smart automotive lighting for vehicle safetyhsinmu/wiki/_media/paper/cm... · 2014-05-05 · 52...

IEEE Communications Magazine • December 201350 0163-6804/13/$25.00 © 2013 IEEE

1 For example, when esti-mating the distance to avehicle using a camera.

INTRODUCTIONThe conventional paradigm for vehicle safety hasbeen an “independent” approach — to incorpo-rate a large number of sensors in each vehicle sothat sufficient coverage can be provided to iden-tify neighboring objects that could cause acci-dents. The main downside of such an approachis the high cost of the system as a result of thelarge number of sensors. Recent advances ofcommunication and networking technologieshave enabled a new cooperative paradigm forvehicle safety systems, in which, via direct vehi-cle-to-vehicle (V2V) communication links, vehi-cles not only share information about their

current status such as positions and speed, butalso what they observe of neighboring objects atdifferent locations. The advantages of the newparadigm include:• Wireless communications and networks can

penetrate or route around (i.e., utilizingmultihop communications) obstacles block-ing line-of-sight (LOS), effectively extend-ing the sensor coverage to include all ofthose neighboring vehicles.

• Cooperation among vehicles can reduceuncertainty of measurements [1], such asthe position and the speed of a certain vehi-cle, in multiple ways:–Self-information of a vehicle is more accu-rate than observations from neighboringvehicles.–Observations from a nearby vehicle aremore accurate than observations from a dis-tant vehicle.1–Combining observations of the same objectfrom multiple vehicles can reduce the noisein the measurements.

• The system can have lower cost as a directresult of the lower required number of sen-sors in each vehicle — information does nothave to be only from on-board sensors, butalso from sensors in neighboring vehicles.

THE COOPERATIVE PARADIGM REQUIRESRELIABLE V2V COMMUNICATIONS

Dedicated short-range communications (DSRC)is often considered the most promising V2Vtechnology [2]. The technology incorporates aset of physical, data link, and higher layer stan-dards that use the 5.9 GHz radio spectrum toenable V2V and vehicle-to-infrastructure (V2I)communications. Although the standards inDSRC have been drafted or ratified for morethan a few years, to this date there is still nocommercial adoption of the technology. Thefuture of DSRC is not clear as of today. Forexample, the U.S. government will make a deci-sion regarding the technology at the end of 2013,

ABSTRACT

It is believed that vehicle-to-vehicle (V2V)communications and accurate positioning withsub-meter error could bring vehicle safety to adifferent level. However, to this date it is stillunclear whether the envisioned V2V standard,dedicated short-range communications, canbecome available in commercially available vehi-cle products, while widely available consumer-grade GPS receivers do not provide the requiredaccuracy for many safety applications. In thisarticle, combining visible light communicationsand visible light positioning, we propose the useof smart automotive lighting in vehicle safetysystems. These lights would be able to providethe functions of illumination and signaling, reli-able communications, and accurate positioningin a single solution. The proposed solution haslow complexity, and is shown to be scalable inhigh vehicle density and fast topology changingscenarios. In this article, we also present severaldesign guidelines for such a system, based on theresults of our analytic and empirical studies.Finally, evaluation of our prototype provides evi-dence that the system can indeed detect poten-tial risks in advance and provide early warningsto the driver in real-world scenarios, loweringthe probability of traffic accidents.

VISIBLE LIGHT COMMUNICATIONS: THE ROAD TOSTANDARDIZATION AND COMMERCIALIZATION

Shun-Hsiang Yu, Oliver Shih, and Hsin-Mu Tsai, Intel-NTU Connected Context Computing Center and National Taiwan University

Nawaporn Wisitpongphan, King Mongkut’s University of Technology North BangkokRichard D. Roberts, Intel Labs

Smart Automotive Lighting for Vehicle Safety

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IEEE Communications Magazine • December 2013 51

based on real-world tests carried out in the pasttwo years [3].

The main reason that V2V technology hasnot yet seen its adoption is that there is very lowincentive for early adopters to purchase a newvehicle with the technology. Many envisionedapplications that use multihop communicationsrequire a minimum market penetration rate of10 percent or more [4].

The implication of the 10 percent minimummarket penetration is that even if every newvehicle were equipped with a new V2V radiostarting from today, it will still take more thantwo years before these applications can be func-tional on the road.2 As a result, early adoptersdo not gain any benefit in purchasing a V2V-equipped vehicle, which has a higher price tag.To jumpstart the initial market penetration rate,we believe the key directions include:• To discover applications that can immedi-

ately provide benefits to the driver on theday they obtain the new vehicle

• To lower the complexity of the technologyso that the added cost to the vehicle prod-uct is minimized, and we do not rely on alarge sale quantity to bring down the costs

The latter implies that the communications tech-nology should be designed to fulfill the require-ments of only a small set of key applications.

Visible light communications (VLC) utilizemodulated optical radiation in the visible lightspectrum to carry digital information in freespace. A VLC system usually uses an LED asthe transmitting component and a photodiode asthe receiving component. Over the past fiveyears, LED has become very common in auto-motive lighting due to its long service life, highresistance to vibration, and better safety perfor-mance due to its short rise time. Today, LEDscan be found in center high mount stop lamps(third brake lights), brake lights, turn signals,and headlamps in many commercial vehicles. Asa result, VLC becomes a new and attractivesolution to realize V2V communications [5–7] ina completely different way.

In this article, we propose the use of VLC invehicles for several key safety applications, creat-ing smart automotive lighting that combines thefunctions of illumination and signaling, commu-nications, and positioning. As shown in Fig. 1, inthe case of cars, a VLC transmitter is connectedto each of the two headlamps and two taillightsto create four VLC-capable lights transmittingthe same signal; a photodetector is placed nextto each of these four lights and connected to aVLC receiver. Additional photodetectors can beinstalled on the rear facing side of each of thetwo side rearview mirrors to provide communi-cation coverage to vehicles on the side. In thecase of motorcycles or scooters, both the head-lamp and the taillight are connected to the VLCtransmitters, creating two VLC-capable lightstransmitting the same signal, and a photodetec-tor is installed right next to each of these twolights and connected to VLC receivers. As theoptical signal is modulated at a high frequency,persistence of vision causes these optical signalsto be invisible to human eyes. Therefore, theVLC-capable lights can still retain their originalillumination and signaling functions.

The unique properties of optical propagationand VLC present many advantages over conven-tional radio frequency (RF) communications forsafety applications:

Low complexity and low cost: The design ofthe VLC transmitter and receiver is much lesscomplex than a comparable RF transceiver, dueto a much less severe multipath effect. Com-bined with simple modulation schemes and thefact that the main transmitting component,LED, already exists in vehicles, this minimizesthe additional cost to realize smart automotivelighting.

Scalability: In scenarios with high vehicledensity, conventional V2V communicationsusing RF typically experience longer delay andlower packet reception rate due to the largenumber of nodes that participate in channel con-tention. An adaptive transmission power schemecan be used to mitigate the problem, but requireshigh overhead to accurately estimate the numberof nodes in the neighborhood, which could alsoreduce the reliability. On the other hand, in thecase of VLC, only a small number of nodes with-in direct LOS of the receiver are in the samecontention domain, and those nodes are of themost importance since they are the vehicles mostlikely to collide with the receiving vehicles. Thisfiltering mechanism depends on the opticalpropagation property, does not require any over-head, and hence is highly scalable.

Positioning capability: Due to the high direc-tivity of visible light propagation, it is possible toperform accurate relative positioning betweenvehicles [8]. Compared to a typical positioningerror of up to 10 m with GPS [9], the positioningerror of visible light positioning (VLP) is on theorder of only tens of centimeters, much more suit-able for vehicle safety applications.

Security: For a malicious attacker to send fal-sified information or jam a VLC receiver, due tothe closer operation range and the LOS-onlypropagation property of VLC, the attacker hasto be in visual range of the victim vehicle for anextended period of time, which renders theaction less likely compared to when using con-ventional RF communications. In addition, thepositioning capability can be used to provide anadditional layer of security by verifying whetherthe received message is sent from a correct orpossible position.

VLC also presents a few challenges whenused in outdoor environments, most of whichhave been investigated in existing literature [10].

Severe weather conditions: Heavy fog, rain,or snow could create additional attenuation tothe transmitted optical signal, shortening theoperation range. However, existing work [11] hasshown that a VLC receiver has better sensitivitythan human eyes; this implies that, in these dras-tic weather conditions, VLC will be able toreceive a message before human eyes can per-ceive the light from the same transmitting light,proving the usefulness of VLC.

Sunlight and ambient light: Direct sunlightor strong ambient light could saturate the VLCreceiver. This is usually addressed by utilizing afrequency higher than 1 kHz and a high pass fil-ter to eliminate the majority of the solar radia-tion power. However, the shot noise induced by

2 Based on our investiga-tion of the numbers ofvehicle sales and regis-tered vehicles, this state-ment is true for both theU.S. and Taiwan markets.

The implication ofthe 10 percent

minimum marketpenetration is that,even if every new

vehicle wereequipped with the

new V2V radio start-ing from today, itwill still take more

than two yearsbefore these applica-

tions can be func-tional on the road.


IEEE Communications Magazine • December 201352

the received sunlight or ambient light remainsand becomes the dominating noise source thatdetermines the performance of VLC.

The rest of this article is organized as follows.We present a few applications that are enabledor enhanced by smart automotive lighting. Wepresent the evidence that VLC is more scalableto vehicle density and rapid topology changethan RF communications for vehicle safety appli-cations. We show the results from a numericalanalysis to quantify the positioning error perfor-mance of VLP for vehicles. We present thedesign of our smart automotive lighting proto-type on two scooters and the results of a real-world evaluation of our prototype. Finally,concluding remarks and future work directionsare given. In addition, a brief overview of theVLC link budget model is presented in theappendix.

APPLICATIONS

COLLISION WARNING AND AVOIDANCECombining the communication and positioningcapabilities of smart automotive lighting andintegrating them into the vehicle safety system,each vehicle can build a map that has the rela-tive positions, as well as the speed, brake status,heading, and so on of all surrounding vehiclesthat has a direct path to it (and thus the VLCtransmission is not blocked). The relative posi-tions can be obtained by VLP, while the otherscan be obtained from packets sent via VLC byother vehicles. The map with the estimated posi-tions of these vehicles can be presented to thedriver so that he/she can adjust the vehicle’sheading or speed to avoid collisions. The systemcan also provide early detection of stopped andovertaking vehicles. In addition, the informationcan be used to estimate the trajectories of thesevehicles in the next few seconds; if the projectedpaths of two vehicles cross with each other, awarning can be presented to the driver to takeappropriate evasive actions or slow down. Coop-erative forward collision warning, which utilizesthe same concept, is identified as one of theeight high-priority and representative vehiclesafety applications enabled by DSRC [12]; [12]also identifies the requirements for the applica-tion: the maximum required communicationrange is 150 m, the latency needs to be less than100 ms, and the size of the application payload is419 bits (53 bytes). Smart automotive lightingcan certainly satisfy these requirements and offera low-cost alternative to DSRC, while it can alsoprovide more accurate positioning than GPS.

LANE CHANGE ASSISTANCE/WARNINGSimilar to the collision warning and avoidanceapplication, a map with the positions and speedof all surrounding vehicles is created in eachvehicle, including those in nearby lanes. Whenthe driver indicates that he/she will change to adifferent lane by switching on the turning signal,the system can provide indication of when thelane change can take place based on the map,and can provide a warning if the driver starts toturn the steering wheel while the trailing vehiclein the target lane does not have a sufficient gap

from its preceding vehicle for the vehicle tomove into that lane. This application requiresvery accurate positioning to identify the lane inwhich each surrounding vehicle is traveling,which cannot be provided by GPS. The highpositioning accuracy of VLP makes smart auto-motive light an attractive solution for this appli-cation. VLC can also satisfy the communicationrequirements: a maximum required communica-tion range of 150 m, a latency lower than 100ms, and a payload size of 36 bytes [12].

COOPERATIVE ADAPTIVE CRUISE CONTROLAn adaptive cruise control (ACC) system auto-matically adjusts the speed of the vehicle accord-ing to the readings of an onboard ranging sensor,typically a radar or a laser imaging detection andranging system (lidar), which reports the distanceof the preceding vehicle. One of the most impor-tant design goals of ACC is to increase roadcapacity by shortening the gaps between vehicles,but without compromising road safety. However,it has been shown that the inaccuracy and pro-cessing delay introduced by the ranging sensorseverely limit the potential of ACC. Today, com-mercially available ACC systems are usuallyoffered as an optional package at a high price ofa few thousand U.S. dollars, which furtherdecreases the driver’s incentive to adopt such asystem. A cooperative adaptive cruise control(CACC) system, in addition to the onboard rang-ing sensor data, incorporates the more accurateself-information transmitted from the precedingvehicle (e.g., speed, acceleration, and brakingcapability) via a V2V communication link. Stud-ies show that such a system could overcome theaforementioned limitations and is capable ofoperating CACC with a time gap of 0.6 to 1.1 sbetween vehicles as opposed to 1.1 to 2.2 s forACC [13]. This translates to an 80 percentincrease in road capacity at 100 percent marketpenetration rate [1] compared to the saturatedroad capacity (2200 vehicles/lane/h) when notusing any automatic system. We believe that theproposed smart automotive lighting system isperfect for use in a CACC system. As a commu-nication system to carry the information from thepreceding vehicle, VLC has more than sufficientdata rate and delay performance for CACC. Inaddition, VLP offers the positioning capabilitythat can be used to determine the distance to thepreceding vehicle, eliminating the need to have aseparate high-cost ranging sensor.

SCALABILITYFor vehicle safety applications, the main concernis collision with nearby vehicles. Therefore, thedriver’s situational awareness should be confinedto a small potential collision area. Vehicles inthis area, to which we refer in this article as criti-cal neighbors, include the leading and followingvehicles in the same lane or vehicles in differentlanes in blind spot positions. For safety purpos-es, being aware of such neighbors can reduce thechance of accidents and increase road safety.

With the current DSRC technology, driverscan be aware of most vehicles within a 300 mrange despite an obstruction between thetransceivers. Hence, DSRC can possibly detect

Combining the com-munication and posi-tioning capabilities of

smart automotivelighting and integrat-

ing them into thevehicle safety system,

each vehicle canbuild a map which

has the relative posi-tions, as well as the

speed, the brake sta-tus, the heading,

etc., of all surround-ing vehicles that hasa direct path to it.



all critical neighbors and many additional non-critical neighbors. With VLC, on the other hand,we claim that while the number of neighborsthat can be detected is far fewer than that detect-ed by DSRC, most of them will be critical neigh-bors. In fact, the number of vehicles that can bedetected by VLC depends on the topology ofnearby vehicles, which can either emit or blocklight. In other words, VLC coverage scales withthe topology and only includes vehicles of whichthe drivers should be aware.

SIMULATION SETUPTo further illustrate how VLC differs fromDSRC, we conducted a simulation study of anurban scenario with a vehicle arrival rate of 1vehicle/s on a straight three-lane one-way road oflength 2.4 km. With fixed transmission power,the VLC range varies with the alignment angleand relative positions of the surrounding vehicles.In the simulation, each vehicle is assumed to beequipped with two 80 W headlamp transmittersand two 30 W taillight transmitters, both with ahalf-power angle of 20˚. The ranges of these twotypes of light sources are approximately 260 and160 m with 0˚ alignment angle, respectively.Each of the four receivers are assumed to beplaced at the same locations as the transmitters(i.e., at the two headlamps and two taillights),and an optional receiver is placed at each of thetwo side mirrors, as shown in Fig. 1.

To measure the usefulness of the networkconnectivity, we compare the number of neigh-bors that can be detected by different technolo-gies with the number of critical neighbors. Thealternative technology we considered is theDSRC technology with an omnidirectional RFrange of 200 m. Since VLC is directional, wealso compare our results with a bidirectionalDSRC transceiver whose maximum gain is in theforward and backward directions with 90˚ hori-zontal beamwidth. The bidirectional RF rangeconsidered is also 200 m. The simulation time isset to 2000 s. However, the considered roadtopologies are a series of vehicular traffic snap-shots at every 2 min interval starting from thetime instance of 300 s into the simulation.

COMPARISON STUDY OF VLC AND DSRCNumber of Neighbors — Figure 2a shows theprobability mass function (PMF) of the numberof neighbors that can be detected by differenttechnologies: VLC with four receivers, andomnidirectional and bidirectional DSRC.According to the results, it is clear that DSRC(RF) can communicate with a lot more neigh-bors than VLC. That is, on average, it can detectabout 32 vehicles in all directions with ommidi-rectional DSRC, while the number neighborsreduces slightly by 1–2 neighbors with bidirec-tional DSRC. On the other hand, the number ofneighbors that can be detected by VLC is muchfewer. More specifically, if we allow loose VLCneighbor detection (using only the less accuratepositioning provided by GPS), with at least onelink being established between any transmitter/receiver pair, each vehicle will have approxi-mately eight neighbors. However, in order to usethe accurate relative positioning provided byVLP, we need a stricter detection rule with at

least three VLC links established. In that case,the average number of neighbors is approxi-mately five, which is only slightly greater thanthe average number of critical neighbors.

Critical Neighbor Detection Rate — In termsof detection performance, we also measured thepercentage of critical neighbors that can bedetected by VLC. Figure 2b shows a comple-mentary cumulative distribution function(CCDF) at different detection rates with differ-ent technologies. By using four VLC receivers,at least 82 percent of the vehicles can detect allthe critical neighbors. This ratio increases to 99.8percent when we have an additional pair of

Figure 1. The locations of VLC transmitters and receivers in cars and scootersfor smart automotive lighting: a) car; b) scooter.

(a)

(b)

Interfaceto

onboardsafetysystem

Photodetector

Photodetector

(Optional)

(Optional)

Taillight

Taillight

Headlamp

Headlamp

VLCtransmitter

VLCreceiver

Interfaceto

onboardsafetysystem

VLCtransmitter

VLCreceiver



receivers at the two side mirrors. By analyzingour results in detail, we have discovered that themissing 0.2 percent are usually the neighbors indistant blind spots, which are at least two lanesaway from the considered vehicle (e.g., theneighbor is on the side but in the leftmost lanewhile the considered vehicle is in the rightmostlane. We claim that while these critical neigh-bors are of lower priority than the ones directlyon the side, which could potentially cause anaccident, we could possibly exploit the neigh-bors’ broadcast information of their local map toindirectly detect these neighbors. However, if weapplied a strict VLC detection scheme, only70–75 percent of the vehicles can detect all criti-cal neighbors. An in-depth analysis shows thatthese critical neighbors that cannot be detectedby the strict VLC scheme are mostly in blindspot areas, but they can typically be detected byusing the loose VLC detection scheme with sixreceivers.

As for DSRC, omnidirectional RF can detectall critical neighbors, while bidirectional RF failsto detect a much greater number of criticalneighbors because of the missing signal radiationin blind spot areas. Hence, the performance ofbidirectional DSRC is similar to that of theloose VLC scheme with four receivers.

Discussion — While it seems that DSRC out-performs VLC, we note here that the presentedresults do not take into account the inter-nodeinterference. With a much greater number ofneighbors, it is very likely that some of the com-munication will be in error if one uses DSRCtechnology (or RF in general) because all theneighbors are in the same collision domain, soall of them are potential interferers of oneanother. However, the interference when usingVLC is much less because not all the neighborscan interfere with one another due to the direc-tionality property of the technology, which cre-ates multiple collision domains. In addition, astraffic volume increases, the number of neigh-bors when using DSRC will grow with O(r2)when r is a transmission range, whereas the

number of neighbors when using VLC remainsroughly constant, O(1), because of the dynamicnature of the VLC range caused by the lightblocking effect. Hence, for safety purposes, VLCis a promising alternative to DSRC.

POSITIONINGVLP has become an active research topic in thepast few years. In indoor environments, strongsignal attenuation prevents GPS from providingaccurate location information, and VLP appearsas an attractive alternative because lights aregenerally installed throughout a building for illu-mination. In a typical VLP system, each LEDemits a modulated optical positioning signal,which can be used by the receiver to determinethe absolute location of the light (by the IDinformation embedded in the signal) and the dis-tance to the light. Combining the resultsobtained from multiple lights, the receiver canthen use geometrical calculation to accuratelyestimate its own position with an error of tens ofcentimeters.

A similar configuration can be used for vehi-cle relative positioning [8]. In such a system,each taillight or headlight emits a high frequencysinusoid, and the receiver can then measure thephase differences of the receiving sinusoids fromdifferent lights in the same vehicle. The differ-ence of the distances to different lights can becalculated with the phase difference. When twoor more sets of distance differences are available(i.e., more than three established VLC linksbetween the two vehicles are available), they canbe used to solve a set of equations to obtain theposition of the vehicle with respect to the trans-mitting vehicle on the 2D plane.3 Compared toranging sensors used in off-the-shelf vehicleproducts today, such as radar and lidar, VLP ismuch more cost effective, and its error perfor-mance of tens of centimeters is sufficient formost safety applications.

In this section, we present the results from aseries of numerical analyses to determine theerror performance of a VLP system, followed by

Figure 2. Comparison of the number of vehicles in the collision domain and the critical neighbor detection rates: a) PDF of the numberof neighbors detected by different technologies; b) detection rate achieved by different technologies.

Number of neighbors100

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RF omniRF bidirectionalCriticalVLC strictVLC loose

3 When this requirement isnot satisfied, but at leastone link is available, thesystem can always fallback to transmit its GPSlocation via VLC. This ismuch less accurate, withan error of up to 10 m.

TSAI_LAYOUT_Layout 12/3/13 1:49 PM 4


4 The typical recommend-ed safety distance betweenvehicles on a highway.

5 The angle at which theeffective transmissionpower is only half of themaximum power.

important design guidelines and system parame-ters that can be derived from the results. Resultspresented in this section assume no additionalattenuation caused by severe weather conditionssuch as rain, snow, and fog. For details on theVLC link budget model used for the analysis,please refer to the Appendix.

SIGNAL FREQUENCYWhen using the phase difference positioningscheme, thermal noise and shot noise add a ran-dom phase to the received sinusoid, which caus-es the positioning error. One way to mitigate theproblem is to increase the frequency of the sinu-soid. As the phase difference is inversely propor-tional to the frequency, the random phase causedby the noise has less influence on the positioningresult when using a higher signal frequency.

When the signal frequency increases to morethan 1 MHz, for most high brightness LEDs theeffective transmission power at that frequencystarts to degrade drastically. This is due to eitherthe phosphor relaxation time of a phosphores-cent LED or the parasitic capacitance due to thelarge die area of a high brightness LED; botheffects are present and, depending on individualdiode construction, one or the other would dom-inate to determine the actual response time. Theresponse time of a LED is typically on the orderof hundreds of nanoseconds. To improve theeffective transmission power at the operating sig-nal frequency, a resonant driving circuit needs tobe designed and placed behind the LED compo-nent [14]. However, as the frequency increases,it becomes more complex to design such a cir-cuit. Moreover, the processing performancerequired for high frequency signals also increasethe system cost significantly. As a result, it iscrucial to determine a frequency that can offersufficient positioning accuracy for vehicle safety.

Figure 3 shows the mean positioning errorswhen using different signal frequencies. The tar-get vehicle with its lights sending the VLP signalis assumed to be 40–50 m from the receivingvehicle,4 and is in the same lane, in the left orright lane with respect to the receiving vehicle.One can observe that a higher signal frequencycan indeed reduce the positioning error signifi-cantly. To achieve a positioning error of lessthan 1 m for all lights on a vehicle 50 m away (2percent error), the signal frequency needs to bemore than 20 MHz.

TRANSMISSION OPTICAL POWER ANDHALF-POWER ANGLE

Adopting high brightness LEDs (i.e., LEDs withhigh transmission power) increases the SNR andalso reduces the influence of the random phasecaused by the noise. Figure 4 compares the posi-tioning error performance of a headlight (i.e.,locating a following vehicle) and a taillight (i.e.,locating a preceding vehicle). The middle of thefront/rear bumper is assumed to be at the origin,with the two headlights/taillights located at (0,1)and (0,–1). With the headlight, VLP can gener-ate accurate positioning results with mean errorless than 20 cm for a vehicle up to 50 m away.On the other hand, with the taillight, the systemcan generate positioning results with the same

level of error for a vehicle up to 40 m away. Thebetter error performance for a following vehiclemake sense in terms of vehicle safety, as it ismore likely to be within the blind spots of thedriver than the preceding vehicle is.

Existing lights in vehicles are usually designedto have a very small divergence angle; the lightsare intended for vehicles directly in front orbehind. Figure 4c shows the positioning errorperformance when the half-power angle5 of theheadlamp is only 20˚, which is typical for auto-motive lighting. One can observe that a triangu-lar blind zone with very high positioning errorappears in the upper left corner, correspondingto a vehicle that is very close but slightly to theside. However, this could be problematic becausewhen the vehicles are closer to each other, ahigher positioning accuracy is required to pre-vent collisions. To avoid this problem, the lightsneed to have a larger divergence angle.

It is worth mentioning that other LED lightsin the vehicle, such as the turning signals andthird brake light, can also be used in VLP. Onthe other hand, as the transmission optical powerof these lights is much less than that of the head-lights and taillights, it can only be used to gener-ate accurate positioning results for vehicles thatare very close. However, this can sometimes stillbe useful. For example, the rear-facing turningsignals on the side rearview mirror (only avail-able in certain car models) can be used to locatevehicles on the side, which is not possible withheadlights and taillights.

PROTOTYPING EFFORTIn this section, we present the design and theresults from the prototyping effort to implementa VLC system using commercially availablescooter LED taillights and software definedradios (SDRs). Scooters are one of the mostimportant transportation means in Taiwan, andin several other Asian and European countries.

Figure 3. Mean positioning error when using different signal frequencies

Signal frequency (MHz)

Distance between vehicles: 40–50 (m)

2010

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Headlamp (half-power angle = 60°)Headlamp (half-power angle = 20°)Taillight (half-power angle = 20°)



In Taiwan, they account for approximately 70percent of registered mobile vehicles, includingcars, trucks, buses, and so on. In the past 10years, they have been responsible for more than75 percent of deaths in traffic accidents, result-ing in more than 2000 deaths annually. As aresult, it is crucial to quickly develop a cost-effective solution to improve their safety, andthe objective of this effort is to evaluate the fea-sibility of integrating VLC as part of a safety sys-tem in commercially available scooters, as wellas how they perform in real-world scenarios.

SYSTEM DESIGNFigure 5 shows the system block diagram of ourprototype. On the transmitting end, the electron-ic control unit (ECU) connector periodically col-lects information such as current speed, engine

revolution, brake status, and turning signal statusfrom the scooter, and sends it to a laptop. In thelaptop, digital packets with the information asthe payload and a footer with forward error cor-rection (FEC) code is created, and then modu-lated with 4-pulse position modulation (4-PPM).The packet goes through a digital-to-analog con-version in a SDR and is passed to the VLC front-end, which changes the light intensity of theLED taillight according to the input analog sig-nal. On the receiving end, the photodetectorconverts the received optical signal to an electricsignal, which goes through an analog-to-digitalconversion in SDR. The laptop then performsthe demodulation and decode processes toobtain the scooter information in the originalpacket. Finally, the information is sent to asmartphone mounted on the handlebar of thescooter. The smartphone presents a warning,and the information of a preceding scooter tothe driver when a collision with this scooter ispossible.6

The following presents a few key design con-siderations of the prototype, which can alsoserve as design guidelines for future commercialproducts.

•We choose to use SDR to implement thecommunication system of our prototype so thatwe have the flexibility to easily change variousphysical layer designs and networking protocols.To commercialize the system, these designs canbe transferred to a field programmable gatearray (FPGA) or an application-specific integrat-ed circuit (ASIC) to reduce costs.

•We only implemented a one-way link withthe taillight and a photodetector on the front ofthe scooter. A second link with an LED head-lamp and a photodetector on the back of thescooter can be added in a similar way so that thecommunication link between the two scootersbecomes bidirectional.

•Our choice of 4-PPM as the modulation for-mat is due to its high power efficiency [16] —with the same optical transmission power, themodulation can achieve the highest range withthe same bit error rate (BER).

•We do not use a lens in front of the pho-todetector, resulting in a wider 90˚ field-of-view (FOV) angle. A lens is usually used toincrease the received optical power, providinga higher link signal-to-noise ratio (SNR) andthus a more reliable link. However, in that caseit also decreases the FOV angle. Our measure-ment results of two different taillights indicatethat the beam angle is only about 20˚7 (see thepacket reception rate contour with respect tothe first successful reception location in theleft plot of Fig. 6); as a result, receiving vehi-cles on the side already have smaller receivedpower and less reliable links, and the FOVangle of the receiver cannot be furtherreduced. Instead, we choose to use a photode-tector with a larger receiving area (100 mm2)at the cost of a lower receiving bandwidth (2.4MHz). Since most safety applications do notneed a data rate of more than 1 Mb/s, thistrade-off does not limit our system perfor-mance. However, if a higher link data rate isdesirable, the taillights need to be designedwith a larger beam angle so that a lens can be

Figure 4. Mean positioning error when using headlamps and taillights. Thewhite dashed lines represent the lane markings: a) headlight transmitter (80W), half-power angle = 60˚, f = 40 MHz; b) taillight transmitter (30 W),half-power angle = 60˚, f = 40 MHz; c) headlamp transmitter (30 W), half-power angle = 20˚, f = 40 MHz.

X coordinate (m)

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6 This prototype is demon-strated in [15], and ademo video is available athttp://goo.gl/lo1f9.



used. Alternatively, infrared LEDs, togetherwith photodetectors covering both the infraredand visible l ight wavelengths, can be usedtogether with existing lights to boost the SNR.

•Ambient light in the environment couldinterfere with VLC transmission and decreasereceiving performance. To collect the opticalspectrum on roads, a photodetector wasmounted on the front bumper of a car torecord received optical signals while the carwas driven in a downtown area of Taipei, inboth day and night. The obtained data revealsthat the ambient light has most of its power invery low frequencies: 87.8 percent of the poweris below 1 kHz during the day, while 58.6 per-cent of the power is below 1 kHz during thenight. We also discovered that streetlights andilluminated signs are strong sources of inter-ference, but concentrated mostly at 120 Hzand its multiples. Our system uses a carrierfrequency at 100 kHz, and a high-pass or band-pass filter could remove most ambient inter-ference.

REAL-WORLD EVALUATIONTo evaluate performance of our prototype

in the real world, we carried out a series ofexperiments that emulate the scenario whereone scooter overtakes another scooter from adifferent lane. The experiments were carriedout on a sunny day with no rain or fog. Bothscooters operated at speeds between 10 and 40km/h. The overtaking scooter is equipped witha VLC taillight transmitter, and 20-byte pack-ets that contain information about the currentspeed, brake status, and so on were continu-ously broadcasted from the taillight at a datarate of 10 kb/s. The overtaken scooter isequipped with a VLC receiver and has thephotodetector mounted on the front. If theovertaken scooter can start receiving the pack-ets before the other is directly in front, thesafety system could either send a warning tothe driver or automatically lower the speed inadvance, decreasing the severity of a potentialcollision or even avoiding it.

Figure 6 presents the packet reception tracesof one of the experiments as well as the averagepacket reception rate combining all experiments.In the experiments, both scooters are moving,but the figures are plotted with the receiving(overtaken) scooter at the origin, showing therelative movements and locations of the overtak-ing scooter. The following observations can bemade from the experimental results, and thesepreliminary results are encouraging in that itshows evidences that:

•There is no observable difference betweenthe error performance of scooters operating atdifferent speeds. This is expected, as with oursystem parameters the Doppler shift is only0.037 Hz when the relative speed between thetwo scooters is 40 km/h, and 4-PPM is not sensi-tive to frequency shift.

•With an unmodified off-the-shelf scooterLED taillight,8 our results show that the frontscooter can reliably communicate with the backscooter when they are more than 10–15 m apart.Most scooters in the urban area do not travel atspeeds higher than 60 km/h or 16.67 m/s. This

implies that, when a sudden traffic event hap-pens directly in front, VLC allows the driver tohave as much as 0.9 s to react to the event afterreceiving the warning. When feasible, the datarate could be reduced to increase the range, or,equivalently, the maximum reaction time, to ahigher level. Note that most literature indicatesthat the time required for a person to react tothe warning takes about 1 s.

•Figure 6 shows that the packets started tobe received by the overtaken scooter more than1 s before the overtaking scooter moves into itsprojected path. This allows sufficient time forthe overtaken driver to react and avoid a poten-tial collision.

CONCLUSION AND FUTURE WORKIn this article, we propose the use of VLC forvehicle safety applications, creating a smartautomotive lighting system that combines thefunctions of illumination and signaling, com-munications, and positioning. The system pro-vides an all-in-one low-complexity and low-costsolution that could replace a DSRC onboardunit and ranging sensors, and we believe this isimportant in bootstrapping the adoption ofV2V communications in commercial products.Taking advantage of the propagation propertyof visible light, VLC can automatically limit itscommunication coverage to include only the

7 The local safety regula-tion for scooters specifiesthe minimum light inten-sity at 30 m only up to 20˚alignment angle as thetaillight is designed to beseen by vehicles directlybehind. Reflector shieldsare commonly usedbehind the LEDs to limitthe beam angle andincrease the light intensityat locations with smallalignment angles. Ourresults seem to match thespecification.

8 On a Yamaha Cygnus-X125 (model year 2011)scooter.

Figure 5. System block diagram of the scooter VLC prototype.

Band passfilter

4-PPMdemodulator

Photodetector -Thorlabs PDA100A

ECU connector

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Reed-Solomon

FEC encoder

Reed-Solomon

FEC decoder

3



vehicles that could potentially collide with itshost vehicle, and thus is more scalable in bothvehicle density and rapid topology change.Several useful design guidelines are alsoobtained from our studies:• The beam angle of the current automotive

lights are usually very small; a larger beamangle can provide better communicationsand positioning performance to vehicles onthe side, that is, in different lanes.

• Additional photodetectors on the siderearview mirror could significantly improvethe coverage to vehicles on the side.

Finally, our real-world evaluations of the pro-totype have provided evidence that the pro-posed system could indeed improve road safetyby providing advance warnings to driversbefore a potential accident might occur. Ournext step is to develop a lightweight mediumaccess control (MAC) protocol that allowsmultiple vehicles to transmit to the samereceiving vehicle with minimum interference,as well as feasibility studies for a few specificsafety applications.

APPENDIX: VLC LINKBUDGET MODEL

In an optical link, the channel gain is given as

(1)where m is the order derived from a Lambertianpattern, A is the physical area of the photodetec-tor, Dd is the distance between the transmitterand receiver, q is the angle of irradiance, and �is the angle of incidence. The Lambertian orderm is given by m = ln 2/ln (cos �1/2) where �1/2 isthe half-power angle. The equation only appliesif � < �C, where �C denotes the width of theFOV at a receiver; otherwise, H(0) = 0. In mostcases in our scenarios, q = �, and is referred asthe alignment angle in the article.

The received power Pr can be derived fromthe transmission optical power Pt as

Pr = H(0) * Pt (2)and the SNR can be obtained by

UV ^= +H m A

D(0) ( 1)

2cos ( )cos( )

dm

2

Figure 6. Packet reception in overtaking scenarios.

0.3

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(3)

where g is the detector responsivity, sshot2 is the

shot noise variance, and sthermal2 is the thermal

noise variance.Full details of the model can be found in

[17].

ACKNOWLEDGMENTThis work is supported in part by National Sci-ence Council, National Taiwan University, andIntel Corporation under grants NSC-101-2911-I-002-001, NSC-101-2221-E-002-169, NSC-102-2221-E-002-093-MY2, and NTU-102R7501.

REFERENCES[1] S. E. Shladover, “Keynote: How Vehicular Networking

Can Enable Automated Driving,” Proc. IEEE Vehic. Net.Conf. (VNC), California PATH Program, Institute ofTransportation Studies, UC Berkeley, 2011.

[2] Y. Morgan, “Notes on DSRC and WAVE Standards Suite: ItsArchitecture, Design, and Characteristics,” IEEE Commun.Surveys and Tutorials, vol. 12, no. 4, 2010, pp. 504–18.

[3] M. Schagrin, 2012, Connected Vehicle Safety Pilot Pro-gram, ITS Joint Program Office, Research and Innova-tive Technology Administration, U.S. Department ofTransportation; http://www.its.dot.gov/factsheets/safe-ty\_pilot\_factsheet.htm.

[4] M. Ergen, “Critical Penetration for Vehicular Networks,”IEEE Commun. Letters, vol. 14, no. 5, 2010, pp. 414–16.

[5] T. D. C. Little et al., “Directional Communication Systemfor Short-Range Vehicular Communications,” Proc. IEEEVehic. Net. Conf., 2010, pp. 231–38.

[6] C. B. Liu, B. Sadeghi, and E. W. Knightly, “EnablingVehicular Visible Light Communication (V2LC) Net-works,” Proc. ACM Int’l. Wksp. Vehic. Inter-Network-ing, 2011, pp. 41–50.

[7] A. Cailean et al., “Visible Light Communications: Appli-cation to Cooperation Between Vehicles and RoadInfrastructures,” Proc. IEEE Intelligent Vehicles Symp.,2012, pp. 1055–59.

[8] R. Roberts, P. Gopalakrishnan, and S. Rathi, “VisibleLight Positioning: Automotive Use Case,” Proc. IEEEVehic. Net. Conf., 2010, pp. 309–14.

[9] M. G. Wing, A. Eklund, and L. D. Kellogg, “Consumer-Grade Global Positioning System (GPS) Accuracy and Relia-bility,” J. Forestry, vol. 103, no. 4, June 2005, pp. 169–73.

[10] K. Cui et al., “Traffic Light to Vehicle Visible LightCommunication Channel Characterization,” AppliedOptics, vol. 51, no. 27, 2012, pp. 6594–05.

[11] K. Cui, G. Chen, and Z. Xu, “Final Report for TrafficLight to Automobile Visible Light Communication LinkStudy,” Center for Ubiquitous Communication by Light,UC Riverside, tech. rep., 2013.

[12] “Vehicle Safety Communications Project Task 3 FinalReport — Identify Intelligent Vehicle Safety ApplicationsEnabled by DSRC,” U.S. Nat’l. Highway Traffic SafetyAdmin., tech. rep., Mar. 2005.

[13] C. Nowakowski et al., “Cooperative Adaptive Cruise Con-trol: Testing Drivers’ Choices of Following Distances,” CAPATH research rep., UCB-ITS-PRR-2010-39, 2010.

[14] H. Le Minh et al., “High-Speed Visible Light Communica-tions Using Multiple-Resonant Equalization,” IEEE PhotonicsTech. Letters, vol. 20, no. 14, 2008, pp. 1243–45.

[15] S.-H. You et al., “Demo: Visible Light Communicationsfor Scooter Safety,” Proc. ACM Int’l. Conf. Mobile Sys-tems, Applications and Services, June 2013.

[16] R. J. Green et al., “Recent Developments in IndoorOptical Wireless Systems,” IET Commun., vol. 2, no. 1,pp. 3–10, Jan. 2008.

[17] T. Komine and M. Nakagawa, “Fundamental Analysisfor Visible-Light Communication System Using LEDLights,” IEEE Trans. Consumer Electronics, vol. 50, no.1, Feb. 2004, pp. 100–07.

BIOGRAPHIESSHUN-HSIANG YU is a graduate student in the Department ofComputer Science and Information Engineering at NationalTaiwan University (NTU). He received his Bachelor degree incomputer science and information engineering from NTU in2011. His main research focus has been VLC since joiningthe Mobile and Vehicular Network Laboratory at NTU forhis graduate study, which has implemented the prototypeof a scooter safety system based on VLC. The prototype wasdemonstrated at ACM MobiSys ‘13. He is currently anexchange student at the University of Houston, Texas.

OLIVER SHIH is currently a Ph.D. student in the Electrical andComputer Engineering Department at Carnegie Mellon Uni-versity. He received his Bachelor’s degree in computer sci-ence and information engineering from NTU in 2012.Before his Ph.D. study, he worked as a full-time researchassistant in the Mobile and Vehicular Network Laboratoryat NTU. His research interests include vehicular networking,vehicular safety systems, and VLC and positioning.

NAWAPORN WISITPONGPHAN is a lecturer in the Faculty ofInformation Technology and the Computer EducationDepartment at King Mongkut’s University of TechnologyNorth Bangkok, Thailand. She received her B.S., M.S., andPh.D. degrees in electrical and computer engineering fromCarnegie Mellon University in 2000, 2002, and 2008,respectively. From 2003 to 2009 she was also a researchassociate in the Electrical and Control Integration Laborato-ry, General Motors Corporation. Her research interestsinclude traffic modeling, chaos in the Internet, and cross-layer network protocol design for wireless networks.

HSIN-MU TSAI ([email protected]) is an assistant pro-fessor in Department of Computer Science and InformationEngineering and Graduate Institute of Networking andMultimedia at NTU. He received his B.S.E in computer sci-ence and information engineering from NTU in 2002, andhis M.S. and Ph.D. in electrical and computer engineeringfrom Carnegie Mellon University in 2006 and 2010, respec-tively. In 2013, he received the Intel Early Career FacultyAward and was the first to receive this honor in Asia. Healso received NTU’s Distinguished Teaching Award in 2013.His research interests include vehicular networking andcommunications, wireless channel and link measurements,vehicle safety systems, and VLC.

RICHARD D. ROBERTS has been with Intel Labs Oregon since2005 where he is a research scientist. He has a 40+-yearbackground in communications, both commercial and govern-ment. He has been leading Intel Lab’s optical wireless researchsince 2008, and is currently focusing on positioning via modu-lated IR beacons and camera-based photogrammetry.

LX X

=+

SNR Prshot thermal

2 2

2 2Taking advantage of

the propagationproperty of visible

light, VLC can auto-matically limit its

communication cov-erage to include only

the vehicles thatcould potentially col-

lide with its hostvehicle, and thus ismore scalable in

both vehicle densityand rapid topology

change.


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