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Vehicle Traffic Congestion Estimation Based on RFID

Authors:
Fawzi Mohammed Munir Al-Naima at Nahrain University
Fawzi Mohammed Munir Al-Naima
Hassan Abdulsalam Hamid at Northern Technical University
Hassan Abdulsalam Hamid
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Abstract and Figures

Due to the proliferation in the number of vehicles on the road, traffic problems are bound to exist. Therefore, the use of Intelligent Transportation Systems (ITS) has become mandatory for obtaining traffic information from roads. Radio Frequency Identification (RFID) technology has been used to obtain vehicles’ IDs (tag ID) from RFID readers and to collect traffic information in real‐time. This paper proposes a simulation system for the Vehicle Traffic Congestion Estimation (VTCE) based on RFID. The RFID reader will read the vehicle tags and transfer the necessary information to a database in a Central Computer System (CCS). The CCS utilizes these data to determine the traffic congestion status of the road network by following a specific procedure.
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International Journal of Engineering Business Management
Special Issue on Radio Frequency Identification and Wireless Sensor Networks
Editor: Cristina Turcu
Vehicle Traffic Congestion
Estimation Based on RFID
Regular Paper
Fawzi M. Al-Naima1,* and Hassan A. Hamd2
1 Department of Computer Engineering, Nahrain University, Baghdad, Iraq
2 Department of Computer Engineering, Nahrain University, Baghdad, Iraq
* Corresponding author E-mail: fawzi.alnaima@ieee.org
Originally published in the International Journal of Radio Frequency Identification & Wireless Sensor Networks, ISSN 1847-9812
© 2012 Al-Naima and Hamd; licensee InTech. This is an open access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,
distribution, and reproduction in any medium, provided the original work is properly cited.
AbstractDuetotheproliferationinthenumberof
vehiclesontheroad,trafficproblemsareboundtoexist.
Therefore,theuseofIntelligentTransportationSystems
(ITS)hasbecomemandatoryforobtainingtraffic
informationfromroads.RadioFrequencyIdentification
(RFID)technologyhasbeenusedtoobtainvehicles’IDs
(tagID)fromRFIDreadersandtocollecttraffic
informationinreal‐time.Thispaperproposesa
simulationsystemfortheVehicleTrafficCongestion
Estimation(VTCE)basedonRFID.TheRFIDreaderwill
readthevehicletagsandtransferthenecessary
informationtoadatabaseinaCentralComputerSystem
(CCS).TheCCSutilizesthesedatatodeterminethetraffic
congestionstatusoftheroadnetworkbyfollowinga
specificprocedure.
KeywordsRFID,Trafficcongestion,Intelligent
TransportationSystems.
1.Introduction
Therapidincreaseinroadtrafficappearstobeoneof
themajorproblemsfacingurbanandsub‐urbanareasin
recentyears.Trafficcongestionandjamsareoneofthe
mainreasonsforimmenselyincreasingtransportation
costsduetothewastedtimeandextrafuel.Traffic
reportsinreal‐timeareessentialforalleviating
congestioninovercrowdedcities,aswellasallowing
commutersthechoiceofproperroutestoavoid
becomingstuckintrafficforhours.Severalinitiatives
havebeenproposedandimplementedtogathertraffic
datatofeedtheITS[1].Accordingtooursurvey,most
effortsfocusonlimitedinstallationoffixedsensors
suchasloop‐coilsandintelligentvideocameraswith
imageprocessingcapability.However,thecostsof
suchimplementationsareveryhighduetothehigh
costofthedevices,installationandmaintenance.
Moreover,thesefixedsensorsarevulnerableto
extremeweatherincertainareas.Analternativeway
tocollecttrafficdataatalowercostwithwider
coverageisthereforeneeded[1].
Evenifdriversattempttoavoiddailyrushhourtraffic,
thecircumnavigationofallsuddenlyarisingtraffic
congestionismostlyimpossiblewithcurrenttraffic
managementsystems.Tomanagethischallengeinthe
future,theU.S.FederalHighwayAdministration
(FHWA)identifiedthreegeneralapproachestoreduce
trafficcongestion[2]:
Extensionofthecurrentbasecapacity,e.g.,increase
ofthenumberandsizeofhighways.
1
Fawzi M. Al-Naima, and Hassan A. Hamd:
Vehicle Traffic Congestion Estimation Based on RFID
www.intechopen.com
ARTICLE
www.intechopen.com Int. j. eng. bus. manag., 2012, Vol. 4, 30:2012
Encouragementofalternativetravelandlanduse
conceptsthatrequirefewerresources,e.g.,non‐
automotivetravelmodes.
Usingtheexistingcapacitiesmoreefficiently.
Theapproachproposedinthispaperfocusesonthethird
strategy.AsstatedintheFHWAfinalreport[2],allof
thesethreestrategiesreducetrafficcongestion,but
strategiesforamoreefficientuseofexistingcapacities
havethemosteffectiveimpact,sincetheyconcentrateon
thebasiccauseoftheproblemsinsteadofonlyalleviating
thenegativeeffects.
RFIDtechnologyisoneofthemostrapidlygrowing
segmentsoftodayʹsautomaticidentificationdata
collection(AIDC)industry[3]. ʹʹRFIDtagsʹʹonobjectsor
assets,and ʹʹRFIDreadersʹʹ areusedtogatherthetag
information.RFIDrepresentsanimprovementonbar
codesintermsofnon‐opticalcommunication[4].The
VTCEsystembasedonRFIDisdesignedforalllegally
registeredvehicleswhichmustholdRFIDtags.When
thesevehiclestravelalongaroadorintersectioninwhich
aVTCEsystemisinstalled[5][6],thevehicletag
informationisreadandsentimmediatelytotheCCSunit
forthepurposesofreal‐timemonitoringand
managementofvehiclemovementconditions.

Thispaperisorganizedasfollows:section2introduces
theprinciplesofRFID.Section3describestheVTCE
system.Section4discussesthesoftwareofVTCE.Section
5describesthesimulationofroadsandtraffic
intersections.Section6discussesthetrafficcongestion
estimationstrategy.Section7givestheapplicationof
VTCE,andfinally,theconclusionisgiveninsection8.
2.PrinciplesofRFIDTechnology
RFIDisnotanewtechnology,forexample,theprinciples
ofRFIDwereemployedbytheBritishinWorldWarIIto
identifytheiraircraftusingtheIFFsystem(Identity:
FriendorFoe)[7].TodayRFIDisagenerictermfor
technologiesthatuseradiowavestoautomatically
identifypeopleorobjects[4].AtypicalRFIDsystemwill
compriseRFIDtags,RFIDreaderandmiddleware,see
Fig.1.
Figure1.ComponentsofanRFIDsystem
EachRFIDtaghasauniqueserialcodeorID,andplaced
inorattachedtotheobjecttobeidentified.Itcontains
informationonthebasicpropertiesoftheobject[8].An
RFIDtagrespondstoareaderquerywithitsfixedunique
ID.ThisfixedIDenablestrackingoftagsandthebearers.
Sometagscarryinformationabouttheobjectstheyare
attachedto[9].Areaderdetectsthetagsthatisattached
toorembeddedintheselecteditems.Itvariesinsize,
weightandmaybestationaryormobile.Thereader
communicateswiththetagthroughthereaderantenna,
whichbroadcastsradiowavesandreceivesthetag’s
responsesignalswithinitsreadingarea.Afterthesignals
fromthetagaredetected,thereaderdecodesthemand
passestheinformationtomiddleware[6].
Typically,anRFIDmiddlewareplatformperforms
aggregationofdataacrossdifferentreadersand
forwardingofrelevantdatatosubscriberserversor
application‐levelsystems,andpersistentstoragefor
receiveddata[10].However,anRFIDmiddlewareis
oftengiventhetaskofmanaging,monitoringand
configuringthedifferentreaders[11].
InVTCE,anAlienALR‐9800EnterpriseRFIDReader
typeischosen,becauseitfulfilsmostoftheRFID
hardwareʹspropertyrequirements,suchasitoperates
withUHFfrequency,multi‐staticantenna,multiple
antennaportsandsupportEthernetconnection.
3.VTCESystemArchitecture
TheVTCEprojectisdividedintotwoparts,softwareand
hardware.Thesoftwarepartisprogrammedusingthe
MicrosoftVisualBasic2010programandthelarge
databasesystemisdesignedbyMicrosoftSQLServer
2008R2ManagementStudio.Thehardwarepartconsists
ofRFIDreaders,whicharesimulatedbytheuseofthe
RifidiPlatform[12]andRoadsandTrafficIntersections
Simulator(RTIS).Rifidiisaprogramdesignedto
simulateanRFIDsystemandtoperformasahardware
reader.ItisthepremieropensourcesimulatorforRFID.
Also,wedesignedanRTISprogramtosimulatethe
physicalmovementsofvehicles,theRFIDtagson
vehiclesandtheroadnetworkwithtrafficintersections.
Figure2.ArchitectureofVTCEbasedonRFID
2Int. j. eng. bus. manag., 2012, Vol. 4, 30:2012 www.intechopen.com
ThesystemarchitectureoftheVTCEisshowninFig.2.It
canbeseenthatthissystemmainlyconsistsofRFIDtags
attachedtoallvehicles,twoRFIDreadersandfour
antennasoneachreader.IneachbranchtwoRFID
antennasareinstalled,theycansimultaneouslyscanin
oppositedirectionsfromthetwovehiclesandcanrecord
relevantinformationforeachvehicle.
ThetwoRFIDantennasarelocatedinthemedianisland
oftheroadnearthetrafficintersectionandseparatedbya
convenientdistance.Thisarchitectureofarrangingthe
directionofantennasmeanstheantennas’RFradiation
areasdonotoverlapwitheachother.IntheCCS,
accordingtotheorderofreceivingthesametagIDfrom
twodifferentantennas,thedirectionofvehiclemovement
willbeknownfromitsentrytoitsexit.Inthissystem
architecture,theVTCEwillmonitorthepathdirectionfor
allvehiclesinthetrafficintersectionsinreal‐time.
TheCCSperformsmanagement,monitoringand
maintenanceonthecommunicationwiththereaders,and
containsthemiddlewareanddatabaseserver[10].Figure
3showshowtheCCSisconnectedwiththeRFIDreaders
andthedatabase.
Figure3.ThelayoutoftheVTCEenvironment
4.VTCESoftware
TheVTCEsoftwareisrundirectlyontheCCS,the
middlewarerequeststhedatabasetoobtainthe
requirementstoestablishconnections.These
requirementsincludethetrafficintersection’sID,the
RFIDreader’sIPandPortandtheRFIDreaderʹs
UsernameandPassword.Aftertheresponseisreceived
fromthedatabasethesystemstartstheconnectionwith
thereadersandbeginsrequestingthereaderstogetthe
gatheredtaglistoverperiodsofonesecond.
Thedatareceivedintheformofapackagefromthe
readermustbeprocessedthroughseveralstepsand
filters,asshowninFig.4.Thepackageinformationis
filteredastagID,antennanumber,dateandtime.This
informationwillbestoredinanonlinedatatable.Ifthe
antennanumberiseven,thepackagedataarestoredina
temporarytableandiftheantennanumberisodd,the
systemrequeststosearchinthetemporarytableforthat
tagID.Whenbothevenandoddpackagesareobtained
together,thesystemwillinferthevehicleIDthathas
passedthrough,trafficintersectionID,from‐road,to‐
road,date,in‐timeandout‐time.Theinferredinformation
willbestoredinthevehiclelocationtable.Thenextstep
istocheckwhetherthisvehicleIDisinablacklisttable
ornot.Ifthisisdetectedthenthesystemdisplaysa
warningmessagethatincludestheIDofthevehicle
passingthroughthetrafficintersection,from‐road,to‐
road,dateandthetime.
Figure4.Flowchartofmiddlewareperformance
3
Fawzi M. Al-Naima, and Hassan A. Hamd:
Vehicle Traffic Congestion Estimation Based on RFID
www.intechopen.com
5.RoadsandTrafficIntersectionsSimulator(RTIS)
5.1TheRTISArchitecture
BeforeintroducingtheVTCEprojectintoareal‐life
situation,theability,functionality,efficiencyandfurther
effectshavetobetestedcarefully.Toevaluatethe
improvementsthatcanbeachieved,simulationshaveto
beconducted.Hence,arealisticsimulationofroadand
trafficintersectionscenariosisneeded.Various
parametersareneededtosimulatethetraffic,theVTCE
communicationwithreaders,theapplicationandthe
environment[2].
Trafficincludesthephysicalmovementsofvehiclesonan
arbitraryroadnetwork.WiMAXwirelessEthernet
communicationbetweenCCSandreaders[13]is
simulatedviaWi‐FiwirelessEthernetcommunication.
Applicationsimulationmeansthesimulationof
applicationsthataretobeintegratedinreal‐world
vehicles.Forthispurpose,innervehicleinterfaceshaveto
beemulatedtoallowtheapplicationtointeractwith
RFIDreaders,suchasattachedRFIDtagsonvehicles.The
lastpartistheenvironmentsimulationwhichincludes
theroadnetworkwithtrafficintersections.Also,aTCP/IP
serverisbuilttosimulatetheconnectionmethodinRTIS
suchastheAlienALR‐9800EnterpriseRFIDreader.The
VTCEconnectionwithRTISisliketheconnectionwith
therealAlienreaders.
5.2TheRTISScenario
ToevaluatetheeffectivenessoftheVTCEandtoidentify
potentialproblems,asimplesimulationscenariohastobe
considered.Forthisreason,aspecialregionisselected
whichhassevenin‐outwaysandfivetrafficintersections.
Oneintersectioniscomposedofthreeroadsintersected
andtheothersarecomposedoffourroadsintersected.
Thisregionischosenbecauseitprovidesagoodroad
structureforVTCEtests.
AnintersectionIDisgiventoeachintersectionsuchas
(146,147,…,150).TenRFIDreadersaretobesimulated;
tworeaderstoeachintersectionasshowninFig.5.
Severalvehiclesaresimulatedandeachvehicleisgivena
specificvehicleIDandtagID.Thespeedofvehicles
movingcanbecontrolledinRTIS.Thesevehiclesmove
ontheroadnetworkalongarandompath.Severalroutes
aredesignedforeachvehicleonroadnetwork.The
vehicleselectsaspecificroutetopassthroughby
implementingarandomfunction.
TheRTISsimulatestheRFIDreadertoscanandreceivetag
IDsfromvehicles.Thevirtualreaderaccumulatesthese
datauntilitreceivesthe‘GetTagList’instructionfromthe
VTCE.Then,itwillsendthegathereddatatoVTCEinCCS
bytheTCP/IPserver.TheRTISisdesignedforcreatinga
scenariothatisalmostreal.Alltheunnecessaryor
unpredictablefactorsthatcaninfluencetheresults,suchas
sideroadtrafficorcomplextrafficlightsystems,are
avoidedinordertoprovidesignificantresults.
Figure5.ThevehicleandroadnetworkinRTIS
6.ProposedTrafficCongestionEstimationStrategy(TCES)
Reportingroadtrafficcongestioncanbeaconfusingtask
sincethereisnoadoptedstandardformeasuring
congestion[14].Typicalusersneedaconciseandeasyto
understandtrafficreport.Thenormaltrafficsituationcan
beroughlycategorizedintotwostates,openand
congested[15],butsuchaclassificationisnotenoughto
describethetrafficsituation.Thus,intheVTCEproject
threetrafficpatternshavebeenadoptedtofacilitatequick
andeasystepstounderstandthereport[14],namely,Red
(TrafficJam),Yellow(SlowMoving),andGreen(Free
Flow)aredefinedasthefollowing:
TrafficJam:thereareaverylargenumberof
vehiclesandalmostallofthemrunveryslowlyand
thiswillberepresentedbyredcolour.
SlowMoving:therearealargenumberofvehicles
andmostofthevehiclesrunathalfspeedandthis
willberepresentedbyyellowcolour.
FreeFlow:thereareaminimumnumberofvehicles
andthevehiclesrunatnormalspeedintheregion
ofinterestandthiswillberepresentedbygreen
colour.
Todetermineacongestionlevel,thefollowingthreesteps
arecarriedout:
6.1ComputingtheAverageTimeSpent
Tocomputetheaveragetimethatisrequiredtopassthe
street,inthefirststepthesystemgetsthetimefromGUI.
Then,thesystemgoesbackfiveminutes.Therewith,it
requeststheIDsofthevehiclesthathaveleftthestreet
withinthoselastfiveminutes.Inthenextstep,thesystem
recallstheentrytimeintothestreetforthosevehicles.
Then,itsubtractstheexittimefromentrytimeforeach
4Int. j. eng. bus. manag., 2012, Vol. 4, 30:2012 www.intechopen.com
vehicleasdepictedinFig.6.Thelaststepiscomputing
thetimeaverageusingthesumofthespenttimeofallthe
vehiclesanddividesitbythenumberofvehicles.
6.2ComputingtheAverageSpeedofVehicles
Thesystemwillcomputetheaveragespeedofvehicles
afteritgetsthedistanceofthestreetfromthetraffic
intersectionstable.Thesystemcomputestheaverage
speedofvehiclesbydividingthedistanceonaverage
timespent.
6.3DeterminingtheCongestionLevel
Afterthesystemobtainstheaveragespeedofvehiclesin
thestreet,inthenextstep,congestionlevelsareclassified
usingspeedintothreelevels:red,yellowandgreen.The
VTCEprojectusestwoclassificationthresholds,γ and δ,
foradjustingparametersofthealgorithm,asfollows[14]:
Greenlevel,iftheaveragespeedislargerthanor
equaltoγ.
Yellowlevel,iftheaveragespeedlessthanγand
largerthanδ.
Redlevel,iftheaveragespeedislessthanδ.
Attheend,theuserobtainsfromthesystemtheaverage
requiredtimetakentopassthestreetandtheaverage
speedofvehiclesinthelastfiveminutes,aswellas
estimatingthetrafficcongestionlevel.
Figure6.Theflowchartfortrafficcongestionstatusestimation
7.VTCEApplications
7.1TheTrafficCongestionAppraisal
TheVTCEsystemsupportssomeapplicationsforthe
datathataregatheredandanalysed.Thetraffic
congestionappraisalisoneofthem.Thisapplicationcan
estimatethecongestionintwoconditions;alongthestreet
orwithintheintersection.
Figure7showstheGUIofintersectioncongestion
appraisal.Appraisaloftrafficintersectioncongestionis
usedtoestimatetherequiredtimetocrosstheintersection.
Itcalculatestheaverageoftherequiredtimetocrossthe
distancebetweentheantennaofentryandtheantennaof
exit.ThisapplicationusesonlythefirststepoftheTCES.
ThetrafficintersectionIDshouldbeenteredinitsspecific
field.Thecongestioncanbeappraisedforthetimebeing
(default)oratthepreviousdateandtimebyselectingits
buttonthenspecifyingthedateandtime.Thesuggested
systemuses α andβcriteriatoestimatethestatusof
congestionintheintersection.Thesystemenablesαandβ
tobechangedbytheuserviaclickingontheSettingbutton
thatactivatesitstextsboxes. α and β arethetimerange
thatarerequired(inseconds)tocrosstheintersection.By
clickingontheCongestionStatusbutton,thesystemwill
computeanddisplayresultsasthenumberofvehicles
passedthroughtheintersectioninthelastfiveminutes,the
averageoftherequiredtimetopassthisintersection(in
seconds)andtheintersectioncongestionstatusasFree
Flow(green),SlowMoving(yellow)orTrafficJam(red).
Figure7.Thetrafficintersectionscongestionappraisal
Figure8showstheGUIofstreettrafficcongestion
appraisal.Thestreetcongestionappraisalisavery
importantapplicationofVTCE.Usingthisapplicationthe
streetcongestionstatuscanbeestimatedinreal‐time.The
usermustspecifythestreetandthedirectionoftraffic.
ThisisdonebygivingtheIDoftheintersection,i.e.,
from‐intersectionto‐intersection.Thetimemustbe
specifiedatthepresenttime(default)orontheprevious
dateandtimebyselectingitsbutton.Inthisapplication
thesystemuses γ and δ criteriatodecidethestatusof
5
Fawzi M. Al-Naima, and Hassan A. Hamd:
Vehicle Traffic Congestion Estimation Based on RFID
www.intechopen.com
trafficcongestioninthestreet.γand δ aretherangeof
vehicles’speedcriteria(inkm/Hr)thatpassalongthe
street.VTCEsystemenablestheusertochangeγandδ.
Figure8.Thestreettrafficcongestionappraisal
ThisapplicationusesallstepsintheTCES.Byclickingon
theCongestionStatusbutton,thesystemwilldisplaythe
requiredtimeaveragetopassthatstreet,theaverage
speedofvehiclesthatpassedalongthestreetandthe
streettrafficcongestionstatus.
7.2TrafficCongestionStatusWebsite
TheVTCEsystemcollectsusefuldatafromintersections
aboutvehiclemovements.Thesedataareonlyallowed
foradministratoruse.Twowebsitesaredesignedtoallow
anyusertobenefitfromtrafficcongestionestimation
applicationsasshowninFig.3.Viathesewebsites,the
usercanavoidtrafficcongestionbycheckingthe
congestionstatusbyintersectionorstreet.
Theintersectioncongestionstatusestimationwebsite
estimatestherequiredtimetocrosstheintersection.This
applicationusesonlythefirststepoftheTCES.Theclient
(user)shouldenterthetrafficintersectionID.Thewebsite
loadsthepresentdateandtime,and α and β criteria,
automatically.Thewebsiteenablestheusertochangeαand
βcriteriaandspecifypreviousdateandtime.Bypressingon
theIntersectionCongestionStatusbuttonthewebsite
computesanddisplaystheresultsonline,seeFig.9.
Thestreetcongestionstatuswebsiteisdesignedforany
user(driver)tocheckthecongestionstatusofastreet
beforejoiningit.Theuseroughttodefinethestreetby
from‐intersectionIDto‐intersectionID.Thewebsiteloads
thepresentdateandtime,andγand δ criteria,
automatically,ortheycanbedefinedmanually.This
websiteusesallstepsintheTCES.ByclickingontheStreet
CongestionStatusbutton,thesystemwilldisplaythe
averageoftherequiredtimetopassthatstreet,theaverage
speedofvehiclesthatpassedalongthestreetandthestreet
trafficcongestionstatus.Fig.10showstheInternetpage.
Figure9.Thewebsiteofintersectioncongestionestimation
Figure10.Thewebsiteforstreetcongestionestimation
7.3StreetTrafficCongestionAppraisal/SMSServer
IntheVTCEproject,theStreetTrafficCongestionAppraisal
/SMSServer(STCA/SMS)isdesignedsothatausercan
obtaininformationaboutstreetcongestionwithoutaccessto
theInternet.ThisisdonebysendinganSMSmessagetothe
STCA/SMSserver.TheSTCA/SMSserveriscomposedof
twoparts:STCAandGSMmodem,(seeFig.2).TheSTCA
receivestherequestfromtheGSMmodemandcalculates
thecongestionstatusatthepresenttimebytheuseofTCES,
seeFig.11.Then,itsendsthereplytotheGSMmodem.
AGSMmodemisawirelessmodemthatconnectsa
computertoaGSMnetwork.LikeaGSMmobilephone,a
GSMmodemrequiresaSIMcardinordertooperate.Figure
12showstheestablishedcommunicationbetweenthe
cellularnetworkandthecomputerviaGSMModem[16].
6Int. j. eng. bus. manag., 2012, Vol. 4, 30:2012 www.intechopen.com
Figure11.StreetTrafficCongestionAppraisal/SMSServer
Figure12.GSMmodemcommunications
AnexternalGSMmodemisconnectedtoacomputerbya
serialcable.Itispossibletomakeandreceivephonecalls
andsendtextmessages.ATcommandsmustbeusedfor
establishingcommunicationbetweentheGSMmodemand
thecomputer[16].ATcommandsarethesetofcommands
thatarespecifiedforcontrollingaGSMphoneormodem
andmanagingtheSMSfeatureofGSM.IntheVTCE
project,theSonyEricssonMobilePhoneModemAAD‐
3880020‐BVhasbeenusedalongwiththeSonyEricsson
built‐inmodemsoftware.TheVTCEmodemis
programmedbyATcommandswithProtocolDescription
Unit(PDU)formatmode[17].Itisusedtosend/receive
SMSmessagesto/fromtheuser(thedriver).TheGSM
modemreceivestheSMSmessagefromGSMnetworkand
sendsittoSTCAandviceversa,asdepictedinFig.13.
Figure13.SonyEricssonGSMmodemconfigurations
Theusermustsendamessageinaspecificformat.The
messageoughttostartwiththe(STCA)symbol,capitalor
small,followedbyaspace.Then,theusermustspecify
thestreetbyenteringtheIDoftheintersectionfollowed
byaspaceandtheIDofthenextintersection,forexample
(STCA150149).Themessageissenttotheservice
number;themodemreceivesamessageandsendsitto
STCA/SMSserver.Theserverwillsendthereplytothe
modemtosendittotheuser.
8.Conclusion
VehicleTrafficCongestionEstimationbasedonRFIDisa
projectwithagoaltogatherinformationaboutthe
vehiclespassinginanyspecifictrafficintersection.This
informationisthenutilizedtodeterminethetrafficstatus
ofaroadnetwork.ThisgoalisrealizedbyinstallingRFID
readersinalltheseintersectionsandattachingRFIDtags
toallvehicles,whereuponthesereaderssendthe
informationtoaCCS.TheproposedVTCEprojectuses
theTCEStoclassifythereportintothreetrafficpatterns,
namely,Red(TrafficJam),Yellow(SlowMoving)and
Green(FreeFlow),whichmayalsobeextendedto
classifyfivepatterns,ifneeded.TheproposedVTCE
projectusesthisinformationinthreedifferent
applications;TheTrafficCongestionAppraisalforthe
administrator,TrafficCongestionStatusWebsitefor
InternetusersandStreetTrafficCongestionAppraisal/
SMSServerforGSMmobileusers.Itisimportanttonote
thatiftheproposedVTCEsystemistobeimplemented,
thenlargedataneedtobeprovidedbythetraffic
authoritiesfortestingtoensuretherobustnessofthe
system.
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... The growing number of vehicles and increased population have triggered to the requirement of effective traffic management systems. An Intelligent Transportation System (ITS) is an effective approach to solve traffic problems without building any extra physical infrastructure such as tunnels and bridges [3]. It applies Information and Communication Technologies (ICT) to the online transportation systems to improve performance and help to alleviate traffic congestion and optimize fuel consumption [4]. ...
... RFID is shaping up to be an important building block for the IoT. The affordable cost with improved benefits has made RFID a reliable technology with a competitive advantage [3]. RFID is highlighted as one of the converging technologies and main catalyst playing a significant role in this project. ...
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... The growing number of vehicles and increased population have triggered to the requirement of effective traffic management systems. An Intelligent Transportation System (ITS) is an effective approach to solve traffic problems without building any extra physical infrastructure such as tunnels and bridges [3]. It applies Information and Communication Technologies (ICT) to the online transportation systems to improve performance and help to alleviate traffic congestion and optimize fuel consumption [4]. ...
... RFID is shaping up to be an important building block for the IoT. The affordable cost with improved benefits has made RFID a reliable technology with a competitive advantage [3]. RFID is highlighted as one of the converging technologies and main catalyst playing a significant role in this project. ...
View
... The growing number of vehicles and increased population have triggered to the requirement of effective traffic management systems. An Intelligent Transportation System (ITS) is an effective approach to solve traffic problems without building any extra physical infrastructure such as tunnels and bridges [3]. It applies Information and Communication Technologies (ICT) to the online transportation systems to improve performance and help to alleviate traffic congestion and optimize fuel consumption [4]. ...
... RFID is shaping up to be an important building block for the IoT. The affordable cost with improved benefits has made RFID a reliable technology with a competitive advantage [3]. RFID is highlighted as one of the converging technologies and main catalyst playing a significant role in this project. ...
View
... The growing number of vehicles and increased population have triggered to the requirement of effective traffic management systems. An Intelligent Transportation System (ITS) is an effective approach to solve traffic problems without building any extra physical infrastructure such as tunnels and bridges [3]. It applies Information and Communication Technologies (ICT) to the online transportation systems to improve performance and help to alleviate traffic congestion and optimize fuel consumption [4]. ...
... RFID is shaping up to be an important building block for the IoT. The affordable cost with improved benefits has made RFID a reliable technology with a competitive advantage [3]. RFID is highlighted as one of the converging technologies and main catalyst playing a significant role in this project. ...
A Traffic Congestion Framework for Smart Riyadh City based on IoT Services
Article
Full-text available
  • May 2018
Internet of Things has become one of the most challenging issues in many researches to connect physical things through the internet by creating a virtual identity for everything. Traffic congestion in Riyadh city is chosen due to the proliferation in the number of vehicles on Riyadh roads that is resulting in grumbling by residents. Currently, there are few reliable services offered to residents from the traffic department enabling them to access traffic information. A new traffic congestion framework for Riyadh is proposed to help the development of traffic congestion services. This framework aims to benefit from the current Riyadh road infrastructure and apply the Internet of Things paradigm for detecting traffic congestion with Everything as a Service approach. Sensing devices are used to identify the congestion of the traffic flow through providing multiple proposed services such as a vehicle counting, live streaming video and rerouting services. Users are able to access the services by using proposed mobile application connected to the internet, as those services are integrated with public map service. By using the services, the users are able to identify the exact location where congestion occurs and an alternate solution can be provided easily. To achieve this, Business Process Execution Language is embedded as a supporting framework layer. Due to the effectiveness in this layer, executable workflows are designed to combine the proposed services with the legacy Riyadh services as individual model. This approach clearly defines how the services are executed through the proposed models. A quantitative evaluation is provided to support the usability of this research.
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... Many proposed solutions use intrusive sensors such as inductive and pneumatic loops [4]. As per their design, these tools disrupt traffic flow during installation and maintenance, moreover these tools are relatively expensive to install and maintain [5]. Other tools which are non-intrusive include visual and acoustic sensors; they too however are comparatively expensive and have accuracy issues. ...
... The other most common application of RFIDs that is meant to manage congestion, is similar to the one being suggested here. The uniqueness of our proposed solution is the inclusion of fuzzy logic; further, the focus of the solution is on the volume and modal speed of vehicles [5]. ...
Ubiquitous traffic management with fuzzy logic — Case study of Maseru, Lesotho
Conference Paper
  • May 2016
Maseru is the capital city of Lesotho and is a relatively small city with roughly 67 vehicles registered each day. Traffic lights are used with the intension of effectively managing vehicular traffic at junctions. These traffic lights follow a predetermined sequence usually based on historic data. As a result of this design, they inherently fail to efficaciously manage traffic flow when it is abnormal. Vehicles on one side have to wait even though there are no cars on other sides of the road. The consequences of this include increased congestion and atmospheric air pollution. Technological advancements have resulted in the now widely researched Internet of Things paradigm with one of its applications being vehicular traffic management. The focus of this paper is the design of a prototype reactive system based on Internet of Things whose functionality includes traffic lights that are capable of reacting to prevailing conditions. The system makes use of Radio Frequency IDentifier technology and mobile tools to ubiquitously collect traffic data and disseminate value added traffic information.
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... It is based on a time management method that calculates a sophisticated schedule for the passage of each traffic column in real-time. (Al-Naima & Hamd, 2012) proposed an RFID-based simulation framework for Vehicle Traffic Congestion Estimation (VTCE). An RFID reader reads vehicle tags and transfers the collected data to a database in a central computer system (CCS). ...
Traffic violation detection systems : A survey
Conference Paper
Full-text available
  • Dec 2021
Due to the massive population increase and the overcrowding of transport networks, traffic accidents are also increasing. These accidents cause colossal material and moral losses and are considered a hindrance to development. Accidents are frequently triggered by a combination of variables rather than a single cause. The most effective way to reduce these accidents is to activate the control systems, detect violators of traffic laws promptly, and deter potential violators. Traffic violation detection systems (TVDS) are an effective solution to help traffic management authorities. TVDS can detect traffic rules violations, such as escaping from red lights and over-speeding. However, despite the diversity of existing systems, there is no comprehensive research that abstracts the used systems and technologies as a foundation for TVDS. Therefore, this paper proposed an extensive analytical collection of the techniques used to build TVDS. This survey paper aims to provide a source that can reference organizing ideas and direct research in a promising direction. Furthermore, many techniques are used to build TVDS. However, the most important and promising ones like Vehicular Ad Hoc Network (VANET), Radio Frequency Identification (RFID), and Artificial intelligence (AI) are discussed, analyzed, and compared with details in this paper.
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... The static infrastructure is designed to access, process and share the data from identification tags [26]. Israeli Waze and Brazilian Wabbers crowd sourcing services have been implemented for a navigating the users using GPS to aware of accurate congestion in the highway via automatic data acquisition [27]. The bus dispatch model was accomplished to offer arrival time, the current location of public bus transport using the Internet and smart mobile devices. ...
Optimized traffic control and data processing using IoT
Article
Full-text available
  • Jan 2019
  • CLUSTER COMPUT
The development of the Internet of Things facilitates various dimensionalities in a home, industrial and business applications. The integration of sensors and smart objects with accessible infrastructure makes the efficient data processing and decreases the human resource, operating time. The novel smart traffic control framework is proposed using local traffic smart server and remote cloud server to improve the traffic signal processing time that reduces the vehicles’ waiting time, congestion and pollution at the roadway intersection. This approach is also capturing the vehicle’s transition that is used to track high-speed vehicles. Optimized regression algorithm is proposed to collect multi-path data and compute single-point nifty decision using waiting vehicle density at four-direction roadway intersection. The sensor data is processed using regression algorithm and take the decision to change the lamp onset. The case study implementation has been demonstrated for four-direction roadway by considering the existing infrastructure with Arduino Uno kit and evaluated the smart traffic framework by comparing with normal traffic system. The results prove that proposed framework smooth the progress of hassle-free travel by reducing the waiting time for the green lamp onset, and also can be use the recorded vehicles images to track the high-speed vehicles.
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... The rapid increase in road traffic appears to be one of the major problems facing urban and sub-urban areas in recent years. Traffic congestion and jams are one of the main problems that must be solved [1]. So, Analyses of V2V communications systems have drawn a great attention by many considerable researchers aim to reduce traffic jams, accident rate and time to reach the destination [2]. ...
Analytical Model for Wireless Channel of Vehicle-to-Vehicle Communications
Article
Full-text available
  • Jun 2017
Vehicle-to-Vehicle (V2V) communication system is a network of vehicles that communicate with each other to exchange information. The environment between vehicles affect in the signals that travel from the transmitter to the receiver, subsequently, it is important to comprehend the underlying characteristics propagation channels. This paper discusses and models some of the key metrics such as path loss, power delay profile, and delay spread at 5.2 GHz carrier frequency. The analyses are presented for two scenarios; both of the transmitter and receiver are stationary and in moving case with considering the direction of the moving and the separation between the vehicles. Likewise, a probability of a presence of some impediments in between of the vehicles with various separations is considered. The achieved results show that path loss for many types of environments may be predicted with using the presented model channel Model and location of the obstacles is sensitive to the received signals.
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Road Traffic Congestion (TraCo) Estimation Using Multi-Layer Continuous Virtual Loop (MCVL)
Article
Full-text available
  • Jan 2021
Any road traffic management application of intelligent transportation systems (ITS) requires traffic characteristics data such as vehicle density, speed, etc. This paper proposes a robust and novel vehicle detection framework known as multi-layer continuous virtual loop (MCVL) that uses computer vision techniques on road traffic video to estimate traffic characteristics. Estimations of traffic data such as speed, area occupancy and an exclusive spatial feature named as corner detail value (CDV) acquired using MCVL are proposed. Further, the estimation of traffic congestion (TraCo) level using these parameters is also presented. The performances of the entire framework and TraCo estimation are evaluated using several benchmark traffic video datasets and the results are presented. The results show that the improved accuracy in vehicle detection process using MCVL subsequently improves the precision of TraCo estimation. This also means that the proposed framework is well suited to applications that need traffic characteristics to update their traffic information system in real time.
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RFID Emulation in Rifidi Environment
Article
Full-text available
  • Jan 2009
RFID is a technology for radio frequency identification that enables software systems to automatically detect and identify objects in the real world. Thanks to this ability, RFID is of interest for numerous companies; unfortunately, the evaluation of a new business scenario involving RFID demands significant in-vestments in time, hardware, and infrastructure. Instead, Rifidi is a tool that quickly and realistically emulate RFID scenarios in order to explore their possibil-ities before investing in them. We present here an analysis of Rifidi, showing how to practically exploit it to design a new business process, and discuss pros and cons in its use. Furthermore, as a case study, we consider a new application that we have devised and that could be of interest for companies: an RFID-based, vir-tual shop assistant.
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Estimating Road Traffic Congestion using Vehicle Velocity
Conference Paper
Full-text available
  • Jul 2006
This study investigates an alternative way to estimate degrees of road traffic congestion based on routine GPS measurements from main roads in urban areas of Bangkok, Thailand. We classify three levels of traffic congestion according to the weighted exponential moving averages of measured GPS speed. Human perception is used to obtain classification thresholds and evaluated the performance of the proposed method. The benefits of our proposed method over existing techniques is that it is simple, easy to understand, and compatible with existing traffic report systems in Bangkok
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Radio frequency identification
Book
  • Jan 2011
Radio-frequency identification (RFID) is the use of an object applied to or incorporated into a product, animal, or person for the purpose of identification and tracking using radio waves. RFID has many applications; for example, it is used in enterprise supply chain management to improve the efficiency of inventory tracking and management. This book presents current research from across the globe in the study of radio frequency identificatio, including the role of RFID in agriculture; plants with implanted RFID microchips to yield safer and more wholesome products; radio frequency identification in the support and transmission of medical information in the field of disaster medicine; and RFID adoption in the developed and developing world.
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An RFID electronic tag based automatic vehicle identification system for traffic iot applications
Article
  • May 2011
This paper introduces the design and implementation of an active RFID tag based system for automatically identifying running vehicles on roads and collecting their data. The design principles and the archi- tecture of the system are presented, including active electronic tags and reading equipments (readers and antennas), the monitoring base station deployment, the two-layered network construction, and the monitoring software. To solve identification uncertainty problems, the two key techniques are: anti- interference protocol and data clearing algorithm are proposed. Finally, the effectiveness and efficiency of the system is analyzed. The system will have wide applications in traffic IOT (Internet of Things) to support traffic monitoring, traffic flow statistics, traffic scheduling, and special vehicle tracking.
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Automatic vehicle identification (AVI) system based on RFID
Article
  • Jul 2010
RFID is a Radio Frequency Identification technology, which has a unique advantage in data collection and data transmission. Based on the expatiate of the identification principle, the system structure, and the characteristics of the RFID, this paper introduces the structure, technical target and application of the AVI system Based on the RFID.
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RFID Explained: A Primer on Radio Frequency Identification Technologies
Article
  • Jan 2006
This lecture provides an introduction to Radio Frequency Identification (RFID), a technology enabling automatic identification of objects at a distance without requiring line-of-sight. Electronic tagging can be divided into technologies that have a power source (active tags), and those that are powered by the tag interrogation signal (passive tags); the focus here is on passive tags. An overview of the principles of the technology divides passive tags into devices that use either near field or far field coupling to communicate with a tag reader. The strengths and weaknesses of the approaches are considered, along with the standards that have been put in place by ISO and EPCGlobal to promote interoperability and the ubiquitous adoption of the technology. A section of the lecture has been dedicated to the principles of reading co-located tags, as this represents a significant challenge for a technology that may one day be able to automatically identify all of the items in your shopping cart in a just few seconds. In fact, RFID applications are already quite extensive and this lecture classifies the primary uses. Some variants of modern RFID can also be integrated with sensors enabling the technology to be extended to measure parameters in the local environment, such as temperature & pressure. The uses and applications of RFID sensors are further described and classified. Later we examine important lessons surrounding the deployment of RFID for the Wal-Mart and the Metro AG store experiences, along with deployments in some more exploratory settings. Extensions of RFID that make use of read/write memory integrated with the tag are also discussed, in particular looking at novel near term opportunities. Privacy and social implications surrounding the use of RFID inspire recurring debates whenever there is discussion of large scale deployment; we examine the pros and cons of the issues and approaches for mitigating the problems. Finally, the remaining challenges of RFID are considered and we look to the future possibilities for the technology.
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Implementation of National Traffic Information Collection Systems in Ubiquitous Environments
Conference Paper
  • Jan 2009
The objectives of the research include to develop a novel Traffic Information Collection System (TICS) based on RFID, and to create a chance to lead ubiquitous environments in the transportation area.
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Optimization Management System for Level Crossing Traffic Based on RFID
Conference Paper
  • May 2010
This paper describes the use of radio frequency identification technology and computer technology to solve level crossing problems in the management of traditional vehicles, proposed management system optimized design, including the hardware architecture and system software; built automatic vehicle identification and information management platform; for Intelligent Transportation Systems laid an important foundation; for the Smooth Traffic Project of urban road has an important practical value.
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Radio frequency identification (RFID)
Article
  • Feb 2006
  • COMPUT SECUR
First conceived in 1948, Radio Frequency Identification (RFID) has taken many years for the technology to mature to the point where it is sufficiently affordable and reliable for widespread use. From Electronic Article Surveillance (EAS) for article (mainly clothing) security to more sophisticated uses, RFID is seen by some as the inevitable replacement for bar codes. With increasing use comes increasing concern on privacy and security. Clearly there is considerable work to be undertaken before RFID becomes as pervasive as bar codes although the tempo of change is increasing rapidly.
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