EMERGENCY INFORMATION DISSEMINATION IN MOBILE

NETWORKS FOR VEHICLES

Ioan Chisalita and Nahid Shahmehri

Department of Computer Science, Linköping University, SE-581 83, Linköping, Sweden

Keywords: Safety vehicular communication, reactive protocol, safety information, vehicular networks.

Abstract: Due to the unacceptably high number of accidents with severe consequences, in-vehicle safety systems that

provide a better service to drivers are needed. One of the key technologies for supporting the development

of efficient safety systems is vehicular communication. In this paper we propose a reactive protocol for

disseminating emergency notifications to vehicles in traffic. The communication performance and the

protocol usefulness for help avoiding accidents are investigated via computer simulations. The results of the

evaluation indicate that timely and reliable communication can be provided by the proposed protocol.

1 INTRODUCTION

Every year, more than one million people die

worldwide on the roads (Evans, 2004). In addition,

the financial impact of traffic accidents is enormous:

for example, in 2003 the total of accident-related

losses reported in the U.S. was more than $230

billion (Biswas, Tatchikou & Dion, 2006). For

improving traffic safety, extensive investigations

into the causes of accidents and crash

countermeasures have been conducted over the

course of the last decade (Bishop, 2000). Many of

these studies have identified driver error as the

major cause of crashes (i.e. 90 %). Consequently, a

great deal of effort has been directed towards

helping drivers and reducing operator error. On-

board safety systems are considered to have a great

potential for reducing the number of accidents, e.g.

reductions with up to 70 % were predicted for

specific crashes (DOT, 2003).

Safety systems that make use of data wirelessly

exchanged between vehicles are able to efficiently

act towards avoiding collisions (Miller & Huang,

2002). These systems extend the perception of

vehicles in comparison to safety systems based only

on sensors such as radar. They are also capable to

cope with complex traffic situations. However, the

development of a communication system that

provides support to in-vehicle safety systems pose

difficulties due to the specifics of the environment in

which the exchange of data takes place. In the traffic

environment, the vehicles can constantly change

their position, heading and velocity. They also join

and exit the traffic in a relatively random manner,

and can rapidly pass through zones with very

different transmission patterns. In addition, the

development of traffic safety applications requires

communication systems that can assure low latency

and high reliability (Biswas, Tatchikou & Dion, 2006).

Considering the above aspects, the

dissemination of safety information was considered

to benefit from the use of direct communication

between vehicles that form an ad-hoc network

(Chisalita & Shahmehri, 2006). This type of

communication implies that no servers are involved

in controlling the exchange of data, and the network

is organized and maintained by vehicles alone. In

this paper we consider the above approach, and

propose a reactive protocol for effectively distribute

notifications about dangerous situations that occur in

traffic.

The rest of the paper is organized as follows.

Section II presents related work. Section III provides

an overview of the proposed protocol. Section IV

presents details on the reactive operation of this

protocol. Section V presents an evaluation of the

protocol. Finally, section VI summarizes the paper

and presents future directions.

2 RELATED WORK

Work in vehicular communication has been mostly

focused on three aspects: network management,

medium access, and communication protocols. The

284

Chisalita I. and Shahmehri N. (2006).

EMERGENCY INFORMATION DISSEMINATION IN MOBILE NETWORKS FOR VEHICLES.

In Proceedings of the International Conference on Wireless Information Networks and Systems, pages 284-289

 SciTePress

work presented in this paper relates to the last

aspect, and we survey below related contributions.

Various routing protocols have been proposed

for distributing data in mobile ad-hoc networks

(Royer & Toh, 1999). However, since these

protocols require the sender to know the identities of

the receivers, their applicability to safety vehicular

communication is limited (Biswas, Tatchikou & Dion,

2006). Also, the establishment of routes from sender

to destination(s), and their maintenance, is time and

bandwidth consuming. Consequently, most of the

protocols proposed for routing in ad-hoc networks

do not map well for safety vehicular communication.

Several specific protocols have been proposed

for dissemination of data between vehicles. These

protocols can be classified as reactive or proactive.

Reactive protocols employ the sending of

notifications to warn oncoming vehicles. Proactive

protocols provide traffic data in a regular manner. In

this case, the vehicles have a constant and up-to-date

view of the traffic. Using proactive protocols, safety

systems can have early information and are able to

predict well in advance the possibility for an

accident to occur. Consequently, they can efficiently

act towards eliminating it. In comparison, safety

systems supported by reactive protocols can only

limit the consequences of dangerous situations that

have already occurred. However, there are situations

in traffic that require the sending of notifications, or

in which the vehicles can benefit by having explicit

notifications about road hazards.

Several communication protocols for

distributing notifications to vehicles have been

previously proposed. Briesemeister (2001)

introduced a protocol for implementing a warning

system for traffic jams. This protocol employs a

method of estimating the size of the traffic jam for

controlling the distribution of messages. However,

this solution cannot be generalized for supporting

other traffic applications. Yang et al. (2004)

proposed a protocol for distributing warning

messages that use an analytic approach for adapting

the transmission rate. Nevertheless, this proposal

applies only for notifications about rear-end

accidents. A broadcast protocol that performs

relaying of notifications based on an estimation of

the transmission area covered by nearby vehicles

was proposed in (Sun at al., 2000). However,

Briesemeister (2001) demonstrated that the technique

can be unreliable.

We propose a protocol that is both proactive

and reactive. The proactive operation allows an

efficient organization of the vehicular network, and

delivers data used by in-vehicle safety systems to

identify hazards in traffic (Chisalita & Shahmehri,

2006). The reactive operation considers the specific

organization of the network when distributing

emergency data in traffic. We note that even when

using reactive protocols, the vehicles usually still

need to regularly exchange some identification data

in order to be able to organize the network. We have

extended the use of this data for realizing the

proactive component of the protocol. In previous

work we report on the network organization and the

proactive operation (Chisalita, 2006). In this paper

we focus on the reactive operation of the protocol.

Our work in the context of the DSRC standard

(ASTM, 2003) is discussed below. DSRC (Dedicated

Short Range Communication) was initially proposed

for vehicle-to-road communication and recently

extended for vehicle-to-vehicle communication. The

standard specifies the MAC layer, the link layer and

the radio layer for vehicular communication

systems. However, DSRC do not address multihop

communication and network organization. We

propose techniques for managing the vehicular

network, and for forwarding information. Our work

is complementary to DSRC. The protocol we

propose can also be implemented using DSRC

radios and channels, and can be used for augmenting

DSRC functionality when providing safety services.

3 SAFETY VEHICULAR

COMMUNICATION

OVERVIEW

In safety vehicular communication, traffic data

needs to be transferred in a timely manner between

vehicles that may not know about each other.

Reactive protocols should also aim to deliver

notifications to as many hosts as possible, which

may require data transmission in large areas.

However, the receiving hosts should be enabled with

filtering capabilities as they may not be interested in

all the received messages. Considering these

requirements, we controlled the delivery of safety

information by two methods.

First, we define a method for organizing the

vehicles. Vehicular network organization is essential

for obtaining scalable and reliable communication.

Therefore, we propose the grouping of vehicles in

manageable clusters that are defined based on the

current interest in traffic of the vehicles. Each

vehicle creates and maintains its virtual cluster,

which is defined as a local network (Chisalita,

2006). An example is presented in Figure 1. The

data needed for performing the network

organization is provided via the proactive operation

EMERGENCY INFORMATION DISSEMINATION IN MOBILE NETWORKS FOR VEHICLES

285

of a dedicated communication protocol (Chisalita &

Shahmehri, 2006). Thus, if data provided by a

vehicle is considered useful, the receiver registers

this vehicle in its local network. Further on, if the

information about the sender is not updated within a

time interval, the sender is removed from the local

network.

Figure 1: Example of local networks.

The determination of the level of interest is

performed using a set of traffic-related rules. The

criteria used for defining these rules were:

• Vehicle position. This data is needed by in-

vehicle safety systems for identifying dangerous

situations, e.g. (Sun et al., 2000).

• Service area extent. Research in traffic safety

has indicated that vehicles in proximity usually

have important data (e.g. vehicles situated

within 300-500 m), e.g. (Yang et al., 2004).

• Local network composition. Traffic analyses

have indicated that the number of vehicles that

can provide useful data is limited (e.g. 15-20)

(Asher & Galler, 1996).

• Parameters of the driving situation, e.g. relative

distance between vehicles, relative heading,

road status, vehicle status, road type. Accident

reports indicated that these parameters are

strongly related to crashes (DOT, 2003).

The size of a local network was denoted as Service

Area Threshold (SAT) and was initially set to 300 m.

The maximum number of hosts in a local network

was denoted as MNH, and was set to 20. The

suitability of these values (i.e. for SAT and MNH)

was then validated via simulations (Chisalita, 2006).

Further on, we propose an anonymous context-

based protocol for delivering safety data among

vehicles. This protocol is a scoped broadcast where

the identities of the destinations are not known by

default. Therefore, the vehicles are required to

analyze the received messages in order to determine

if they are the intended destination. The data used in

proactive operations is encapsulated in Basic Safety

Messages (BSMs) that are regularly sent at short

intervals. These messages contain data needed by

on-board safety systems for assessing hazards in

traffic. Examples are position, velocity, heading and

status of vehicles, and data about the road type and

status. Data included in BSMs is also used for

determining the level of interest for senders, and for

organizing the vehicular network. Filtering and

forwarding of BSMs are performed using a set of

traffic-related rules that make use of contextual

information (Chisalita & Shahmehri, 2006).

Data about hazards that occur in traffic is

encapsulated in Warning Messages (WAMs). These

messages are issued when an in-vehicle safety

system detects a hazard in traffic and considers that

other vehicles should be announced about it. The

safety system should also specify the transmission

and digest of WAMs, e.g. sending frequency and

time validity. In our work we have mostly focused

on supporting the efficient distribution of

notifications rather than providing specific

techniques for disseminating WAMs in particular

traffic situations. Thus, we propose a general

mechanism for issuing notifications that can be

further specified for diverse safety applications.

Warning messages can be disseminated in an area

specified by a local network, or in larger areas.

These messages are by default accepted by vehicles.

However, we also provide means for defining the

conditions that need to be fulfilled for warning

messages to be accepted.

4 WARNING MESSAGES

DISTRIBUTION

We introduce in the followings the techniques that

we have proposed for generating and forwarding

warning messages.

4.1 WAMs Generation and Content

Warning messages are generated when dangerous

events occur in traffic. A WAM is generated when a

safety system detects a hazard that can pose dangers

to other vehicles. The message can then be issued a

number of times in order to increase the probability

of being received by other vehicles. If the danger

persists, other WAMs can be generated.

As previously mentioned, a received warning

message is usually accepted by a vehicle. However,

the protocol can be configured so that the receivers

perform filtering of WAMs. For this, two options

were included within WAMs. The first addresses the

acceptance of notifications issued by hosts from the

same local network. Thus, it is possible to issue

WAMs that should be received only if the sender is

part of the receiver’s local network. For

implementing this option, we provided a field

default acceptance in WAMs. The second option

refers to the emergency degree of the traffic

situation that required the WAM to be sent. Thus,

Local Networks

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WAMs contain indications of the criticality of the

situation. We use this term to indicate how

dangerous a traffic situation is at a certain moment

in time. Two parameters are used to describe

dangerous traffic situations: criticality type and

criticality level. The criticality type provides a high-

level description of the situation. The criticality level

is a parameter that provides the possibility to set a

numeric value for indicating the level of emergency

associated with a dangerous situation. The criticality

level and type can be used for deciding if a WAM

should be accepted or not.

The WAMs structure is presented in Table 1.

Each warning message contains the sender identity

and the moment when the message was sent. These

two fields uniquely identify the transmitted message.

WAMs also contain the position of the dangerous

situation or event, and a short description of it. Other

types of information included in WAMs are the

criticality type and level, a retransmission counter,

and the default acceptance indication. Additional

information concerning dangerous situations can be

also provided using the reserved field Other data.

Table 1: Warning Message.

Message type Hazard position

Host identity Retransmission counter

Sending moment Hazard description

Criticality type Criticality level

Other data Default acceptance

4.2 WAMs Forwarding

As WAMs contain indications about dangerous

situations in traffic, they are subject to

retransmissions. Delivering a warning message to as

many hosts as possible in a short time was the

desideratum, and we took advantage of the

redundancy provided by a flooding-alike technique.

Thus, the retransmission of WAMs is controlled by

counters. Each WAM includes a retransmission

counter that indicates how many times it was

retransmitted. When a host retransmits a warning

message, the retransmission counter is decreased and

the new value is included in the (re)transmitted

message. A host that received and considered a

warning message, it retransmits it if the message was

not previously retransmitted and if the

retransmission counter is higher than zero. The

retransmission counter is set to a higher value if the

(original) issuer of a WAM decides that it is of

importance to disseminate the message in a larger

geographical area. We defined the retransmission

counter on the basis of the maximum number of

hosts (i.e. MNH) that can coexist in a local network.

Thus, the retransmission counter was specified as

β*MNH, with β = 1 for large area notifications, and

β = 0.5 for notifications within a local network.

A problem related to WAMs retransmission is

that the same message can be forwarded at the same

moment by a number of hosts close to each other.

This lead to a peak-load on the channel, which can

in turn reduce the communication quality. Even

more, it can lead to information loss. For alleviating

the consequences of this behavior, we enforce the

deferring of retransmitted WAMs. Thus, each host

waits a short time interval before retransmitting a

WAM. One possibility is to randomize this interval.

We implemented this approach by randomly

selecting a deferring interval between 0 and 0.1 s.

Another possibility is to calculate a deferring

interval that is inversely proportional to the distance

to sender. This approach allows distant vehicles to

relay messages faster, leading to a more rapid

propagation of data in an extended area. We

implemented this approach by specify the interval

for deferring the WAM retransmission as:

⎪

⎭

⎪

⎬

⎫

⎪

⎩

⎪

⎨

⎧

⎪

⎭

⎪

⎬

⎫

⎪

⎩

⎪

⎨

⎧

Tdr

SATkD

TTdefer

SAT

kTdr

Tdefer

max

max,**

In the above formula, D is the distance to sender,

SAT is the size of the communication service area, k

is a system parameter, Tmax is a maximum value for

the deferring interval, and Tdr is a regular value for

deferring the WAMs retransmission.

5 EVALUATION

An evaluation environment was developed by

integrating the proposed communication protocol

within a well-known network simulator, i.e.

GloMoSim. Traffic simulators have been developed

for generating movement patterns close to those of

real vehicles. For evaluating the performance of the

reactive component of the protocol, we used the

delivery delay for WAMs, and the WAM

dissemination success, i.e. the number of vehicles

that should receive a WAM reported to the number

of vehicles that received it. These metrics were

evaluated when WAMs were transmitted in the

presence of dissemination of BSMs.

The free parameters that we have used were:

- Load density, 6 - 20 [vehicles/km/lane].

- Vehicles mobility, maximum speed: 10 - 40 [m/s].

- Service area threshold (SAT), 50 - 600 [m].

Beside the communication performance, the system

usefulness for help avoiding accidents was

EMERGENCY INFORMATION DISSEMINATION IN MOBILE NETWORKS FOR VEHICLES

287

investigated. We examined if specific crashes can be

avoided by using a collaborative safety system based

on reactive vehicular communication. We first

simulated the accidents and the safety system

operations in order to derive requirements on

communication (e.g. latency) (Chisalita, 2006). We

then investigated if WAMs sent by specific vehicles

can fulfill these requirements.

When investigating the communication

performance, we used a general traffic scenario

modeling a two-lane bi-directional road. The

movement of the vehicles was specified using a car-

following model given in the literature (Chisalita,

2006). For investigating the system usefulness to

accident avoidance, we used realistic accidents

modeled using their descriptions given in crash

research (DOT, 2003).

The evaluation was performed for a BSMs

frequency of 10 BSMs/second. The tests were

performed using the standard radio layer of

GloMoSim (i.e. based on IEEE 802.11), and CSMA

as the MAC scheme. The propagation model was two-

ray and the nodes had a transmission range of 320 m.

For investigating the success of disseminating

WAMs, we define a zone of interest that contained

the vehicles that should receive specific WAMs. For

particular accident scenarios, this zone contained all

the vehicles in the simulation. For the general traffic

scenario, the zone was the extent of a local network

when WAMs were generated only within local

networks. When WAMs were generated in larger

areas, the zone contained vehicles in behind on the

same lane, and vehicles in front on the opposite lane,

situated at less than 500 meters from the vehicle that

issued the WAM (when the WAM was generated).

For evaluating the communication performance

we randomly selected hosts that generated WAMs.

The moments when these messages were issued

were also randomly selected. When not varied, the

SAT was 300 m, the maximum achievable velocity

was 25 m/s, and the network load was

6 veh/km/lane. The initial settings for the deferring

approach based on the distance to sender were

Tmax = 0.2 s, Tdr = 0.05 s, and k = 3.

We exemplify in Figure 2 the delay for WAMs

dissemination in a large area as a function of

network load. The graph shows the metric variations

for both deferring approaches, and present average

and maximum delay values. For low and high

network loads, the delay had larger values. For low

network loads, a small number of vehicles could

retransmit the issued WAMs. Consequently, more

retransmissions were needed for WAMs to reach

distant vehicles, which induced longer delays. For

high network loads, the contention for accessing the

medium was accentuated, and the vehicles waited a

longer time before being able to send WAMs.

Consequently, the delay increased. In these tests, the

random deferring technique assured smaller delays

that the technique based on the distance to sender.

The results of the evaluation indicated that

large area dissemination of WAMs (e.g. till 3.5 km)

with relatively low delays (e.g. 0.8 seconds) is

possible with the proposed protocol. We note that

delay values less than 1 second were considered

appropriate for delivering emergency notifications in

large areas (Briesemeister, 2001).

0.2

0.4

0.6

0.8

1.2

1.4

1.6

1.8

5 7 9 111315171921

Load Density [veh/km/lane]

Delay [s]

Average delay random

Ma xi m de l a y r a n d o m

Average delay distance

Maxim delay distance

Figure 2: Delay – load density.

The information dissemination success was 100 %

when the random deferring technique was used.

However, for the technique based on the distance to

sender the metric has decreased to 86 %, which

indicated that this approach was less reliable.

We also investigated the dissemination of

WAMs only within a local network. In this case we

employed the random approach for deferring the

WAMs retransmission. The results revealed patterns

similar to the previous tests, but with considerably

lower values for the delay. For instance, the highest

value of the maximum delay was 4 times lower for

WAMs dissemination within local networks. The

information dissemination success was again 100%.

As previously mentioned, we have also

investigated the usefulness of the proposed protocol

in avoiding collisions. These tests involved a

significant number of relevant traffic accidents

(Chisalita, 2006). We exemplify in here these

analyses with an intersection scenario that is

introduced in Figure 3. Two vehicles, V1 and V2,

are involved in a crash as follows. V2 is initially

stopped and then tries to pass the intersection. The

driver in V2 fails to notice the approaching vehicle

V1. When the driver in V1 realizes that V2 indeed

wants to pass the intersection, she/he tries to brake,

but is too late and V1 crashes into V2.

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Figure 3: Intersection accident scenario.

The accident avoidance can be achieved by

providing the driver in V1 with early information

about V2’s maneuver. Thus, we assumed that V2

sends a WAM when it starts to pass the intersection

because it comes from a non-priority road. We then

investigated if this WAM can be successfully

received in time by V1 and by other vehicles in the

simulation. The analysis indicated a delay of 0.64 ms

for V2’s WAM. This value was considerably lower

than the latency required for avoiding the initial

accident, i.e. 0.5 s. In addition, all the other vehicles

received the WAM with similar delays.

To summarize, the proposed protocol allows for

WAMs distribution with small delays in large areas

and very low latencies in small areas. The delay

values also fulfill the requirements of safety

applications, and are similar to, or lower than, results

obtained by pure reactive protocols (e.g. Yang et al.,

2004). The high values of the dissemination success

show that the emergency notifications were received

by the hosts in need. In addition, investigations of

accidents avoidance indicate the proposed solution

to effectively support in-vehicle safety systems.

In previous work we have obtained good

communication performance for the proactive

operation of the protocol (Chisalita & Shahmehri,

2006). In this work we also investigated the

communication performance when both the proactive

and the reactive modes were active. The results

indicated that the reactive operation did not pose

significant overload on the communication.

6 CONCLUDING REMARKS

This paper focuses on the distribution of emergency

notifications to vehicles in traffic. We propose a

technique for disseminating warning messages that

can fulfill requirements of safety applications.

Simulation results indicate that the communication

performs well in various conditions.

Future work includes investigations of

alternative techniques that can provide even lower

delivery latency while maintaining high

dissemination success. Further specification of the

content and digest of warning messages for

implementation of specific safety applications is also

of interest.

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