Research supported inpart by General MotorsR&D Center through thecontract #TCS 34628 toU. C. Berkeley. The viewsexpressed here are those ofthe authors and not of theresearch sponsors.
INTRODUCTION
Vehicle-to-vehicle (V2V) communications is acrucial component of the intelligent transporta-tion system (ITS) [1], which utilizes the GlobalPositioning System (GPS) and dedicated short-range communications (DSRC) or IEEE 802.11pradios [2] for vehicles to exchange informationwith each other in an ad hoc mode. One impor-tant V2V application is cooperative active safetythat expands a driver’s perception horizon andthus has the potential to enhance the roadwaysafety [3]. In general, cooperative safety firstrequires that a vehicle has good real-time track-ing of its neighboring vehicles, and then, basedon that proximity awareness, various active safe-ty applications can provide advisories to the driv-er or perform emergency maneuvers to avoidhazardous situations.
In such a V2V safety communication concept,each vehicle is assumed to have a GPS receiver,a DSRC radio, and enough computing power totrack other vehicles in proximity. One of themost pressing challenges is to design a scalablecommunication protocol that would maintainacceptable tracking accuracy of neighboringvehicles while avoiding channel congestion. Priorimplementations of V2V safety communicationsused periodic broadcast of safety messages, typi-cally at a constant rate of 10 Hz, and at constanttransmission power, typically 20 dBm [4, 5].Small-scale V2V safety demonstrations havebeen shown to work well with such a communi-cation policy, but many simulation studies haveshown that such a naive strategy will not be scal-able for high market penetration of onboardwireless devices due to channel congestion andnumerous message collisions [6–9].
The implication of the capacity notion forwireless ad hoc networks in [10, 11] is that whenthe network becomes denser, one needs to eitherthrottle data rate or reduce transmission powerso that the limited wireless medium can be prop-erly shared by all nodes. Therefore, most existingV2V scalable communication designs focus oneither transmission rate or power adaption forscalability. For example, [6] proposes to fairlyallocate transmission power across all cars in amax-min fashion, which helps reduce beaconload at every point of a formulated one-dimen-sional highway and thus reserves bandwidth foremergency messages. The message dispatcher in[7] is proposed to reduce the required data rateby removing duplicate elements from differentV2V safety applications. This dispatcher designresembles compression ideas in source coding.
This article complements our previous simu-lation study in [9] by presenting an evaluation ofpractical and real-world implementation of theproposed V2V transmission control protocol[12]. We describe our protocol design. We pre-sent results from a simple outdoor test scenariowith two radios and vehicle mobility. The results
ABSTRACT
Vehicle-to-vehicle (V2V) communications playa critical role in enabling numerous importantcooperative safety applications. V2V safety com-munications rely on broadcast of self-state infor-mation (e.g., position, speed, and heading) byeach vehicle, which allows a vehicle to track itsneighboring vehicles in real time. One of the mostpressing challenges in this research is to maintainacceptable tracking accuracy of neighboring vehi-cles while avoiding congestion in the shared com-munication channel. In this article we describethe evaluation of a transmission control protocolthat adapts the message rate and transmissionpower for V2V safety communications. This pro-tocol has been implemented on V2V test vehicleswith wireless radios and integrated with existingactive safety applications. The testing and evalua-tion results show that proposed communicationdesign works well in practice, its performancematches the observations from previous simula-tions and shows great promise for a large-scaledeployment of V2V cooperative safety systems.
TOPICS IN AUTOMOTIVE NETWORKINGAND APPLICATIONS
Ching-Ling Huang and Raja Sengupta, U. C. Berkeley
Hariharan Krishnan, General Motors R&D Center
Yaser P. Fallah, West Virginia University
Implementation and Evaluation ofScalable Vehicle-to-Vehicle SafetyCommunication Control
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IEEE Communications Magazine • November 2011 135
from a test scenario with 15 radios are presentedto validate the scalability of the proposed V2Vtransmission control. We summarize our obser-vations and future work.
PROPOSED TRANSMISSIONCONTROL PROTOCOL
In this section, we present a joint transmissionrate-power control protocol for the V2V safetycommunications [14]. The protocol comprisestwo parts:• Rate control, which decides when a vehicle
should broadcast a safety message• Power control, which decides how far the
safety message should be broadcast, thusdetermining the transmission power levelfor the 802.11p radio to send this messageThe proposed V2V safety communication
framework is shown in Fig. 1. Each vehicle isassumed to contain a DSRC radio, a bank ofestimators to track other vehicles, and a GPSreceiver. In this concept of V2V communica-tions, each vehicle broadcasts self-state informa-tion (e.g., position, speed, and heading) in theform of basic safety messages (BSMs) to neigh-boring vehicles via the DSRC channel. Thesesafety messages are in the WAVE short message(WSM) format defined in IEEE 1609.3 for effi-cient information exchange and per-messagepower assignment [13]. The receiving vehiclescan then use incoming messages to track thesending vehicle in real time. The estimatedstates of all neighboring vehicles (i.e., the vehicleneighborhood mapping in Fig. 1) will be fed intoactive safety applications, such as forward colli-sion warning (FCW), electronic emergency brakelight (EEBL), and slow/stopped vehicle alert(SVA) [3].
TRANSMISSION RATE CONTROLThe Tx rate controller on a host vehicle (HV)decides when an HV should broadcast a safetymessage to update its state information toremote vehicles (RVs) in proximity. Betweenmessage arrivals, an HV uses the latest receivedmessage and a constant speed predictor to trackother RVs’ position, which is sometimes referredas coasting.
Proposed on-demand message generation istriggered by an HV’s suspected tracking error.This suspected tracking error is an HV’s guess ofthe tracking error on RVs toward its own cur-rent position. This error represents an HV’s esti-mate of how wrong RVs track itself. When thissuspected tracking error becomes larger, an HVuses a higher transmission probability to dissemi-nate its state information to reduce the poten-tially large tracking error on RVs. When thissuspected tracking error is small, an HV uses asmall transmission probability so that other vehi-cles with larger errors can use the channel.
At each time step t ∈ N (e.g., at every 100 msepoch), the jth HV calculates transmission prob-ability pj(t) based on suspected tracking error~ej(t) on RVs toward its own position in theEuclidean sense (i.e., the usual distance defini-tion for Cartesian coordinates). If this suspectederror ~ej(t) is smaller than eth (the error thresh-
old), there is no transmission at all from the jthHV, pj(t) = 0. This threshold design leaves thechannel to be used by other vehicles when thesuspected error by the jth HV is within a tolera-ble range. Otherwise, if this ~ej(t) is larger thanthis threshold eth, the probability of sending amessage in that time step t is computed by
pj(t) = 1 – exp(–α × | ~ej(t) – eth|2), (1)
where α > 0 is the sensitivity to suspected track-ing error. The on-demand nature of Eq. 1responds to the fact that a higher transmissionrate, thus probability, is required for an HV thathas more unexpected movements to RVs.
Since there is no explicit acknowledgment forbroadcast in DSRC, after each transmission, weuse the estimated packet error rate (PER) tosimulate the evolution of suspected error ~ej(t)used in Eq. 1: ~ej(t+) = (1 – ζ) × ~ej(t), where ζ isa Bernoulli trial with success probability 1-PERto address potential channel loss. If the outcomeof this trial is positive, the suspected error isreset to zero; otherwise, suspected error accu-mulates from ~ej(t) based on the constant speedprediction. Note that this ~ej(t) is not the actualtracking error by RVs; instead, it is only a mea-sure used by an HV to adjust its own transmis-sion probability. Based on pj(t) in Eq. 1, the ratecontroller in Fig. 1 stochastically generates asafety message and passes it to the power con-troller.
Due to the outdoor environment and differ-ent scales of fading in a DSRC channel, it is ingeneral hard to apply a mathematical model toget this PER. Therefore, an HV is proposed toestimate PER empirically by checking the incon-sistency in sequence numbers of received mes-sages from all corresponding RVs within every 5s time window. That is, an HV uses the numberof lost packets divided by the number of totalpackets initiated from a certain RV to inferrecent channel loss ratio; PER is this measure
Figure 1. Proposed V2V communication framework: Rate Controller decideswhen to generate a message and Power Controller assigns power for it.
The jth vehicle
Sensor inputs
RxDSRC channel
Tx
Safety messages (WSM)
Safety messages (WSM)
Clear ch. assessment(CCA)
Tx rate controller
Tx power controller
Vehicle’s GPSmeasurements
Active safety applications (FCW, EEBL, SVA)
Vehicle neighborhood mapping(a bank of estimators for RVs)
DSRC radio (802.11p MAC/PHY)
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averaged over all RVs within a range (e.g., a 100m radius). Assuming network symmetry, thisPER gives an HV the unreliability of the chan-nel between itself and all surrounding RVs.
TRANSMISSION POWER CONTROLThe Tx power controller on an HV deter-
mines the transmission power for outgoing safetymessages based on sensed channel utilization(i.e., how busy the wireless medium is being usedby vehicles in a geographical area). Channel uti-lization has been shown to be a good measurefor an HV to infer the intensity of data traffic inits proximity [15].
The targeted transmission range Lj(t) is firstadjusted based on sensed channel utilization bythe jth HV. The channel utilization Uj(t) is com-puted by the jth HV by observing the clear chan-nel assessment (CCA) indicator available fromthe physical (PHY) layer of 802.11. This Uj(t) issimply the time average of recently sampledCCA within a 1 s time window. In the proposeddesign, if sensed channel utilization is higherthan Umax, minimum transmission range Lmin isused; if sensed channel utilization is lower thanUmin, maximum transmission range Lmax is used;otherwise, the range is selected by
(2)
where Lmin and Lmax are communication rangelower/upper bounds, which are usually deter-mined from safety specifications for vehicularenvironments. Besides, Umin and Umax representthe desired operating range of channel utiliza-tion so that the wireless medium is neitherunderutilized nor overutilized. Since the powergranularity for our testbed is 1 dBm [14], to con-vert Lj(t) to power, we apply a power range
mapping (with 50 percent reception probability)based on the DRSC channel propagation modelin [15]. Overall mapping from channel utilizationto transmission power is listed in Table 1.
The idea behind the proposed transmissioncontrol is that nearby RVs are assumed to bephysically more involved with an HV. It is thusmore dangerous if an HV does not know thestate of its immediate neighboring vehicles. Inthe proposed power control, when a channelbecomes congested, an HV tries to make surethat its nearby RVs can still hear its state infor-mation by reducing the power, which results intemporarily giving up farther cars. In short, theproposed design does not compromise informa-tion intensity during channel congestion; instead,a HV reduces power to mitigate congestionwhile maintaining decent tracking accuracy onsurrounding RVs toward itself to ensure safety.
Previous simulation study [9] has shown thatthe proposed transmission control achieves bet-ter tracking accuracy over that of default 10 Hzbeaconing with 20 dBm power in large-scalehighway traffic scenarios. For our implementa-tion and evaluation in this article, the followingparameters are used to calculate transmissionprobability and power every 100 ms: α = 10 m–2,eth = 0.2 m, Lmin = 50 m, Lmax = 250 m, Umin =0.4, and Umax = 0.8. That is, we consider chan-nel utilization below 0.4 as a sign of the mediumbeing underutilized and use maximum power; weconsider channel utilization above 0.8 as a signof the medium being overutilized and use mini-mum power [11]. The transmission controldescribed in this section has been implementedon wireless safety units (WSUs) [14]. Since therate control requires an HV’s mobility to triggermessage generation, our outdoor evaluation isdescribed next for a mobility test and later for ascalability test. The power control evaluation canbe found in [12] and omitted here.
OUTDOOR MOBILITYTESTS AND RESULTS
The V2V transmission control protocoldescribed earlier has been implemented andintegrated with General Motors (GM) V2Vsafety applications [4], which serve as the maintesting platform in this section and later, tounderstand how proposed V2V transmissioncontrol impacts these safety applications andhow accurate the real-time tracking is. Oneadditional protection was added to our ratecontrol: when the latest transmission from anHV is more than 0.5 s ago, a message will bescheduled for transmission. Our scalability eval-uation is presented later. In this section, pro-posed transmission control is mainly evaluatedwith two radios and vehicle mobility. These out-door mobility tests were conducted within theGM Technical Center; the test route is shownin Fig. 2.
Each test run had two vehicles acting as theleader and the follower. Each vehicle had a sin-gle-radio WSU. These two vehicles tracked eachother continuously during the test run. The safe-ty message size was around 400 bytes, and thePHY rate was 6 Mb/s for both radios [4]. Each
L t LU U t
U UL Lj
j( )( )
( ),minmax
max minmax min= +
−
−× −
IEEE Communications Magazine • November 2011136
Table 1. Overall mapping from channel utilizationto Tx power.
HV’s sensed channelutilization
Tx power to beused
> 77.4% 10 dBm
74.2% to 77.4% 11 dBm
71.0% to 74.2% 12 dBm
67.8% to 71.0% 13 dBm
64.6% to 67.8% 14 dBm
61.4% to 64.6% 15 dBm
58.2% to 61.4% 16 dBm
55.0% to 58.2% 17 dBm
51.2% to 55.0% 18 dBm
47.2% to 51.4% 19 dBm
< 47.2% 20 dBm
The proposed design
does not compro-
mise information
intensity during
channel congestion;
instead, a HV
reduces power to
mitigate congestion
while maintaining
decent tracking
accuracy on
surrounding RVs
toward itself to
ensure safety.
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IEEE Communications Magazine • November 2011 137
vehicle recorded its own GPS position and eachof the communicating RV GPS positions every100 ms. The RV’s coasted GPS position is thenlinearly interpolated to match with the exacttime epochs of the HV’s GPS time recordings.Every 100 ms, the actual tracking error is calcu-lated as the Euclidean distance of the true GPSposition of the HV and the interpolated andcoasting GPS position of the RV.
Two test runs were conducted for the routein Fig. 2. In the first run (with results presentednext), both the leader and follower vehicles usedour proposed transmission control. In the secondrun, both the leader and follower vehicles usedthe default 10 Hz beaconing of safety messageswith 20 dBm transmission power. Two communi-cation strategies are compared later and inTable 2.
A typical vehicle heading profile for the testrun is shown in Fig. 3a, and a typical vehiclespeed profile is shown in Fig. 3b. The four turnsin Fig. 2 can easily be identified in Fig. 3a whenthere is a 90˚ change of heading, and a signifi-cant speed slowdown and then speedup in Fig.3b. Note that 360˚ means 0˚; thus, there is nodiscrepancy at the 5th and 14th seconds in Fig.3a. In Fig. 3b, the speed slowdown and thenspeedup at the 174th second is due to a pedestri-an crossing.
Besides the tracking accuracy, which wasused as the main performance metric in ourprevious simulation study [9], the application-level target classification (TC) of the GM V2Vsafety applications is also reported. This TC isan HV’s lane level identification of an RV’sposition with respect to that HV’s own position
[4]. The more accurate this TC is, the better anHV can identify its relative position to that RV,and the better safety applications can functionaccordingly.
TEST RESULTS FORPROPOSED TRANSMISSION CONTROL
We only show results for the leader trackingthe follower due to space limitations. First, thesuspected tracking error of the follower isshown in Fig. 4a. Note that this suspectedtracking error is an HV’s guess of the trackingerror on the RV toward itself. This suspectederror is higher when the HV has made a turnsince the heading/speed of an HV changesdramatically during a turn. When an HV hasmade more unpredictable maneuvers (to theRV) and created larger suspected trackingerrors, more safety messages are broadcast inFig. 4b. Based on our on-demand rate controlin Eq. 1, a higher transmission probability isused by an HV when its suspected trackingerror is larger.
The actual tracking error on the leader isshown in Fig. 5a, which has a similar trend asthat of the suspected error by the follower inFig. 4a. Although the suspected tracking errordoes not match exactly with the true trackingerror, it gives the HV a rough estimate of howlarge the tracking error is on the RV. This justi-fies the use of a suspected tracking error for anHV to adapt its transmission rate. This on-demand style rate control on two vehicles collab-oratively reduces the total amount of messagesover the air and mitigates channel congestion.
Figure 2. Outdoor mobility test route within the GM Technical Center. These four corners of the route can be clearly identified in themobility profiles in Fig. 3 and our test results in Figs. 4 and 5.
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IEEE Communications Magazine • November 2011138
Finally, the TC correctness in Fig. 5b is almost100 percent, which is similar to the performanceof the default periodic communication (Table 2).These results confirm that the proposed V2Vtransmission control works according to ourintended design, especially the rate control part.Finally, Tables 2a and 2b show that the trackingperformance is symmetrical for both vehicles.
COMPARISON OFTWO COMMUNICATION STRATEGIES
Table 2a summarizes the results for the leaderbeing tracked by the follower. First, the defaultcommunication design always used 10 messages/sand 20 dBm transmission power. Our proposeddesign used around 2 messages/s and 20 dBmtransmission power (since the channel utilizationis below 1 percent). The tracking accuracy iscompared based on 95 percent cutoff error [9],which means that 95 percent of the time duringthe test run, the actual tracking error is belowthis number. For the default communicationdesign, its 95 percent cutoff error is 0.09 m,while that of our transmission control is 0.43 m.The lane level identification (i.e., TC correct-ness) for default communication design was 99.4percent correct, while that of our transmissioncontrol was 99.1 percent correct. It means thatour design can achieve similar performance inthe safety application level as that of the defaultcommunication design with an 80 percent reduc-tion in message rate.
Table 2b summarizes similar results for thefollower being tracked by the leader. Comparingthe statistics in Table 2a and 2b, both communi-cation designs have symmetrical tracking perfor-mance for the leader and follower. Note thatthis test scenario only has two radios; thus, it ismainly used to check whether the proposedtransmission control functions according to ourintended design. In such a simple scenario, bothcommunication designs can achieve decent track-ing accuracy; thus, the results in Table 2 do notindicate the scalability of the default 10 Hz com-munication design.
OUTDOOR SCALABILITYTESTS AND RESULTS
In this section, the proposed transmission con-trol was evaluated with 15 radios, and our designis shown to outperform the default 10 Hz bea-coning with 20 dBm transmission power. Thesescalability tests were conducted within a parking
Figure 3. A typical vehicle trajectory profile for the mobility test route on Fig. 2: a) a typical vehicle heading profile; b) a typical vehiclespeed profile.
Table 2. Outdoor mobility test results for the route in Fig. 2: a) follower vehicletracked leader vehicle; b) leader vehicle tracked follower vehicle.
(a)
Parameters Default comm. design Proposed Tx control
Tx message rate 10 msg/s 1.87 msg/s
Tx power 20 dBm 20 dBm
Channel utilization < 2% < 1%
PER < 2% < 10%
95% cutoff error 0.09 m 0.43 m
TC correctness 99.4% 99.1%
(b)
Parameters Default comm. design Proposed Tx control
Tx message rate 10 msg/s 1.85 msg/s
Tx power 20 dBm 20 dBm
Channel utilization < 2% < 1%
PER < 2% < 10%
95% cutoff error 0.11 m 0.45 m
TC correctness 99.3% 98.2%
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lot in the GM Technical Center. This smallparking lot has a square size of roughly 100 m ×80 m; the test route is illustrated in Fig. 6.
There were four stationary WSUs in theparking lot: three WSUs with dual radios andone WSU with single radio. Each test run hadtwo vehicles acting as the leader and the fol-lower. Each vehicle had two dual-radio WSUs;that is, there were four radios on each vehicle.Each dual-radio WSU ran two copies of testedcommunication protocol so that a dual-radioWSU acted like two single-radio WSUs. Thesetwo vehicles tracked each other continuouslywhile they were circling around this parkinglot for 5 min. During these test runs, the mes-sage size was around 400 bytes and the PHYrate was 6 Mb/s for all radios [8]. For each 100ms, the actual tracking error is calculated asearlier.
This test route in Fig. 6 was more challengingthan the test route mentioned earlier (Fig. 2) inthe following two aspects:• There were more radios trying to share the
wireless channel, thus potentially creatingmore channel collisions and a higher PER.
• There were more turns since vehicles werecircling around a small parking lot.From the evaluation earlier, one can observe
that an HV changes its speed and heading quick-ly during a turn, so it is harder for an RV totrack this HV properly if there are messages lostduring a turn. Two test runs were conducted. Inthe first run, all 15 radios used our proposedtransmission control. In the second run, all 15radios used default 100 ms periodic beaconing ofsafety messages with 20 dBm transmission power.Both the leader and follower vehicles trackedeach other continuously during these test runs.
Table 3a summarizes the results for the lead-er being tracked by the follower. First, thedefault communication always used 10 mes-sages/s and 20 dBm transmission power. Ourproposed design used around 2 messages/s and20 dBm transmission power (since the channelutilization is around 1–3 percent). For thedefault communication design, its 95 percentcutoff error was 2.41 m while that of our designwas 0.36 m. The lane level identification (i.e.,TC correctness) for default communicationdesign was 87.4 percent correct while that of our
IEEE Communications Magazine • November 2011 139
Figure 4. Follower’s message transmission behavior for the mobility test route on Fig. 2: a) suspected tracking error sensed by the follower;b) message transmission decision made by the follower.
Figure 5. Tracking accuracy of the leader by the follower for the mobility test route on Fig. 2: a) actual tracking error of the leader by thefollower; b) TC correctness of the leader toward the follower.
design was 99.7 percent correct, which meansthe proposed transmission control can achievemuch better tracking performance than that ofthe default communication design.
Table 3b summarizes the results for the fol-lower being tracked by the leader. Comparingthe statistics in Table 3a and 3b, both commu-nication designs have roughly symmetricaltracking performance for the leader and thefollower. However, the tracking accuracy andlane level identification of default communica-tion design were very poor compared to thoseof our transmission control protocol. Uponcloser inspection of the tracking error of thedefault 10 Hz communication, large trackingerrors usually happened when the HV made aturn, but the RV did not get the message fromthat HV (due to consecutive channel colli-sions) and assumed the HV was stil l goingstraight ahead.
The main reason behind this huge perfor-mance difference in Table 3 is that the default10 Hz communication design produced too manymessages by all 15 radios in such a small parkinglot and thus resulted in a higher channel PER.Our transmission control uses on-demand ratecontrol: an HV uses a higher transmission prob-ability to send out messages if it suspects thatRVs have large tracking error toward its ownposition. Otherwise, an HV tends to stay quietand let other vehicles use the channel. This sta-tistical multiplexing allows all vehicles to reducethe total message amount and improves theoverall efficiency of information exchange. The
results in Table 3 also indicate the scalability ofour proposed transmission control.
SUMMARY AND FUTURE WORKThis article reports the implementation and test-ing results of our proposed V2V transmissioncontrol protocol, which adapts the message rateand transmission power based on a closed-loopcontrol concept that accounts for wireless unreli-ability and channel congestion. The evaluationspresented show that our design works well inpractice and is a promising solution to addressthe scalability of V2V safety communications.Note that the proposed design is meant to pro-vide a scalable communication control for thefrequently exchanged basic safety messages. Forevent-driven messages of different priorities,they can still be broadcast with different pairs ofspecified transmission rate and power. Ourfuture work includes large-scale trials of pro-posed transmission control and empirical param-eter optimization.
However, challenges still await this research.Although the proposed design seems to providea good basic policy for vehicles to talk to eachother for safety, it needs to be further improvedwith additional intelligence (e.g., incorporatingtraffic engineering intuitions to make it morerobust in challenging traffic scenarios). Imaginea highway scenario where the high-occupancyvehicle (HOV) lane is almost empty while non-HOV lanes are fully packed with vehicles. AnHV in the HOV lane still needs to send out
Figure 6. Outdoor scalability test route in a parking lot of the GM Technical Center. This test route featured more wireless radios (thusmore collisions and interference) than the test route in Fig. 2.
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IEEE Communications Magazine • November 2011 141
enough messages with enough power to reach itsfront/back RVs even when the wireless mediumis highly congested due to numerous messagesfrom non-HOV lanes. Different scenarios likethis need to be thoroughly tested. Another chal-lenge is the computation time/resource requiredfor each vehicle to track a large number ofneighboring vehicles in real time and to checkfor various hazardous situations based on thisproximity awareness.
REFERENCES[1] R. Sengupta et al., “Cooperative Collision Warning Systems:
[2] Wireless Access in Vehicular Environments (WAVE) inStandard 802.11, Specific Requirements: IEEE802.11p/D2.01, Mar. 2007.
[3] F. Bai et al., “Towards Characterizing and ClassifyingCommunication-based Automotive Applications from aWireless Networking Perspective,” Proc. 1st IEEE Wksp.Automotive Networking and App., Dec. 2006.
[5] Vehicle Safety Communications Consortium (VSCC),“VSC Project Final Report,” 2005.
[6] M. Torrent-Moreno et al., “Vehicle-to-Vehicle Communi-cation: Fair Transmit Power Control for Safety-CriticalInformation,” IEEE Trans. Vehic. Tech., vol. 58, no. 7,Sept. 2009.
[7] C. Robinson et al., “Efficient Coordination and Trans-mission of Data for Vehicular Safety Applications,”Proc. 3rd ACM VANET, Sept. 2006.
[8] S. Rezaei et al., “Tracking the Position of NeighboringVehicles Using Wireless Communications,” Elsevier J.Transportation Research Part C: Emerging Technolo-gies, Special Issue on Vehicular Communication Net-works, June 2009.
[9] C. L. Huang et al., “Adaptive Inter-Vehicle Communica-tion Control for Cooperative Safety Systems,” IEEE Net-work, Jan. 2010.
[10] P. Gupta and P. R. Kumar, “The Capacity of WirelessNetworks,” IEEE Trans. Info. Theory, vol. 46, no. 2,Mar. 2000.
[11] Y. P. Fallah et al., “Analysis of Information Dissemina-tion in Vehicular Ad-Hoc Networks with Application toCooperative Vehicle Safety Systems,” IEEE Trans. Vehic.Tech., vol. 60, no. 1, Jan. 2011.
[12] C. L. Huang et al., “Implementation and Evaluation ofScalable Vehicle-to-Vehicle Transmission Control Proto-col,” Proc. IEEE Vehicle Net. Conf., Dec. 2010.
Sept. 2009.[15] L. Cheng et al., “Mobile Vehicle-to-Vehicle Narrow-
Band Channel Measurement and Characterization ofthe 5.9 GHz Dedicated Short Range CommunicationFrequency Band,” IEEE JSAC, vol. 25, no. 8, Oct. 2007.
BIOGRAPHIESCHING-LING HUANG ([email protected]) received B.S.and M.S. degrees from National Taiwan University, both inelectrical engineering (NTUEE). His Master’s study in theComputer Science group of NTUEE focused on networkingand mobile communication. He is currently pursuing hisPh.D. degree in the Systems Engineering group, Civil andEnvironmental Engineering, University of California atBerkeley. His current research interests include control andestimation over an unreliable channel, vehicular networks,and cooperative active safety designs for intelligent trans-portation systems.
HARIHARAN KRISHNAN received his Ph.D. from the Universityof Michigan, his M.S. from the University of Waterloo, andhis B.E. from Anna University, India. Currently, he is thethrust area lead on the GM research program on vehicle-to-vehicle (V2V) and vehicle-toinfrastructure (V2I) commu-nications. He works on various research projects in the areaof V2X communication including the Vehicle Safety Com-munications — Applications project conducted by GM,
Ford, Mercedes, Toyota, and Honda under a cooperativeagreement with the U.S. Department of Transportation.Prior to this, he was an assistant professor at the NationalUniversity of Singapore from 1993 to 2000. He has over 60publications in internationally refereed journals and confer-ence proceedings, and over 300 citations. He serves as anAssociate Editor of the IEEE Control System Society andTransportation Research — Part C.
RAJA SENGUPTA received his Ph.D. degree from the Electri-cal Engineering and Computer Science Department, Uni-versity of Michigan, Ann Arbor, in 1995. He is an associateprofessor in the Systems Engineering Program within Civiland Environmental Engineering, University of California atBerkeley, where he is also director of the PATH WirelessLaboratory and deputy director of the Center for Collabo-rative Control of Unmanned Vehicles. He is an AssociateEditor of IEEE Control Systems and the Journal of Intelli-gent Transportation Systems. He was Program Chair ofthe IEEE Conference on Autonomous Intelligent Net-worked Systems 2003 and Co-General Chair of the 1stACM MOBICOM Workshop on Vehicular Ad Hoc Networks(2004).
YASER POURMOHAMMADI FALLAH is an assistant professor inthe Computer Science and Electrical Engineering Depart-ment at West Virginia University (WVU). Prior to joiningWVU in 2011, he was a research scientist at the Universityof California at Berkeley, Institute of Transportation Stud-ies. His current research activities are in the areas of net-worked cyber physical systems and wireless networking forintelligent transportation systems. He obtained his Ph.D. inelectrical and computer engineering from the University ofBritish Columbia in 2007. Prior to his Ph.D., he was withIBM Canada. His research has been supported by numerousawards including an NSERC postdoctoral fellowship, NSERCpostgraduate scholarship, and Bell Canada graduate schol-arship. He served as Co-Chair of the technical programs ofIEEE WiVEC ’11 and PIMRC-ITN ’11.
Table 3. Outdoor scalability test results for the route in Fig. 3: a) follower vehi-cle tracked leader vehicle; b) leader vehicle tracked follower vehicle.
(a)
Parameters Default comm. design Proposed Tx control
Tx message rate 10 msg/s 1.83 msg/s
Tx power 20 dBm 20 dBm
Channel utilization 8–10% 1–3%
PER 10–30% < 5%
95% cutoff error 2.41 m 0.36 m
TC correctness 87.4% 99.7%
(b)
Parameters Default comm. design Proposed Tx control
