTROLUNIT:
3.1HARDWARESENSORS:
3.1.1Radar:
Radarisanobject-detectionsystemwhichuseselectromagneticwavesspecifically
radiowaves-todeterminetherange,altitude,direction,orspeedofbothmoving
andfixedobjectssuchasaircraft,ships,spacecraft,guidedmissiles,motor
vehicles,weatherformations,andterrain.
Figure3.1MACOM SRSRadar

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Theradardish,orantenna,transmitspulsesofradiowavesormicrowaveswhich
bounceoffanyobjectintheirpath.Theobjectreturnsatinypartofthewave’s
energytoadishorantennawhichisusuallylocatedatthesamesiteasthe
transmitter.Themodernusesofradararehighlydiverse,includingairtraffic
control,radarastronomy,air-defensesystems,antimissilesystems;nauticalradars
to locate landmarks and other ships; aircraft anti collision systems;
oceansurveillancesystems,outer-spacesurveillanceand rendezvoussystems;
meteorologicalprecipitationmonitoring;altimetryandflight-controlsystems;
guided-missile target-locating systems; and ground-penetrating radar for
geologicalobservations.Hightechradarsystemsareassociatedwithdigitalsignal
processingandarecapableofextractingobjectsfromveryhighnoiselevels.
A radarsystem hasatransmitterthatemitsradiowavescalledradarsignals
inpredetermineddirections.Whenthesecomeintocontactwithanobjecttheyare
usuallyreflectedand/orscatteredinmanydirections.Radarsignalsarereflected
especiallywellbymaterialsofconsiderableelectricalconductivity-especiallyby
mostmetals,byseawater,bywetland,andbywetlands.Someofthesemakethe
useofradaraltimeterspossible.Theradarsignalsthatarereflectedbacktowards
thetransmitterarethedesirableonesthatmakeradarwork.Iftheobjectis
movingeithercloserorfartheraway,thereisaslightchangeinthefrequencyof
theradiowaves,duetotheDopplereffect.
Radarreceiversareusually,butnotalways,in thesamelocation asthe
transmitter.Although thereflected radarsignalscaptured bythereceiving
antennaareusuallyveryweak,thesesignalscanbestrengthenedbytheelectronic
amplifiersthatallradarsetscontain.Moresophisticatedmethodsofsignal
processingarealsonearlyalwaysusedinordertorecoverusefulradarsignals.
Theweakabsorptionofradiowavesbythemedium throughwhichitpassesis
whatenablesradarsetstodetectobjectsatrelatively-longrangesatwhichother
electromagneticwavelengths,suchasvisiblelight,infraredlight,andultraviolet
light,aretoostronglyattenuated.Suchthingsasfog,clouds,rain,fallingsnow,
andsleetthatblockvisiblelightareusuallytransparenttoradiowaves.Certain,
specificradio frequenciesthatareabsorbed orscattered by watervapor,
raindrops,oratmosphericgases(especiallyoxygen)areavoidedindesigning

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radarsexceptwhendetectionoftheseisintended.
Finally,radarreliesonitsowntransmissions,ratherthanlightfrom theSunor
theMoon,orfromelectromagneticwavesemittedbytheobjectsthemselves,such
asinfraredwavelengths(heat).Thisprocessofdirectingartificialradiowaves
towardsobjectsiscalledillumination,regardlessofthefactthatradiowavesare
completelyinvisibletothehumaneyeorcameras.Hightechradarsystemsare
associatedwithdigitalsignalprocessingandarecapableofextractingobjects
fromveryhighnoiselevels.
HereweusetheMACOM SRSRadarResistanttoinclementweatherandharsh
environmentalconditions,24GHzultrawideband(UWB)radarsensorsprovide
objectdetection and tracking.Parkingassistancecan beprovided byrear
mountedsensorswith1.8m rangethatcandetectsmallobjectsinfrontoflarge
objectsandmeasuredirectionofarrival.Sensorswithabilitytoscanoutupto30
mprovidewarningofimminentcollisionsoairbagscanbearmedandseat
restraintspretension.FigureshowstheRADARwavesinthesystem.
Figure3.2RadarRange

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3.1.2Lidar:
LIDAR (LightDetectionAndRangingalsoLADAR)isanopticalremote
sensingtechnologythatcanmeasurethedistanceto,orotherpropertiesofa
targetbyilluminatingthetargetwithlight,oftenusingpulsesfrom alaser.
LIDAR technology hasapplication in geometrics,archaeology,geography,
geology,geomorphology,seismology,forestry,remotesensingandatmospheric
physics,aswellasinairbornelaserswathmapping(ALSM),laseraltimetryand
LIDARContourMapping.TheacronymLADAR(LaserDetectionandRanging)
isoftenusedinmilitarycontexts.Theterm”laserradar”issometimesusedeven
thoughLIDARdoesnotemploymicrowavesorradiowavesandisnottherefore
inrealityrelatedtoradar.
LIDARusesultraviolet,visible,ornearinfraredlighttoimageobjectsandcanbe
usedwithawiderangeoftargets,includingnon-metallicobjects,rocks,rain,
chemicalcompounds,aerosols,cloudsandevensinglemolecules.A narrow
laserbeamcanbeusedtomapphysicalfeatureswithveryhighresolution.LIDAR
hasbeenusedextensivelyforatmosphericresearchandmeteorology.
figure3.3Lidar
AdvancedResearchLidar.InadditionLIDARhasbeenidentifiedbyNASAasa
keytechnologyforenablingautonomousprecisionsafelandingoffuturerobotic
andcrewedlunarlandingvehicles.Wavelengthsinarangefrom about10

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micrometerstotheUV(ca.250nm)areusedtosuitthetarget.Typicallylightis
reflectedviabackscattering.ThereareseveralmajorcomponentstoaLIDAR
system:
1.Laser6001000nm lasersaremostcommonfornon-scientificapplications.
Theyareinexpensivebutsincetheycanbefocusedandeasilyabsorbedbytheeye
themaximum powerislimitedbytheneedtomakethem eye-safe.Eye-safetyis
oftenarequirementformostapplications.Acommonalternative1550nmlasers
areeye-safeatmuchhigherpowerlevelssincethiswavelengthisnotfocusedby
theeye,butthedetectortechnologyislessadvancedandsothesewavelengthsare
generallyusedatlongerrangesandloweraccuracies.Theyarealsousedfor
militaryapplicationsas1550nm isnotvisibleinnightvisiongogglesunlikethe
shorter1000nminfraredlaser.Airbornetopographicmappinglidarsgenerallyter
withmuchlessattenuationthandoes1064nm.
Figure3.4Lidarusedfor3Dimaging
2.ScannerandopticsHowfastimagescanbedevelopedisalsoaffectedbythe
speedatwhichitcanbescannedintothesystem.Thereareseveraloptionstoscan
the azimuth and elevation,including dualoscillating plane mirrors,a
combinationwithapolygonmirror,adualaxisscanner.Opticchoicesaffectthe
angularresolutionandrangethatcanbedetected.A holemirrororabeam
splitterareoptionstocollectareturnsignal.

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3.Photodetectorandreceiverelectronicstwomainphotodetectortechnologies
areused in lidars:solid statephoto detectors,such assilicon avalanche
photodiodes,orphotomultipliers.Thesensitivityofthereceiverisanother
parameterthathastobebalancedinaLIDARdesign.
Figure3.53-Dmapofcarsurroundings
4.PositionandnavigationsystemsLIDARsensorsthataremountedonmobile
platformssuchasairplanesorsatellitesrequireinstrumentationtodeterminethe
absolutepositionandorientationofthesensor.Suchdevicesgenerallyincludea
GlobalPositioningSystemreceiverandanInertialMeasurementUnit(IMU).3D
imagingcanbeachievedusingbothscanningandnon-scanningsystems.”3D
gatedviewinglaserradar”isanon-scanninglaserrangingsystem thatappliesa
pulsedlaserandafastgatedcamera.
3.1.3GlobalPositioningSystem:
heGlobalPositioningSystem (GPS)isaspace-basedglobalnavigationsatellite
System (GNSS)thatprovideslocationandtimeinformationinallweather,
anywhereonorneartheEarth,wherethereisanunobstructedlineofsightto
fourormoreGPSsatellites.GPSreceivercalculatesitspositionbyprecisely
timingthesignalssentbyGPSsatelliteshighabovetheEarth.

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Figure3.6GoogleMap
Eachsatellitecontinuallytransmitsmessagesthatinclude:
1)Thetimethemessagewastransmitted
2)Preciseorbitalinformation(theephemeris)
3)ThegeneralsystemhealthandroughorbitsofallGPSsatellites
Thereceiverusesthemessagesitreceivestodeterminethetransittimeofeach
messageandcomputesthedistancetoeachsatellite.Thesedistancesalongwith
thesatellites’locationsareusedwiththepossibleaidoftrilateration,depending
onwhichalgorithmisused,tocomputethepositionofthereceiver.Thisposition
isthendisplayed,perhapswithamovingmapdisplayorlatitudeandlongitude;
elevation information may be included.Many GPS units show derived
informationsuchasdirectionandspeed,calculatedfrompositionchanges.Three
satellitesmightseem enough to solveforposition sincespacehasthree
dimensionsandapositionneartheEarth’ssurfacecanbeassumed.However,
evenaverysmallclockerrormultipliedbytheverylargespeedoflightthespeed
atwhichsatellitesignalspropagateresultsinalargepositionalerror.Therefore
receiversusefourormoresatellitestosolveforthereceiver’slocationandtime.
TheveryaccuratelycomputedtimeiseffectivelyhiddenbymostGPSapplications,
whichuseonlythelocation.AfewspecializedGPSapplicationsdohoweveruse

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thetime;theseincludetimetransfer,trafficsignaltiming,andsynchronizationof
cellphonebasestations.
3.1.4Positionsensor:
ApositionsensorisanydevicethatpermitspositionmeasurementHereweusea
rotatorencoderalsocalledashaftencoder,isanelectro-mechanicaldevicethat
convertstheangularpositionormotionofashaftoraxletoananalogordigital
code.Theoutputofincrementalencodersprovidesinformationaboutthemotion
oftheshaftwhichistypicallyfurtherprocessedelsewhereintoinformationsuch
asspeed,distance,RPM andposition.
Theoutputofabsoluteencodersindicatesthecurrentpositionoftheshaft,
makingthem angletransducers.Rotaryencodersareusedinmanyapplications
thatrequirepreciseshaftunlimitedrotationincludingindustrialcontrols,robotics,
specialpurposephotographiclenses,computerinputdevices(suchasupto
mechanicalmiceandtrackballs),androtatingradarplatforms.
3.1.5Cameras:
Figure3.7StreetViewcamerasystem.

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Googlehasusedthreetypesofcar-mountedcamerasinthepasttotakeStreet
Viewphotographs.Generations13wereusedtotakephotographsintheUnited
States.Thefirstgenerationwasquicklysupersededandimageswerereplacedwith
imagestakenwith2ndand3rdgenerationcameras.Secondgenerationcameras
wereusedtotakephotographsinAustralia.
Thesystem isarosette(R)of15small,outward-lookingcamerasusing5
megapixelCMOSimagesensorsandcustom,low-flare,controlled-distortion
lenses.Theshadowscausedbythe1st,2ndand4thgenerationcamerasare
occasionallyviewableinimagestakeninmorningsandevenings.Thenew4th
generationcamerasHD willbeusedtocompletelyreplaceallimagestakenwith
earliergenerationcameras.
Thusthetotalsensorcomponentscanbeexplainedusingtheabovefigure
assembledonthecar.Allthecomponentsarealreadyexplained.
3.2LOGICPROCESSINGUNIT:
3.2.1GoogleStreetView:
Figure3.8StreetView

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GoogleStreetViewisatechnologyfeaturedinGoogleMapsandGoogleEarth
thatprovidespanoramicviewsfrom variouspositionsalongmanystreetsinthe
world.ItwaslaunchedonMay25,2007,originallyonlyinseveralcitiesinthe
UnitedStates,andhassincegraduallyexpandedtoincludemorecitiesandrural
areasworldwide.
GoogleStreetView displaysimagestakenfrom afleetofspeciallyadapted
cars.Areasnotaccessiblebycar,likepedestrianareas,narrowstreets,alleysand
skiresorts,aresometimescoveredbyGoogleTrikes(tricycles)orasnowmobile.
Oneachofthesevehiclesthereareninedirectionalcamerasfor360viewsata
heightofabout8.2feet,or2.5meters,GPSunitsforpositioningandthreelaser
rangescannersforthemeasuringofupto50meters180inthefrontofthevehicle.
Therearealso 3G/GSM/Wi-Fiantennasforscanning3G/GSM and Wi-Fi
hotspots.Recently,’highquality’imagesarebasedonopensourcehardware
camerasfromElphel.
Whereavailable,streetviewimagesappearafterzoominginbeyondthehighest
zoominglevelinmapsandsatelliteimages,andalsobydragginga”pegman”icon
ontoalocationonamap.Usingthekeyboardormousethehorizontaland
verticalviewingdirectionandthezoom levelcanbeselected.Asolidorbroken
lineinthephotoshowstheapproximatepathfollowedbythecameracar,and
arrowslinktothenextphotoineachdirection.Atjunctionsandcrossingsof
cameracarroutes,morearrowsareshown.
3.2.2Artificialintelligencesoftware:
Figure3.9Hardwareassemblyofthesystem

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Artificialintelligenceistheintelligenceofmachinesandthebranchofcomputer
sciencethataimstocreateit.AItextbooksdefinethefieldas”thestudyand
designofintelligentagentswhereanintelligentagentisasystemthatperceivesits
environmentand takesactionsthatmaximizeitschancesofsuccess.John
McCarthy,whocoinedthetermin1956,definesitas”thescienceandengineering
ofmakingintelligentmachines”.Herethedetailsaboutthesoftwareareatrade
secretofGoogle.Thehardwarecomponentsareplacedinthvehiclebootandis
shownbelow.
4.DRIVEBYWIRESYSTEM:
Drive-by-wire,technologyintheautomotiveindustryreplacesthetraditional
mechanical control systems with electronic control systems using
electromechanicalactuatorsandhumanmachineinterfacessuchaspedaland
steeringfeelemulators.Hence,thetraditionalcomponentssuchasthesteering
column,intermediateshafts,pumps,hoses,belts,coolersandvacuumservosand
mastercylindersareeliminatedfromthevehicle.

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5.APPLICATIONS:
Thevariousapplicationsofthetechnologyare
5.1.Intelligenttransporting:
Intelligent transport systems vary in technologies applied, from basic
managementsystemssuch ascarnavigation;trafficsignalcontrolsystems;
containermanagementsystems;variablemessagesigns;automaticnumberplate
recognitionorspeedcamerastomonitorapplications,suchassecurityCCTV
systems;andtomoreadvancedapplicationsthatintegratelivedataandfeedback
from anumberofothersources,suchasparkingguidanceandinformation
systems;weatherinformationbridgedeicingsystems;andthelike.Additionally,
predictivetechniquesarebeingdeveloped to allow advanced modelingand
comparisonwithhistoricalbaselinedatathistechnologywillbearevolutionary
stepinintelligenttransportation.
5.2.Militaryapplications:
Automatednavigationsystem withrealtimedecisionmakingcapabilityofthe
systemmakesitmoreapplicableinwarfieldsandothermilitaryapplications.
5.3.Shipping:
Autonomousvehicleswillhaveahugeimpactonthelandshippingindustry.One
waytotransportgoodsonlandisbyfreighttrucks.Therearethousandsof
freighttrucksontheroadeverydaydrivingformultipledaystoreachtheir
destination.Allofthesetrucksaredrivenbyapaidemployeeofatrucking
company.
5.4.Transportationinhazardousplaces:
Thecompleterealtimedecisionmakingcapabilityandsensorguidednavigation
willleadstoreplacethehumandriversinhazardousplacetransportation.

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5.5.Taxiservices:
5.6.Publictransportation:
6.MERITSANDDEMERITS:
1.Fueleconomy:
Autonomousvehicleswilleliminateineffectivespeedingupandbraking,operating
atanoptimumperformancelevelinordertoachievebestpossiblefuelefficiency.
Evenifthefuelefficiencyachievedbytheautonomousvehicleswere1percent
betWater,thiswouldresultinbillionsofdollarsofsavingsintheUSalone.It
ispossibletoobtainsuperiorfuelefficiencyasaresultoftheimplementationof
autonomoussafetysystems.Totalsavingsthatcanbeachievedbytheincreased
fuelefficiencycanbecalculatedbymakingsomeassumptionssuchas:o10%asa
resultofmoreeabove,theimplementationautonomousvehicleswillresultinto
fuelsavingsof25percent,whichisroughestimate
2.TimeCosts:
Thephrasetimeismoneyistrueformostsituationsin modern lifeand
themonetaryvalueoftimeisincreasingeveryday.Usingautomatedcarscould
saveconsiderableamountoftimeinapersonslife,especiallyifthepersonresides
inabusycity.Evenifthetimesavingswerenotconsideredashavingmonetary
value,havingmoretimeforleisureactivitieswouldraiseourlifestandards.
Loweringtheamountoftimelostwillalsoenablepeopletobeontimeandmore
dynamic,resultinginasignificantimprovementinworkefficiency.Oneofthe
biggestadvantagesofthistechnologywillbetheeliminationoftrafficproblemsin
cities,whichareatthetopofthemostfrustratingproblemslistformostpeople.
Byenablingasmoothertrafficflow,thenewsystem willbesavingalotoftime
whichcanbeusedforworkorleisure.
3.ImpactsonTraffic:
Withtheintroductionofafullyautonomousvehicle,trafficflowwouldrastically
change.Trafficiscurrentlyanuisancetodriversallovertheworld.Intheearly

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stagesofimplementationtothehighwaysystemtherewouldbeacombinationof
autonomouslydrivenvehiclesandhumancontrolledvehicles.Thiscouldcause
someconfusion and problemsconcerningthereaction ofmotoriststo the
driverlessvehiclesandhowwelltheautonomousvehiclescanintegrateintotraffic
flow.Theautonomousvehicleswouldbefollowingalltrafficlawswhilehuman
drivershavethechoicetobreakthelaw.Astimeprogressesandtheautonomous
carbecomesamorecommonlyusedvehicleontheroad,trafficwouldbecomefar
lesscongested.Carswouldbeabletoseamlesslymergeintomovingtrafficand
thenexitthehighwayjustaseasily.Withthereductionoftraffic,thereisachance
thattherecouldbeeconomicimprovements.Also,withlessstopandgotraffic,
averagefueleconomywouldbeimproved.Vehiclesarealsofollowingeachother
consistentlywhichwouldhelpwithfuelusageaswell.
4.safety:
Safetyisimportantterminourlifeandautonomousvehicle.InGoogledriverless
carthereisaverygoodsafetybecausehumancontrollchangestocomputer
controll.safetyislossonlywhensomedefaultisdoneinsensororanyinstrument.
6.2.DEMERITS:
1)Theequipmentsandtechnologiesusedarecostlythemainequipmentsusedin
this technology are radar,lidar,position sensor,gps module,Multicore
heterogeneousprocessor,JAUS interoperablecommunication systems,high
resolutioncamerasareverycostlynow.
2)Complexartificialintelligencesoftwarethebrainoftheroboticcarisits
intelligentrealtimedecisionmakingsoftwarethedesignandimplementationof
thispartofthesystemismuchmorecomplicated.
3)Presentroadconditionsmayvaryandwhichwillaffectthedecisionsmadeby
thesoftwaresinceoursystem ismainlybasedonpureartificialintelligence,the
non-idealconditionsanddecisionsmadebyotherhumandriversmayvary.This
mayaffecttheidealoperationoftheroboticcar.
4)Professionaldriverswillbejobless.

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7.Futurescope:
Thetransitiontoanautomatedtransportationstructurewillgreatlypreventmany
problemscausedbythetraffic.Implementationofautonomouscarswillallowthe
vehiclestobeabletousetheroadsmoreefficiently,thussavingspaceand
time.Withhavingautomatedcars,narrowlaneswillnolongerbeaproblem less
problematicwiththeintegrationofautonomouscars.
Smoothtrafficflow isatthetopofthewishlistforcountlesstransportation
officials.Carmanufacturersarealreadyusingvariousdriverassistsystemsin
theirhigh-endmodelsandthistrendisbecomingmoreandmorecommon.Asa
resultourdailylives,butitishardtopredictwhen.Themostimportantfactoris
whetherthepublicsectorwillbeproactiveintakingadvantageofthiscapability
ornot.ThePublicSectorwilldetermineifthebenefitswillcomesoonerrather
thanlater.
Sincetheseassistsystemsareverysimilarwiththesystemsthatareusedin
autonomouscarprototypes,theyareregardedasthetransitionelementsonthe
waytotheimplementationfullyautonomousvehicles.
8.Conclusion:
Currently,therearemanydifferenttechnologiesavailablethatcan assistin
creatingautonomousvehiclesystems.Itemssuch asGPS ,automated cruise
control,andlanekeepingassistanceareavailabletoconsumersonsomeluxury
vehicles,Thecombinationofthesetechnologiesandothersystemssuchasvideo
based laneanalysis,steeringand brakeactuation systems,and theprograms
necessarytocontrolallofthecomponentswillbecomeafullyautonomous
system.Theproblem iswinningthetrustofthepeopletoallowacomputerto
driveavehicleforthem.becauseofthese,theremustberesearchandtestingdone
overandoveragaintoassureanearfoolprooffinalproduct.Theproductisnot
beacceptedinstantly,butovertimeasthesystemsbecomemorewidelyused

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peoplewillrealizeThebenefitsOfit.Theimplementation Ofautonomous
vehicleswillbringuptheproblem ofreplacinghumanswithcomputersthatcan
dohumanswithcomputersthatcandoTheworkforthem.Therewillnotbe
instantchangeinsociety,butitwillbecomemoreapparentovertimeastheyare
integratedintosociety.
8.References:
1)S.Thrun,W.BurgardandD.Fex,probabilisticRobotics(IntelligentRobotics
andAutonomousAgent),(2011).
2)SPRINGERLINK,IEEE,GOOGLE,GOOGLESCOLLER.
3)MORGANSTANLEYRESEARCH(2013)
4)ERICOGUIZZO(2013)
5)IJAREEIE(2014)
6)SAEINTERNATIONALSTANDARD
Websites:
1.www.google.com
2.www.springerlink.com
3.www.slideshare.com
4.www.googlescoller.com

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