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A Sustainable Mechanism for Gathering Road Traffic

Data using Smart-phones Samitha Udalagamll, Lumini Sahabandu*2, Lasantha Samarkoon#3, Dinuni Fernando#4, Pankajan Chanthirasegaran#5,

Sahan Udanl6, Dilini Asangl7, Chandima Fernando#8, Chamath Keppetiyagaml9, Chaminda Ranasinghe#IO

University a/Colombo School a/Computing, Sri Lanka

'samdamn.u@gmail.com, 21uminisahabandu@gmail.com, 31asn1987@gmail.com

Efficient and effective surveillance and control of road

traffic has been generally accepted as a cost effective solution

to the ever growing problem of traffic congestion, According

to reports, in most developed countries, this information is

generally gleaned using vast arrays of sensors such as

pneumatic road tubes, piezoelectric sensors, magnetic loops

and video cameras which are very costly [1], One of the most

promising cost effective alternatives to in-situ traffic sensors is to use what is known as 'Floating Car Data' (FCD) [I] to

gather information about the traffic flow, There has been

much research carried out to prove the effectiveness of using

FCD to obtain traffic flow information, Mobile Century is a

field experiment that was carried out in February 2008 with

the intention of demonstrating the use of GPS on cellular

phones to elicit traffic data, Nericell [2] was conducted to

introduce mobile phone based traffic monitoring mechanism

and well known Waze, a community driven smart-phone

application allows users to report traffic jams, accidents, speed

traps, police presence and update roads, In this paper, our goal is to propose a socially and economically viable mechanism

based on the FCD principle, through which the state of traffic

congestion can be detected using inbuilt capabilities of

modern smart-phones,

The system in question that is used for gathering traffic data

consists of two components; the smart-phone application

(client) and the server side application, When the smart phone

application is running, it collects accelerometer and GPS data

in the background (invisible but not unknown to the user), If

the acceleration/deceleration patterns experienced by the device (which indicates the acceleration patterns experienced

by the vehicle the device is in) and the speed with which the

vehicle is moving (derived from the GPS system) are

indicative of a traffic jam, a message is transmitted to a central

server, indicating the devices, location and direction of travel,

On the server side, the messages received from multiple such

applications are clustered and points with traffic congestion

are determined, These traffic alerts are broadcast back to the

smart-phone applications where the points are marked on a

map, based on the location or planned route of the user,

While the technical feasibility of such an implementation has proven to be sound, it does not imply that the system would

work in a real life situation, This is due to the system's heavy

dependence on its users to generate traffic updates, In other

words, the system is unable to provide an acceptable level of

service (in terms of frequent and relevant traffic updates)

unless there is a large enough community of users, Conversely,

it is a challenge to build up a large enough community of

users if the application is unable to provide an acceptable level

of service, because the perceived value of the application is

low, With a significant community in place, a revenue model

can be implemented by the service facilitator to transform the system into a profitable venture, At this stage, we suggest that

the system will have achieved sustainability,

We suggest a model that can be used to obtain a reasonable

estimation of this critical mass that is required, Based on the

assumptions of uniform traffic distribution within a

metropolitan area, we suggest that the number of nodes (Mo)

(vehicles with the application) needed to provide traffic alerts

at a given level of service (p) is given by;

Mo=2pNUjRT

where N is the number of nodes required to accurately verify a

single traffic jam, U is the number of congestion prone road

sections, R is the rate of traversal of those road units by

vehicles and T is the sampling period,

In this work, we present a conceptual model that can be used

to make a reasonable assessment of the size of the community

that is needed in order to achieve the said sustainability, We have devised a simple formula based on our concept of 'jam­

units', to calculate the number of active applications that

would be needed within a given metropolitan area to achieve a

given level of service, Furthermore, we provide an analysis on

how various system parameters can be adjusted to control the

required size of the community, We have presented how 1)

the number of individual nodes that are needed to mutually

confirm a single traffic congestion point and 2) the time span

for which a traffic update is maintained as 'fresh' can be

tweaked to achieve a desired balance between the availability

and the accuracy of traffic updates, We then propose an

extension to the formula proposed earlier, to estimate the number of active application users that would be needed to

ensure that the required number of users are using the

application on the roads at a given time,

REFERENCES

[1] Guillame Leduc, "Road Traffic Data: Collection

Methods and Applications," 2008,

[2] Prashanth Mohan, Venkata N Padmanabhan, and

Ramachandran Ramjee, "Nericell: Rich Monitoring of Road and Traffic Conditions," Microsoft Research,

India, Bangalore, 2008,

The International Conference on Advances in ICT for Emerging Regions - ICTer2012 13th - 14th December 2012