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Inter--vehicle ad--hoc communication protocol for acquiring local traffic information.


Car navigation systems are going to equip GPS receivers and wireless LAN cards to acquire the information about traffic jams, road surface conditions and free parking lots along the street in real time. On the other hand, car drivers always want to access not only trunk road information but also back street road information. To solve these problems, we are doing research on disseminating and propagating road information using mobile inter--vehicle ad-hoc communication protocol. For example, suppose that a preceding car--A holds a set of its own speed, location direction and surrounding facilities information for the fast several minutes, and disseminates it to surrounding cars. Car--B, which is driving on the opposite lane, receives the information, moves to another place and re--disseminates car--A' information together with car--B' s information. At that time another car--C may receives the car A' s information. That means car C can know its preceding traffic conditions and road surface situations using inter--vehicle ad--hoc communication. (Ni at al., 1999.)


By diffusion of GPS systems and progress of car navigation systems, we will be able to use road information services interlocked with map information as follows:

a) Global road information services: the service that provides traffic jams and road-repairing information of trunk roads and highways through radio broadcasting and/or inquiring by cellular phones

b) Local road information services: the service which is used within a narrow region such as the service notifying an approaching vehicle at a crossing of other vehicles and walkers, back road traffic jam information service and free parking lots along the street service (Xu at al., 2004.)

When many vehicles moving to the same direction are stopping and/or moving at very low speeds, we can predict the traffic jam. If this information can be propagated by opposite lane's vehicles' relay and if it is reached to the tail of the traffic jam, drivers just before the jammed area can recognize the length of the queue of the traffic jam, and they may be able to avoid it by re-routing. Recent vehicle sensors help other situations. For example, freeze road surfaces can be detected by slide conditions of tires, and rainy conditions can be detected by movement of wipers. To propagate such information, other vehicles' drivers can prepare danger situations such as advancing slowing down. So combining global and local road information services, we are able to have much safer driving environments.

2.1. Ad--hoc communication protocol

At first, vehicles within the circles of 100 m's radius can communicate each other, however, data communication success probability decreases linearly according to the distance. When the distance between two nodes becomes large, the receiving radio power becomes weaker, so that reception error ratios will be increased. When a vehicle can communicate with vehicles within the range of 100 m, it can communicate with the vehicles that are running at a speed of 60 km/h on its opposite lane only for about 6 seconds. On the other hand, in case of both of lanes are jammed and vehicles are waiting 10 m intervals, the vehicle at the center may receive the road information from more than 40 vehicles simultaneously. Here, we assume that the bandwidth is 100 Kbytes/s and exchange data size is 10 kbytes at the maximum. We also assume that one second is divided into 10 slots, and each data transmission occupies one slot (Kellerer at al., 2001.).For this reason, when two vehicles send data at the same slot, we assume that any vehicle in the over lapped area of 100 m radius circles cannot receives the both of data because of collision.

2.2. Road information dissemination protocol

In this paper, we use SDRP (Speed Dependent Random Protocol) for road information dissemination. In SDRP, according to the vehicle speed v, random transmission interval is calculated between the minimum value min (v) and the maximum value max (v). In case of traffic jams, since there are many vehicles around a vehicle, the transmission interval becomes large. In addition, in case of high speed driving, the interval becomes small to increase propagation probability. For example, we can define SDRP random interval as follows:

* v is less than 30 km/h, min (v) is 3 seconds and max (v) is 5 seconds

* v is more than 30 km/h, min (v) is 1 second and max (v) is 2 seconds


3.1. The structure and the functions of the simulator

To evaluate road information propagation situations in an inter--vehicle mobile ad--hoc network setting, we have developed the network simulator. NETSTREAM II simulator is a traffic flow simulator for performing the effective prediction for traffic jams and prior evaluation of ITS introduction (Teramoto at al., 1998.) It defines traffic flow characteristics and the lengths of signal for all road links, and then calculates all vehicles' actions for every second. For each road, each vehicle calculates its speed V as V = [V.sub.max] (1-K / [K.sub.congestion]). Here let the distance between a front vehicle and itself be S and vehicle density K be K=1/S.

[V.sub.max] is the speed when the traffic density is 0, that means free running. [K.sub.congestion] is the vehicle density when vehicles are stopping because of traffic jams. Therefore, in wide areas, such as the whole city, it can calculate the traffic flows with considerably high accuracy. Based on those parameter values, this simulator produces inter--vehicle data propagation situation from the local information of all the vehicles and records varoius kinds of statisticsc information such as packet collision ratios and reception message amount. The simulator's processing flow is as follows:

a) Setting the given network environment

b) Defining car navigation equipped vehicles by the given equipping ratios

c) Calculating the following NETSTREAM II vehicle log data for every second

* Defining the vehicles to disseminate information by the given algorithm

* Searching the vehicles within attainment distance and determing received vehicles based on their reception probabilities

* Holding received vehicles data for next data transmission

d) Calculating data propagation situation

3.2. Simulation environment

Using our mobile Ad--hoc network simulator, we have evaluated the inter--vehicle road information propagation with the following input parameters: Road Environment: 20 km x 20 km, the number of signals is 198, Simulation Time: 60 minutes (the last 40 minutes data are used for evaluation), Location Information of Vehicles: Every second, The number of Vehicles: 8570 (The total number for 60 minutes), Equipping Ratios of Car Navigation Systems: 30 %, 60 %, 90 %, Network Environment: Attainment distance 100 m, Bandwidth 100 Kbytes/s, Dissemination Algorithm: SDRP (Speed Dependent Random Protocol) with two kinds of transmitting intervals, bordering on speed of 30 km/h, Receiving Probability : Linearly change based on the distance

3.3. Simulation result

At first we have measured the amount of transmitting data and network collision ratios for each equipping ratios and each SDRP protocol' s transmitting interval. (Nadeem at al., 2004.) In SDRP protocol, the transmitting interval for speed v is defined as [ min (v), max (v)]. Here, we assume that min(v)=max (v)/2, that is, [max (v)/2, max (v)] is used as the interval. Hereafter, we call max (v) the interval for the speed v as an abbreviation of [max (v)/2, max (v)]. Fig. 1 and Fig. 2 show the results of fixed transmitting intervals. When the transmitting interval of SDRP are set as <A,B>, it means that A is interval of less than 30 km/h and B is interval of more than 30 km/h. Fig. 1 and Fig. 2 show the results by changing the value of < A, B > from <1,1> to <16,16>. Fig. 3 and Fig. 4 show the results for the cases that B is set to 1 second, and the value of A is varied from 1 to 16. show the results by changing the value of < A, B > from <1,1> to <16,16>. Fig. 3 and Fig. 4 show the results for the cases that B is set to 1 second, and the value of A is varied from 1 to 16. When the equipping ratios are 90 %, the total transmitting data amount is the maximum when a is 4 seconds, and it decreases if the value of A is far from 4 seconds. Similarly, when equipping ratios are 60 %, it is the maximum when A is 2 seconds. The collision ratios at that time are 52 % and 48 % respectively, and the total transmitting data amounts are 64 Gbyites and 26 Gbytes, respectively.






When the equipping ratios are 90 %, the total transmitting data amount is the maximum when A is 4 seconds, and it decreases if the value of A is far from 4 seconds. Similarly, when equipping ratios are 60 %, it is the maximum when a is 2 seconds. In our setting, road information for each vehicle is 100 bytes so that about 4000 vehicles information can be acquired within a minute. We are sure that this data amount is enough to acquire local road information around several kilometers regions. As a future subject, we are studying more efficient protocol like RMDP, data aggregation technique, and more detailed analysis especially for each vehicle by defining actual exchanged information. We also anticipate the simualtion in the real world by implementing the protocol to car navigation systems.


Kelleler, W.; Bettstetter, C. & Sties, P.(2001.): Mobile Communication in a Heterogeneous and Converged World, IEEE Personal Communications, Vol. 8, No.6, pp. 41-47, 2001.

Nadeem, T., Dastinezhad, S., Liao, C.& Iftode, L (2004.).: A Scalable Traffic Monitoring System, Proc. of 2004 IEEE Int. Conf.Mobile Data Management (MDM2004) pp.13-26, ISBN 0-7695-2070-7, 24-08-2004.

Ni, S. Y., Tseng, Y.C., Chen, Y. S. & Sheu, J.P.(1999.): The Broadcast Storm Problem in a Mobile Ad-hoc Network, Proc. of 5th Annual ACM/IEEE Int. Conf. on Mobile Computing and Networking, pp. 151-162, 1999.

Teramoto, E. & al.(1998.): Prediction of Traffic Conditions for the Nagano Olympic Winter Games Using Traffic Simulator: NETSTREAM, Proceedings of 5th World Congress on Intelligent Transport Systems, Vol. 4, pp. 1801-1806, 1998.

Xu, B.; Ouksel, A. & Wolfson, O.(2004): Opportunistic Resource Exchange in Inter-vehicle Ad-hoc Networks, Proc. of 2004, IEEE Int. Conf. on Mobile Data Management pp.4-12, ISBN 0-7695-2070-7, 24-08-2004.
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Author:Cehajic, Arijana; Kovacevic, Drazen; Stimac, Igor
Publication:Annals of DAAAM & Proceedings
Date:Jan 1, 2008
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