Intelligent Traffic Control Based on IEEE 802.11DCF/PCF Mechanisms at Intersections

Chanwoo Park and Jungwoo LeeSchool of Electrical Engineering and Computer Sciences

Seoul National University, Seoul 151-744, KoreaEmail: cpark@wspl.snu.ac.kr and junglee@snu.ac.kr

Abstract—The research on driverless cars has been makingmuch progress lately. In this paper, we propose a new trafficcontrol system without traffic lights at an intersection. Weassume a system with fully autonomous driverless cars, andinfrastructure to avoid collision completely. When automobilesapproach an intersection, they communicates with the accesspoint in both random access mode and polling mode, and themovement of the automobiles will be coordinated by the infrastructure (access point). Traffic congestion is very difficult topredict and deal with because it is a function of many unknownfactors such as number of cars, weather, road constructions,accidents, etc. The proposed algorithm is designed for urban roadnetworks to ease the congestion, and make it more predictableat the same time. A key idea of this paper is that IEEE802.11 DCF/PCF mechanisms are used to control traffic flow fordriverless cars when there are no traffic lights at an intersection.The algorithm utilizes the concept of contention/contention-freeperiod of IEEE 802.11 to find a balance between efficiency oftraffic flow and fairness between users.

I. INTRODUCTION

In many cities, especially in large metropolises, trafficcongestion during rush-hours is one of major problems. Trafficcongestion is a very tricky problem to deal with not onlybecause it makes trip times longer and increase vehicularqueuing but also because there are too many variables on roadnetworks, such as number of cars at a certain time, weather ofthat day, unexpected road construction and car accidents etc.Because of this uncertainty of road networks, it is very difficultto predict and deal with the traffic congestion properly.

Driverless cars are vehicles with fully automated drivingcapabilities [1]. In many urban environments, a rapid increasein the number of cars has caused severe problems such astraffic congestion, air pollution and road safety. Researchershave been putting a lot of effort into developing new types oftransportation systems (e.g., driverless cars) as a solution tothis problem. Researchers first pondered the idea of driverlesscars in the 1960s. Since then, there have been many prototypesof driverless cars tested and lots of research and developmenton driverless cars going on. VisLab (Artificial Vision andIntelligent Systems Laboratory) has successfully completedthe rally of 13,000 km from Milan to Shanghai on driverlessvehicles in 2010. There has been active research on vehiclenetwork going on to develop interactive system enabling anumber of new services for road safety, mobility and effi-ciency such as Vehicle Infrastructure Integration (VII) [2] and

the California Partners for Advanced Transit and Highways(PATH) [3].

There are two basic assumptions in this paper. First, vehiclesare fully self-driven, which means each vehicle knows itsdestination and drives from one place to another without inputfrom a human operator. Secondly, we assume that the system isestablished to completely avoid collisions between cars. Thiscentral system manages the car network to make the roadenvironment collision-free.

Based on these assumptions, we propose an algorithm whichis used for traffic control when there is no traffic light atintersections. The basic principle of this algorithm is that thesystem gives priority to the lane which has the longer queue ofcars so that more congested lanes can be relieved more quickly.This will make travel times during rush-hour more predictable.There are two values we have to consider when it comes totraffic control without traffic lights, which are flow efficiencyand fairness between users. The proposed algorithm in thispaper uses IEEE 802.11 DCF/PCF Mechanisms to balancethese two values.

The rest of this paper is organized as follows: Sections II de-scribes the contention/contention-free mechanisms of 802.11legacy DCF/PCF and the system model. After analyzingsystem performance with/without traffic lights via simulationin Section III, the paper concludes with Section IV.

II. PROPOSED ALGORITHM FOR TRAFFICCONTROL

The system algorithm and the system model are introduced.

A. IEEE 802.11 legacy DCF/PCF

The IEEE 802.11 standard makes it mandatory for allstations to implement the Distributed Coordination Function(DCF), a form of Carrier Sense Multiple Access with CollisionAvoidance (CSMA/CA) [4]. CSMA is a contention-based pro-tocol which makes sure that all stations first sense the mediumbefore transmitting. The main goal is not to have stationstransmitting at the same time, which results in collisions andcorresponding retransmissions. Probabilistically speaking, theyhave the same opportunities when stations contending formedium access in DCF mode. Each station has its own randomback off timer when contending so they can achieve fairnessin the long-term.

978-1-4244-8327-3/11/$26.00 ©2011 IEEE

Fig. 1. IEEE 802.11 legacy DCF/PCF operation between beacon intervals

There is another optional access method, namely, the pointcoordination function (PCF) based on poll-and-response mech-anism. PCF is intended to transmit real-time information suchas VoIP, streaming video. In PCF mode, a point coordinatorwithin the Access Point (AP) controls which stations cantransmit during a certain given period of time, which is calledthe Contention Free Period (CFP). The point coordinatorwill take a look through all stations which are operating inPCF mode and poll them one at a time. Therefore, PCF isa contention-free protocol enabling stations to transmit dataframes continuously.

AP sends beacon frames at regular intervals so that theIEEE 802.11 protocol makes stations alternate between theuse of DCF and PCF in a single interval. With DCF, stationswill compete for the channel access by using CSMA. Forthe following CFP, the stations will wait for a poll fromthe point coordinator before sending data frames as shownin Fig. 1. Therefore, DCF is basically a protocol based onrandom contention so it aims for fairness while PCF is aprotocol controlled by the point coordinator trying to giveopportunities to stations which need to be served first. In thefollowing section, we discuss how we can apply this IEEE802.11 DCF/PCF mechanism to traffic control system.

B. System Model

There is a four-way intersection and each road has eightlanes. In the ith lane, cars are generated by Poisson distributionwith expected number (arrival rate) λi every time slot. Thissystem assumes that all cars are driverless and safely con-trolled by the car network system so that collision avoidancesystem is perfectly implemented. In each direction, the firstlane is dedicated for left-turns, the second and third lanes arefor cars going straight and the fourth lane is only for right-turns. This is described in Fig. 2.

1) Contention-Free Period (CFP): The system divideseach repeat interval into two parts, Contention Period andContention-Free Period just like IEEE 802.11 DCF/PCF. InContention-Free Period, we have total sixteen lanes as incom-ing channel to the intersection and each lane has its own fixedroute to pass through the intersection. Some of the routescan overlap each other so traffic control is needed on theoverlapping spot. Let Qi denote the number of cars queued upbefore entering the intersection in the ith lane (i = 1, · · · , 16)and Qi is updated at the very beginning of each time slot.When the ith route and the jth route intersect and there aretwo cars, one from ith lane and another one from the jthlane, going to the intersecting point, the system has to decide

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Fig. 2. Basic simulation model

which car it will let go first. The decision will be made basedon which one is larger between Qi and Qj . If there are n lanes(x1, · · · , xn) whose routes crossing each other, the system willgive priority to the xth lane, which satisfies,

x = arg maxi∈x1,...,xn

Qi

2) Contention Period (CP): If the system always givepriority to the most congested lane, the car on the road which isrelatively free of traffic will have to wait until its lane becomethe most congested. It is not fair to force the cars on the lesscongested lane to wait for too long just because the other laneis very busy. This motivates us to introduce contention period.In CP, if there are n cars coming to the overlapping spot atthe same time, the n cars will take turns to pass through theoverlapping spot no matter how many cars are queuing upin each lane. When you design a system you can make CFPlonger if your main goal is to ease the congestion, or you canmake CP longer if you aim for fairness. The proposed trafficcontrol system with/without traffic light are shown in Fig. 3and Fig. 4, respectively.

III. SIMULATION RESULTS

A. Proposed traffic system vs. Traditional traffic system

Now we compare the proposed traffic system with tradi-tional traffic system which are characterized by the existenceof traffic lights. We put different weight on each lane withdifferent Poisson expectation, i.e. λNorth = 1/2, λSouth = 1/4,λEast = 1/8, λWest = 1/16, so that each lane has differentlevel of congestion. We measure the travel time for a car topass through the intersection. One cycle (repeat interval) ofthe system consists 60 time slots with 30 time slots of CFPand 30 time slots of CP. The result is shown in Table I.

When the proposed system is used, the elapsed time of asingle car to pass through the intersection is reduced by 34.4 %on average, which means total traffic flow become smoother.Another notable result is that variance between travel timesof different users is significantly decreased by 90.5 %. Thisreduced variance means that the travel time become much

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Fig. 3. Traditional traffic system with traffic lights

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Fig. 4. Proposed traffic system without traffic lights

more predictable even though each road has different trafficdensity. Fig. 5 shows this result in Gaussian distribution. Wecan confirm that the travel time for each user become shorterand a lot more predictable by using the proposed traffic system.

B. Traffic density and the system performance

Now we analyze the relationship between the traffic densityand the system performance. We can expect by intuition thatthe proposed system will work more efficiently if there isless traffic on the road. For example, there are probably fewcars on the road during late nights or early dawns, whichmeans they need not wait before entering the intersection. Inthis simulation, we measure the travel time as a function oftraffic density. As you can see in Fig. 6, the travel time in theproposed system barely increase until traffic density reachesa certain number, 0.2 cars per time slot in this graph. Thatmeans road capacity in the proposed system is able to let cars

TABLE ITRAVEL TIME WITH/WITHOUT TRAFFIC LIGHT

Traditional system Proposed system(with traffic light) (without traffic light)

(unit: Variance Average Variance Averagetime slot) (x104) (x102) (x104) (x102)Left turn 36.85 11.23 0.78 4.05Straight 145.2 22.43 12.74 16.09

Right turn 36.44 11.20 4.53 9.30

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proposed systemwith traffic light

Fig. 5. Gaussian distribution model of travel time

pass through the intersection without stoppage until the trafficdensity reaches 0.2 cars per time slot. After the traffic densityof 0.2, the travel time in the proposed system starts to increasealmost linearly. After applying linear estimation we find theslope of estimated line, and it is shown in Table II. Even trafficdensity become higher than 0.2, the slope of the travel timewith respect to traffic density in the proposed system is stilllower than traditional system.

0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45100

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Tra

vel t

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Fig. 6. Relationship between traffic density and travel time

C. Efficiency vs. Fairness

The proposed algorithm is based on CFP/CP of the IEEE802.11 DCF/PCF mechanisms. The proportion of CFP and CP

TABLE IISLOPE OF TRAVEL TIME ACCORDING TO TRAFFIC DENSITY

With traffic light Proposed system noteLeft turn 21.7 16.8 22.6% reducedStraight 43.3 27.8 35.8% reduced

can be adapted according to the degree of traffic congestion.The longer CFP the system has, the more efficient the systembecomes so that it can ease the traffic congestion faster. Onthe other hand, the longer CP ensures fairness between users,which means the users on the less congested road do nothave to suffer for the sake of overall system efficiency. Inour simulation we set a repeat interval to be 60 time slotsand divide the repeat interval into CFP/CP. In Fig. 7, we plotthe variance of the travel time as we increase the proportionof CFP to CP. The graph shows that the higher proportion ofCFP in the repeat interval makes variance of the travel timesmaller, so the travel time becomes more predictable as weexpected.

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Fig. 7. Contention free period vs. variance of travel time

IV. CONCLUSION

With the advent of driverless car technologies, a newintelligent transport system can be developed to make trafficsystem more efficient and safe with the help of vehicle-to-vehicle and vehicle-to-infrastructure communications. As partof this intelligent system, we have introduced a new trafficsystem model specifically designed for urban road networks.The proposed system has no traffic lights at intersections, anduses IEEE 802.11 DCF/PCF mechanisms to control the trafficespecially during rush hours. Each cycle of traffic controlis divided into contention free period (CFP) and contentionperiod (CP). In CFP, the system will try to clear up the mostcongested lane while the system will address the fairness issuein CP. We can achieve a proper balance between efficiency ofthe system and user fairness by using the proposed algorithm.The proposed algorithm can easily accommodate emergencytraffic by giving the highest priority to emergency vehicle suchas police cars, fire trucks, and ambulances. Although we use

the IEEE 802.11 standard, any other wireless communicationprotocols employing the same medium access control (MAC)layer concept can be employed. It appears that the proposedtraffic control system is promising to alleviate traffic conges-tion in urban road systems.

ACKNOWLEDGMENT

This research was supported in part by Basic ScienceResearch Program (2010-0013397) and Mid-career ResearcherProgram (2010-0027155) through the NRF funded by theMEST, Seoul R&BD Program (JP091007, 0423-20090051),the INMAC, and BK21.

REFERENCES

[1] Rodrigo Benenson, Stephane Petti, “Towards urban driverless vehicles,”International Journal of Vehicle Autonomous Systems, pp.4-23, Volume6, Number 1-2 ,2008

[2] SE Shladover, Preparing the Way for Vehicle-Infrastructure Integration,California. Dept. of Transportation, 2005

[3] James A. Misener1, Steven E. Shladover “PATH investigations in vehicle-roadside cooperation and safety: a foundation for safety and vehicle-infrastructure integration Research,” IEEE ITSC, 2006

[4] IEEE Std. 802.11-1999, Part 11: Wireless LAN Medium Access Control(MAC) and Physical Layer (PHY) specifications, Reference numberISO/IEC 8802- 11:1999(E), IEEE Std. 802.11, 1999 edition, 1999.