INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMSInt. J. Commun.
Syst. 2014; 27:135150Published online 12 April 2012 in Wiley Online
Library (wileyonlinelibrary.com). DOI: 10.1002/dac.2352A roadside
unit-based localization scheme for vehicularad hoc networksChia-Ho
Ou*,Department of Computer Science & Information Engineering,
National Pingtung Institute of Commerce,Pingtung,
TaiwanSUMMARYVehicular Ad Hoc Networks (VANETs), designed to ensure
the safety and comfort of passengers via
theexchangeofinformationamongst
nearbyvehiclesorbetweenthevehiclesandRoadsideUnits(RSUs),haveattractedparticularattention.
However, thesuccessofmanyVANETapplicationsdependsontheirability to
estimate the vehicle position with a high degree of precision, and
thus, many vehicle localizationschemeshavebeenproposed.
Manyoftheseschemesarebasedonvehicle-mountedGlobalPositioningSystem
(GPS) receivers. However, the GPS signals are easily disturbed or
obstructed. Although this problemcan be resolved by
vehicle-to-vehicle communication schemes, such schemes are
effective only in VANETswith a high trafc density. Accordingly,
this paper presents a VANET localization scheme in which
eachvehicleestimatesitslocationonthebasisofbeaconmessagesbroadcast
periodicallybypairsofRSUsdeployed on either side of the road. In
addition, three enhancements to the proposed scheme are
presentedfortheRSUdeployment, RSUbeaconcollisions, andRSUfailures.
Overall, thens-2simulationresultsshow that the localization scheme
achieves a lower localization error than existing solutions on the
basis ofvehicle-to-vehicle communications and is robust toward
changes in the trafc density and the vehicle speed.Copyright 2012
John Wiley & Sons, Ltd.Received 15 April 2011; Revised 5
January 2012; Accepted 8 March 2012KEY WORDS: vehicular ad hoc
networks; localization; positioning; roadside units1.
INTRODUCTIONRecent advances in Intelligent Transportation Systems
(ITS) technology have prompted
thedevelopmentofDedicatedShort-RangeCommunication(DSRC),
aservicecomprisingone-wayor two-way short-to-medium range wireless
communicationchannelsanda correspondingset ofprotocols and
standards. DSRC is designed to support high-speed, low-latency
vehicle-to-vehicle(inter-vehicle), and vehicle-to-infrastructure
(vehicle-to-roadside) communications on the basis
oftheIEEE802.11pstandardforWirelessAccessinVehicularEnvironments(WAVE)[1].
IEEE802.11pdenestheenhancementsrequiredtothe802.11standardtosupport
ITSapplications.Inaddition, several major automobilemanufacturers
havebeguntoinvest heavilyinVANETtechnology and have come together
to create a non-prot-based organization known as the Car-2-Car
Communication Consortium dedicated to improving road trafc safety
and efciency by meansof vehicle-to-vehicle communications [2].In
general, DSRC devices take the form of either an Onboard Unit
(OBU), installed within thevehicle, or a Roadside Unit (RSU),
mounted on the roadside infrastructure (e.g., access points,
trafcsigns, street lights) [3]. In a typical ITS application, every
vehicle tted with an OBU communicates*Correspondence to: Chia-Ho
Ou, Department of Computer Science and Information Engineering,
National PingtungInstitute of Commerce, No. 51, Minsheng E. Rd.,
Pingtung City, Pingtung County 90004, Taiwan, and Department
ofElectrical and Computer Engineering, University of Waterloo, 200
University Avenue West, Waterloo, Ontario, CanadaN2L 3G1.E-mail:
[email protected] 2012 John Wiley & Sons, Ltd.136 C.-H.
OUboth with neighboring DSRC-equipped vehicles and with local RSUs.
For example, a vehicle mayexchange its position information with
neighboring vehicles for collision warning purposes,
whilecommunicating with the RSUs to obtain road, weather, and
trafc-related information. Most ITSapplications require an
up-to-date (i.e., real time) knowledge of the vehicle position. In
practice, theprecision to which the vehicle position should be
known depends on the particular ITS application.Broadly-speaking,
ITS applications can be classied as either comfort-related or
safety-related [4].In applications of the former type, the aim is
to improve passenger comfort and trafc efciencyand/or to optimize
the route to a particular destination. In such applications, a
localization error ofaround 1030 m is generally acceptable. In
applications of the latter type, the ITS system is designedto
enhance passenger safety by exchanging safety-related information
via inter-vehicle communi-cations. Such applications have attracted
signicant interest in the automobile industry. Clearly,
inapplications of this type, a highly precise estimate of the
vehicle position is required. For example,vehicle position
information should be less than 5 m for cooperative driving
applications, and forcollision warning systems, the accuracy should
be within a meter or even sub-meter precision [5].In practice, the
vehicle position in such applications should be known to within 10
m, and thus, arequirement exists for highly precise vehicular
localization
schemes.Themajorityofthelocalizationschemespresentedintheliteraturearebasedonthepremisethat
each vehicle within the VANET is tted with a Global Positioning
System (GPS) receiver anduses a trilateration method on the basis
of the signals required from three or more GPS satellitesto
determine its position. Given an open area in which an unobstructed
line-of-sight is possible tomultiple satellites, GPS can achieve an
average accuracy of approximately 10 m [6]. Enhanced GPSsolutions,
such as the Differential GPS and the Assisted GPS [7], have been
proposed and achievean average accuracy between 3 and 7 m. However,
in practice, GPS signals are easily blocked
ordisturbedbyobstaclessuchasbuildings, rocks, densefoliage,
andsoforth, andthus, avehicletraveling in mountainous or densely
foliated regions, or in urban areas with a dense concentrationof
high buildings, is likely to suffer persistent GPS outages.
Nonetheless, recent studies have shownthat the performance of
GPS-based localization schemes can be enhanced via the use of
vehicle-to-vehicle communications [810]. Similarly, various
enhanced-performance ranging techniques havebeen proposed for
estimating the distance between vehicles [1114]. However, these
systems requirea minimum of three GPS-equipped neighboring vehicles
to estimate the position of the vehicle ofinterest, and thus, the
schemes are effective only in dense VANETs.In an attempt to address
the various limitations of the GPS-based systems described
previously,this paper proposes a VANET localization scheme based
upon the information provided by RSUs.In the proposed approach,
each vehicle estimates its distance to a pair of RSUs located on
eitherside of the road on the basis of the beacon messages
broadcast on a periodic basis. By using theposition information
within the rst set of beacon messages received from the two RSUs
and itsestimateddistancefromthetwoRSUs,
thevehiclethenappliestheconceptoftwointersectingcircles to
computeits two possible positions. After receivingthe second set of
beaconmessagesfromtheRSUs,
thevehicledetermineswhichofthesetwopositionsitisactuallylocatedatbycomputing
its two possible movement vectors over the broadcast period and
comparing the anglebetween these movement vectors and that of the
known road direction. In addition to the localiza-tion scheme, this
paper also proposes three enhancements to the proposed scheme for
dealing withthe RSU deployment, RSU beacon collisions, and RSU
failures. The effectiveness of the proposedapproach is evaluated
via a series of simulations performed using ns-2 [15, 16]. Overall,
the resultsshow that the localization scheme yields accurate
estimates of the vehicle position even in the eventof RSU failures.
In addition, it is shown that the proposed scheme is robust to
changes in the trafcdensity and the vehicle speed.2. OVERVIEW2.1.
Ranging techniquesIn general, the ranging techniques presented in
the literature for estimating the distance betweena transmitter and
a receiver fall into three categories, namely Received Signal
Strength Indicator(RSSI) methods, time-based methods, for example,
Time Of Arrival (TOA) and Time Difference OfCopyright 2012 John
Wiley & Sons, Ltd. Int. J. Commun. Syst. 2014; 27:135150DOI:
10.1002/dacRSU-BASED LOCALIZATION FOR VANETS 137Arrival (TDOA), and
Angle Of Arrival (AOA) methods [11]. RSSI is a well-known, low-cost
methodfor hardware-constrained systems, in which the distance
between the transmitter and the receiver isestimated on the basis
of the received signal strength by using theoretical radio
propagation models.However, the reliability of the RSSI estimates
cannot be guaranteed in environments with multi-path and shadowing
effects because of the resulting attenuation of the received
signal.
Time-basedmethodsutilizethesignalpropagationtimetoestimatethedistancebetweenthetransmitterandthereceiverandperformwellinclearline-of-sightpropagationenvironments,particularlywhenanaccuratereal-timeclocksynchronizationexistsbetweenthetransmitterandthereceiver[12].However,
multipath interference may result in errors in the estimated
propagation time, and thus,the circles or hyperbolas constructed
for localization purposes may not actually intersect at a
singlepoint. To resolve this problem, McCrady et al. proposed a
two-way reciprocal TOA ranging tech-nique, which eliminated the
requirement for clock synchronization between the transmitter and
thereceiver and achieved a ranging accuracy better than 3 m even in
multipath environments [14]. InAOA methods, the distance between
the transmitter and the receiver is estimated on the basis ofthe
relative angles of the signals received from neighboring nodes
[13]. However, such methods arenot only costly as a result of the
requirement to t the nodes with directional antennas or
antennaarrays but also perform poorly in environments without
line-of-sight signals or in which the nodesare sparsely distributed
[9].2.2. Localization in vehicular ad hoc networksBenslimane
presented a localization scheme on the basis of inter-vehicle
communications in whichthe GPS-equipped vehicles within the VANET
were used as reference points for determining
thepositionsoftheGPS-unequippedvehicles[8]. Intheproposedapproach,
eachGPS-unequippedvehicleperiodicallybroadcasts apositionrequest
messagetoits neighbors. Onreceivingthismessage, the GPS-equipped
vehicles send their position information back to the
GPS-unequippedvehicles, whichthenusethisinformationtodeterminetheir
ownpositionsviaatriangulationmethod. However, a minimumof three
neighboring GPS-equipped vehicles are required fortriangulation
purposes, and thus, the localization scheme performs poorly in
VANETS with a lowtrafc density.Kukshyaet al.
proposedarelativepositioningmethodinwhichvehicle-to-vehiclecommu-nicationswereusedtocompensatefor
GPSoutages[9]. Intheproposedapproach, all of thevehicles within a
particular geographic area exploit their local distance information
and then usea trilateration method to establish their individual
position coordinates relative to those of all theother vehicles.
However, the experimental results showed that the RSSI-based
distance estimateswere unreliable.Parker and Valaee proposed a
three-phase localization mechanism for vehicular networks
[10].Intheinitializationphase, eachvehiclemeasures
thedistancebetweenitself andeachof itsneighbors, exchanges this
information with its neighbors, and then determines an initial
estimateof its position by using either GPS information or a
triangulation method on the basis of the inter-vehicle distance
estimates. In the subsequent renement phase, the accuracy of the
initial
positionestimateisimprovedviatheuseofdistancemeasurements,vehiclespeedinformation,androadmap
information. In the nal phase, the renement process is iterated
periodically to maintain anup-to-date estimate of the vehicle
position.Recent studies have proposed a new localization paradigm
for VANET applications in which adata fusion technique is used to
combine the position estimates obtained from multiple
localizationmethods to generate a highly accurate estimate of the
vehicle position [5, 17]. Although such systemsare computationally
complex, the experimental results have shown that the position
estimates aresufciently precise to support VANET safety-related
applications.3. ROADSIDE UNIT-BASED LOCALIZATION SCHEME3.1. System
modelIn developing the RSU-based localization scheme proposed in
this paper, it is assumed that all
thevehiclesareequippedwithOBUdevices.EachvehiclealsorecognizesitsmovementvectorandCopyright
2012 John Wiley & Sons, Ltd. Int. J. Commun. Syst. 2014;
27:135150DOI: 10.1002/dac138 C.-H. OURRr(xr,yr)LRl(xl,yl)WnFigure
1. System model.traveled distance on the basis of the digital
odometer and compass. Note that the digital
odometerandcompassarecommonandavailabledevicesusedinvehicles.
AsshowninFigure1, it isfurther assumed that the vehicles drive
along a section of straight road with a length L and a
widthWseparatedintotwocarriageways, that is,
oneforeachdirection(e.g., northandsouth). TwoRSUs, designated
asRlandRr, are deployed on either side of the road at the midpoint
position,corresponding to coordinates of (xl, yl) and (xr, yr),
respectively. The radio range of each RSU (R)is assumed to be
sufcient to cover the entire width of the road, that is, R
>_L2_2W2.3.2. Distance
measurementIntheproposedRSU-basedlocalizationscheme,
eachvehicleestimatesitsdistancetoapairofRSUs onthebasis of
periodicbeaconmessages. As describedinSection2.1, boththeRSSImethod
and the TOA/TDOA methods provide a technically feasible approach
for obtaining distanceestimatesintheproposedlocalizationscheme.
However, it wasshownin[9]that theaccuracyof the
transmitter-to-receiver distance estimates obtained using the RSSI
method cannot
beguaranteedbecausethevariationintheinstantaneousRSSIissignicant.
Bycontrast,
thetwo-rayreciprocalTOArangingtechnique[14]hasamuchbetterrangingaccuracyandisthereforeadoptedfordistancemeasurement
purposesintheRSU-basedlocalizationmethodproposedinthis paper.3.3.
Vehicle position estimationEach RSU broadcasts a periodic beacon
message containing the following information: the RSUidentication,
the RSU coordinates, the road direction (e.g., n for Rr or s for
Rl), and the timestamp.In Figure 2, a vehicle v located at position
VA,tor VB,treceives beacon messages from Rland Rrwith the same
timestamp t and estimates its distance to Rl and Rr, that is, dl,t
and dr,t, respectively,by using the ranging technique. On the basis
of the RSU position information and the distance esti-mates,
twopossiblepositionsof v, that is, VA,t(xA,t, yA,t)andVB,t(xB,t,
yB,t), areobtainedcorresponding to the intersection points of two
overlapping circles. The equations of the two circlesare expressed
as.x xl/2.y yl/2=d2l,t, (1a).x xr/2.y yr/2=d2r,t. (1b)Copyright
2012 John Wiley & Sons, Ltd. Int. J. Commun. Syst. 2014;
27:135150DOI: 10.1002/dacRSU-BASED LOCALIZATION FOR VANETS
139RrRlLWndl,tVB,tdr,tdl,tdr,tVA,tRoad directionFigure 2. Position
estimation.Suppose that yl = yrfor elaboration (see Figure 2). The
coordinates of VA,tand VB,tcan then bederived as.xA,t, yA,t/ =_x2r
x2l d2l,t d2r,t2xr 2xl, yl x2A,t x2l 2xlxA,t d2l,t_, (2a).xB,t,
yB,t/ =_x2r x2l d2l,t d2r,t2xr 2xl, yl x2B,t x2l 2xlxB,t d2l,t_.
(2b)Byutilizingthepositioninformationcontainedwithintherst set
ofmessagesbroadcast bythetwoRSUs,
vdeterminesitsroaddirectionsimplybycomparingtheanglebetweenitscur-rent
movement vector v and the road direction n (v,n) with that between
the vector v and the roaddirection s (v,s) in accordance with
v,n =cos1_vn[v[[n[_, (3a)
v,s =cos1_vs[v[[s[_. (3b)Ifv,n
