Dynamic Control of Beacon Transmission Rate withPosition Accuracy in Vehicular Networks

Sandy Bolufe1, Samuel Montejo-Sanchez1, Cesar A. Azurdia-Meza1, Sandra Cespedes1,Richard Demo Souza2, and Evelio M. G. Fernandez3

1Department of Electrical Engineering, Universidad de Chile, Santiago, Chile,(sbolufe,smontejo,cazurdia,scespedes)@ing.uchile.cl

2Department of Electrical and Electronics Engineering, Federal University of Santa Catarina,Florianopolis, Brazil, richard.demo@ufsc.br

3Department of Electrical Engineering, Federal University of Parana, Curitiba, Brazil,evelio@ufpr.br

Abstract

The proper performance of cooperative safetyapplications in vehicular networks dependsof the exchange of beacon messages betweenneighboring vehicles. A challenge in these net-works is to control the beacon transmissionrate in real-time to meet the position accu-racy requirements of safety applications. Inthis paper, we propose an adaptive beaconingalgorithm based on dynamic control of beaconrate. The beacon rate is adjusted dynamicallyas a function of the vehicle movement status,to constrain the position error computed bysurrounding vehicles. The results obtainedfrom a realistic simulation framework showthat, the proposed algorithm successfully con-trols the beacon rate to maintain a target posi-tion accuracy. Further, it adapts to the vehic-ular traffic dynamics, being able to maintaina better position accuracy compared to otherfixed beaconing algorithms.

1 Introduction

Intelligent Transport Systems (ITS) are a technologydesigned to support road safety and traffic efficiencyapplications [MP16]. In these systems, the vehicles areequipped with wireless communication devices allow-ing the information exchange between vehicles, andwith infrastructure devices. The Dedicated Short-Range Communication (DSRC) is a short and mediumrange radio access technology that operates in the 5.9GHz frequency band, providing communication sup-port in vehicular networks. This technology relies on

Copyright c© held by the paper authors.

In Proceedings of the III Spring School on Networks (SSN 2017),Pucon, Chile, October 19-20, 2017, published at http://ceur-ws.org/.

several standards designed for vehicular communica-tions, including the IEEE 802.11p standard [IEE10],which defines physical (PHY) and medium access con-trol (MAC) layers for Wireless Access in Vehicular En-vironments (WAVE) [WAV17].

Cooperative vehicular networks have been identi-fied as a promising technology to enable ITS. Thesenetworks require the continuous exchange of status in-formation between neighboring vehicles to support co-operative awareness applications. In this process, eachvehicle periodically transmits one-hop broadcast mes-sages, called beacons [ETS14], containing its position,speed, acceleration, and heading. The beaconing al-lows the receiving vehicles to create a local dynamicmap (LDM) of the vehicular environment, which isused by cooperative safety applications to avoid trafficaccidents. For instance, applications such as intersec-tion collision warning and lane change assistance usethe beacon information to detect and mitigate poten-tially dangerous situations in real-time.

The high mobility of vehicles leads to a rapid ex-piration of the beacon information. In consequence,the position inaccuracies can impact the proper perfor-mance of cooperative safety applications, which rely onreal-time accurate information. Beacon transmissionrate directly translates into accuracy of cooperativeawareness [SLS+10]. Finding the appropriate beaconrate according to the scenario dynamics is essential forthe system performance. In traffic jams a beacon rateof 1 beacon/s may be sufficient to provide the positionaccuracy needed by safety applications. However, thisbeacon rate is not sufficient to obtain a good level ofposition accuracy on a multi-lane high speed highwaywith frequent lane changes.

In cooperative vehicular systems, the precision andfreshness of the status information is indispensable forthe decision-making process, in real-time, of safety ap-plications. The position error computed by neighbor-ing vehicles directly impacts on the vehicle’s systemscapability to detect and mitigate potentially danger-ous situations on time [SLS+10]. In this paper, wepropose and evaluate a novel adaptive beaconing al-

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gorithm that dynamically adjusts the beacon rate tomeet the position accuracy requirements of coopera-tive safety applications. The algorithm adjusts thebeacon rate according to the vehicle movement statusto limit the position error computed by surroundingvehicles under a target threshold.

2 Dynamic Control of Beacon Rate

The Dynamic Control of Beacon Transmission Rate(DC-BTR) algorithm computes the beacon transmis-sion rate required by a vehicle ni as a function of itsmovement status, to limit in real-time the position er-ror computed by surrounding vehicles.

We represent the average position error (E) as in[SLS+10], which expresses the mean error assumingthat the event of looking up the position in the LDMdatabase is uniformly distributed between the mini-mum and maximum time difference to the transmis-sion event of the beacon,

E =bEc+ dEe

2, (1)

where bEc denotes the lower error boundary resultingfrom the transmission delay (tD), and dEe is the upperboundary that occurs when the position of a vehicle islooked up right before receiving the next beacon.

From kinematic equations, E is expressed as a func-tion of the velocity (vi) and acceleration (ai) of ni,

2Ei = vitD + Ibi

(vi +

aiIbi2

)+ tD(aiIbi + vi), (2)

where Ibi is the beacon interval of ni (equivalent tothe inverse of Rbi). We assume beacon messages ofthe same size (bz) and equal data rate (RD), so tD isthe same for all vehicles.

From (2), a second degree polynomial of the formP (Ibi) = AI2bi +BIbi + C can be obtained as,

aiI2bi + 2(vi + aitD)Ibi + 4(vitD − Ei) = 0. (3)

In the general case of ai 6= 0, the polynomial solu-tions are computed as follow,

Ibi{1,2} =−B ±

√D

2A, (4)

where D = B2 − 4AC. On the other hand, if ai = 0,the solution is,

Ibi =2(Ei − vitD)

vi. (5)

Fig. 1a shows the velocity developed by a vehiclein 12 s, with three different constant accelerations: 1,3, and 5 m/s2. The Ib required by the vehicle to con-straint (E) under a target threshold of 1 m, computedby (3), is illustrated in Fig. 1b. The Rb correspond-ing to the vehicle beacon interval is illustrated in Fig.

1c. To obtain a position accuracy of 1 m, the vehicleuses an adaptive beacon rate, broadcasting more than30 beacon/s when the velocity reaches 60 m/s and theacceleration is 5 m/s2. Fig. 1d shows that the averageposition error obtained remains all the time under thepreset threshold of 1 m.

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Figure 1: Behavior in time: a) Velocity , b) Beaconinterval, c) Beacon rate, and d) Average position error.

Algorithm 1 describes the steps followed by DC-BTR to compute the beacon rate in real-time accord-ing to the velocity and acceleration of the vehicle ni(Line 1) and the target position error (Line 2). Thenext beacon interval is computed by ni at each beacontransmission. Lines 9-25 involve the decisions associ-ated according to the movement status of ni: repose(Line 9-10), the beacon transmission rate is set to 1beacon/s equivalent to the minimum value required forthe proper performance of the less demanding vehicu-lar applications [ETS09]; accelerated movement (Line11-14), the beacon transmission rate is computed us-ing (4); uniform movement (Line 15-18), the beacontransmission rate is computed according to (5); decel-eration (Line 19-25) in order to notify with immediacyto surrounding vehicles a possible braking, it is set acritical beacon interval (Ibc). It should be noted thatif two valid solutions are found, the solution that gen-erates the lowest channel load is selected (see Line 12and Line 21).

3 Performance Evaluation

The DC-BTR algorithm has been evaluated in a ur-ban scenario using the well established Veins frame-work [SGD11].

3.1 Evaluation Scenario

The simulations correspond to a real map section ofChicago city, USA, with an area close to 1 km2. Fig.2a and Fig. 2b show the scenario seen from GoogleEarth and Sumo traffic simulator, respectively. Thezone has several traffic lights and multi-lane roads with

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a maximum speed limit of 120 km/h. We use a vehic-ular traffic model based on flows, where vehicles movebetween a point of origin and destination. Fig. 2ashows the seven flows that have been configured with20 vehicles in a simulation time of 500 s. The vehi-cles use the IEEE 802.11p EDCA model [ES12] of theVeins Framework to represent the MAC/PHY layer.The radio signal propagation is modeled with the Two-Ray Interference path loss model [SJD12], with εr =1.02. The communication only occurs on the controlchannel (CCH) without considering the multi-channeloperation. The beacon have 250 bytes and are trans-mitted with the priority of the voice access category.Each vehicle is 5 m long, 2 m wide and has an acceler-ation up to 0.8 m/s2, and deceleration up to 4.5 m/s2.The antenna height is 1.5 m and data rate is 6 Mbps.Table 1 summarizes the main simulation parameters.

Table 1: Simulation ParametersParameter ValueCCH center frequency 5.890 GHzChannel bandwidth 10 MHzTransmit power 20 dBmAverage position error (E) 1 mCritical beacon interval (Ibc) 0.2 sBeacon size (bz) 250 bytesCW [3, 7]AIFSN 2Receiver sensitivity - 82 dBmThermal noise - 110 dBmData rate (RD) 6 MbpsAntenna gain 0 dBAntenna height 1.5 mPath loss model Two-Ray Interference

(a) (b)

Figure 2: Real map section of Chicago, USA, seenfrom: a) Google Earth, b) SUMO.

3.2 Simulation Results

DC-BTR has been compared with the basic fixed bea-coning process, which we named as fixed beaconingalgorithm (FB). As in [SLS+10], four typical fixed bea-con rates between 1 and 10 beacon/s have been inves-tigated. Both beacon control rate approaches use afixed transmit power of 20 dBm.

Fig. 3a illustrates the movement status of a genericvehicle in the scenario. The acceleration and velocityare represented in color blue and red, respectively. Themobility pattern shows a continuous change in vehiclestatus between acceleration, deceleration, and repose,which are typical changes of urban environments. Fig.3b shows the adjustments that the DC-BTR imposes,

Algorithm 1: DC-BTR

Input : {vi, ai, tD, Ei}Output: {Rbi}Algorithm to execute on each beacon transmission;

1 Get vi, ai;

2 Set Ei;3 tD ← bz/RD;4 A ← ai;5 B ← 2(vi + aitD);

6 C ← 4(vitD − Ei);7 D ← B2 − 4AC;

8 Ibi{1,2} ← (−B ±√D)/2A according to (4);

9 if (vi == 0 && ai == 0) then10 Ibi ← 1;

11 else if (vi >= 0 && ai > 0) then12 Ibi ← maximum{Ibi{1} , Ibi{2}};13 if (Ibi > 1) then14 Ibi ← 1;

15 else if (vi > 0 && ai == 0) then16 Ibi ← 2(Ei − vitD)/vi according to (5);17 if (Ibi > 1) then18 Ibi ← 1;

19 else if (vi > 0 && ai < 0) then20 if (D > 0) then21 Ibi ← maximum{Ibi{1} , Ibi{2}};22 if (Ibi > Ibc) then23 Ibi ← Ibc ;

24 else if (D <= 0) then25 Ibi ← Ibc ;

26 Rbi ← 1/Ibi ;27 Rbi ← ceil(Rbi);28 return Rbi ;

in real-time, on beacon interval (color blue) to meeta target average position error of 1 m. Fig. 3b alsoshows in color red the beacon rate corresponding to thebeacon interval required by DC-BTR. Note that, theincrease in velocity demands an increase in the beaconrate, ensuring that, for high velocity values, the bea-con interval is shortened to maintain the target posi-tion accuracy, as illustrated in the interval from 150s to 200 s. In this time interval the velocity achieves28 m/s, demanding 15 beacon/s. The adjustment notonly responds to changes in speed, but also to varia-tions of acceleration, as illustrated in the time inter-vals where the vehicle moves with constant velocity.In this time intervals, the transmission rate oscillatesbetween 5 and 3 beacon/s. Note also that, when thevehicle is stopped, DC-BTR sets a rate of 1 beacon/s,which is considered the minimum beacon rate. In spe-cial cases where the vehicle slows down (see intervalfrom 100 s to 105 s), DC-BTR uses a critical beaconinterval equal to 0.2 s, so that neighboring vehicles im-mediately record any changes in their movement sta-

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Figure 3: Vehicle parameters in time: a) Velocity and acceleration, b) Beacon interval and beacon rate.

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Figure 4: Average position error in time for fixed and adaptive beacon control rate approach.

tus. Fig. 4 evidences the effectiveness of DC-BTR forthe dynamic control of the beacon rate, restricting theaverage position error computed by surrounding vehi-cles to a value that remains most of the time below 1m. As can be seen, the estimated error complied withthe imposed constraint, except on some occasions, dueto packet collisions which lead to harmful position er-rors. Note that DC-BTR achieves a higher positionaccuracy than FB algorithms for the different beacontransmission rates, especially for higher velocities.

4 Conclusion and Future Works

In this paper we have proposed the use of an adap-tive beaconing algorithm in cooperative vehicular net-works, which dynamically adjusts the beacon trans-mission rate to meet the position accuracy require-ments of safety applications. The simulation resultshave shown that the proposed algorithm successfullylimits the average position error under a target thresh-old. Further, it outperforms the fixed beaconing algo-rithms addressed in this paper, in terms of positionaccuracy. However, packet collisions lead to harmfulposition errors. For this reason, in future works weplan to propose a joint power and rate control algo-rithm, to limit the position error while reducing packetcollisions.

Acknowledgment

The authors acknowledge the financial support of CONI-CYT Doctoral Grant No. 21171722; FONDECYT Post-doctoral Grant No. 3170021; Project ERANET-LACELAC2015/T10-0761; as well as the Complex EngineeringSystems Institute, ISCI (CONICYT: FB0816).

References

[ES12] D. Eckhoff and C. Sommer. A multi-channelieee 1609.4 and 802.11p edca model for theveins framework. In 5th ACM/ICST SIMUTools,2012.

[ETS09] European Telecommunications Standards Insti-tute ETSI. Intelligent transport systems; vehic-ular communications; basic set of applications;definitions, tech. rep. 102 638 v1.1.1, 2009.

[ETS14] European Telecommunications Standards Insti-tute ETSI. Part 2: Specification of cooperativeawareness basic service, tech. specif. 302 637-2v1.3.2, 2014.

[IEE10] Wireless lan medium access control (mac) andphysical layer (phy) specifications amendment 6:Wireless access in vehicular environments, ieeestd. 802.11p, 2010.

[MP16] A. Maimaris and G. Papageorgiou. A review ofintelligent transportation systems from a com-munications technology perspective. In 19thITSC, pages 54–59. IEEE, 2016.

[SGD11] C. Sommer, R. German, and F. Dressler. Bidi-rectionally coupled network and road traffic sim-ulation for improved ivc analysis. IEEE Trans-actions on Mobile Computing, 10(1):3–15, 2011.

[SJD12] C. Sommer, S. Joerer, and F. Dressler. On theapplicability of two-ray path loss models for ve-hicular network simulation. In IEEE VNC, pages64–69, 2012.

[SLS+10] R. Schmidt, T. Leinmuller, E. Schoch, F. Kargl,and G. Schafer. Exploration of adaptive beacon-ing for efficient intervehicle safety communica-tion. IEEE Network, 24(1):14–19, 2010.

[WAV17] Ieee draft guide for wireless access in vehicularenvironments (wave) - architecture, p1609.0/d9,2017.

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