traffic handling approach with intelligent speed control ... · traffic handling approach with...

Traffic Handling Approach with Intelligent Speed Control and

Prioritization of Emergency Vehicles using PCM Agent

T.Karthikeyan

Associate Professor

Department of Computer

Science

PSG College of Arts &

Science,Coimbatore, India [email protected]

N.Sudha Bhuvaneswari

Associate Professor

School of IT & Science

Dr.G.R.Damodaran

College of Science,

Coimbatore, India [email protected]

S.Sujatha

Associate Professor

School of IT & Science

Dr.G.R.Damodaran

College of Science,

Coimbatore, India [email protected]

Abstract The agent based architecture proposed in this paper is an

intelligent traffic monitoring agent that controls the speed

of the vehicles in a particular lane at a particular location

using sensors, mobile agents and RFID technology. The

proposed system also categorizes high priority and emergency vehicles to give priority over all the other

vehicles in a lane using mobile agent approach making

the architecture lightweight. By deploying this

architecture, vehicles can be controlled at desired

locations there by proportionately controlling traffic

density and congestion management taking into

consideration the movements of real time emergency

vehicles.

Keywords

SALSA, MATLB, PCM, RFID, Hall Effect Based

Sensors

1.Introduction

Improved technologies and sophistication has taken

the automotive industry to greater heights gradually

increasing the number of vehicles and vehicle owners

thronging the city roads making it a great challenge for

the city development council. Due to heavy usage of

vehicles with excessive or inappropriate speed,

unexpected road hindrances, leads to fatal accidents and

severe congestion. This situation cripples the movement

of emergency and high priority vehicles. The key idea behind this proposal is to manage

congestion effectively and also to prioritize the vehicles in

emergency situation using mobile agent based approach

using Prioritization and Congestion Management Agent

(PCM Agent).

PCM agents are autonomous agents that is capable of

keeping count of vehicles in a particular lane, tracking and

controlling vehicle speed, and managing movement of

emergency vehicles.

2. Concept of PCM Agent

Agent technology is gaining importance in almost all

the real time applications and scenario, because of its features that provide flexible and portable solutions with

user-friendly and environment friendly approach. Agent

technology provides dynamic services through its

property of mobility and adaptability [4].

The PCM agent works in co-ordination with MATLB

agent [5], Hall Effect based sensors, RFID tags, camera,

wireless module. The vehicles are continuously

monitored by cameras fixed at specific locations in the

highway and these images are taken by MATLB agent

and PCM agent. The MATLB agent uses the captured

image to count the movement of vehicles in a lane and the

PCM agent uses the captured image for vehicle

identification that helps in categorization and

prioritization in emergency situation. The PCM agent

takes into consideration the factors like number of lanes in

a ramp, image of the vehicle, alert sound produced by the

vehicle, status of beacon lights of the vehicle to identify emergency vehicles and to give priority to those vehicles.

3. Proposed Architecture with PCM Agent

The various hardware and software components that

make up this architecture are camera, SALSA

middleware, mobile agents MATLB and PCM, RFID tags

and Hall Effect based sensors. The camera is fixed on

polls of highways or on any other tall structures to

monitor the movement of vehicles in the environment [9].

The camera is used for capturing the images of vehicles

on the highway.

The support of SALSA middleware is mandatory that identifies vehicles and keeps a count of vehicles along

with their type in a particular lane by considering the

threshold value that is predetermined. The MATLB agent

is the agent that co-ordinates the activities of the sensors,

camera, SALSA middleware, filters, PCM agent, effectors

[5].

The PCM agent is responsible for controlling the

N Sudha Bhuvaneswari et al ,Int.J.Computer Technology & Applications,Vol 3 (4), 1545-1549

IJCTA | July-August 2012 Available [email protected]

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ISSN:2229-6093

mailto:[email protected]



speed of vehicles in case of congestion when the degree of

congestion increases and it is also responsible for

detecting emergency and high priority vehicles. It also

clears the lane for emergency vehicles by controlling the

traffic signals [6].

The Hall Effect Based Sensor located in the wheel of

a vehicle is used for controlling the speed of that

particular vehicle based on instruction received from the

PCM agent through RFID tags [10].

4. Structure and Functioning Of PCM Agent

in Traffic Handling Scenario

Camera

MATLB Agent

PCM Agent

Hall Effect Based

Sensor

RFID tag

SALSA Middleware

Congested Road with

Emergency Vehicle

Road Clearance for

Emergency Vehicle

Normal Road

Scenario

Image

Imag

e

Ro

ad

Sta

tus

Congestion

Status

Instru

ct s

peed

co

ntro

l

Speed Control, Road Clearance

SALSA computes

vehicle count and

compares with

threshold

Fig 1: Functioning of PCM Agent

The objective of the prescribed architecture with PCM Agent and MATLB agent is to automatically

control the speed of vehicles thereby avoiding

congestion and also to identify high priority and

emergency vehicles on the lane and giving priority to

those vehicles by clearing the lane. This proposed

architecture acts as an intelligent traffic monitor and

controller that provides a hassle free driving experience

considerable avoiding the problems of longer wait time

due to congestion, avoidance of accidents, improve the

fuel efficiency by limiting the speed of the automobile

proportionately improving mileage.

The proposed architecture is inevitable for the

investigation and up gradation of performance in road

traffic. This dynamic model initiates with the activation

of camera which is fixed on polls to overlook the traffic

scene and to capture the images of vehicles in a

particular lane. Images extracted from the camera and then analyzed by the MATLB Agent and the PCM Agent

simultaneously for further processing. The MATLB

Agent counts the number of vehicles in that particular

lane, compares with the threshold value[5] and sends the

road status(Normal or Congested) to the PCM Agent in

coordination with the SALSA middleware. If the status

of the road is normal, the PCM Agent along with Hall

Effect based sensors[1] and RFID tag, control the speed

of the vehicles at four areas: the active warning area, the

transition area, the activity area and the termination area

to avoid accidents and improves fuel efficiency,

considering road conditions, safety rules, climatic

conditions and city speed limit. Else, if the status of the

road is congested, the PCM Agent identifies the high

priority or emergency vehicles like Ambulance (through

their flashing red light,sound,image ) in that lane and

clears the lane for that vehicle without controlling the speed for those vehicles. The lane is cleared by PCM

Agent that controls the active traffic signal to identify the

vehicles as they pass by giving preference to emergency

vehicles and assisting in surveillance in a large scale. If

the road has two lane ramp, the PCM Agent instructs the

active signals to turn green in the lane in which the

emergency vehicles can move and hold the other lane

red ,clearing the path for the emergency vehicles. If the

road has single-lane ramp, the PCM Agent just instructs

the active signals to turn the red light to green and flush

out the vehicles to clear the way for high priority or

emergency vehicles[6]. This model along with MATLB

and PCM agent will results in reduced traffic accidents

and safer, more efficient roadways all over the country.



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5. Operation Mode of MATLB and PCM

Agents

Capture

vehicle images

Image to

MATLB Agent

Image to PCM

Agent

Compute

Traffic

Intensity(TI)

Is

TI>threshold

Intimation of

Road Status

Check Road

Status

Detection of High

Priority/

Emergency

Vehicles

Speed Control

based on Road

conditions

Is high

priority

vehicle

Activate RFID tag

by controlling

traffic signals to

clear the lane

Yes

Congested

Normal

Yes

Road status

No

No

Fig 2: Operation Mode of PCM and MATLB Agent

In the proposed model MATLB and PCM

Agent[5] works in co-ordination to control and

handle real time traffic effectively. The MATLB

agent is responsible for providing the status of the

road based on the count mechanism of vehicles done

by SALSA middleware, parallel the PCM Agent is

responsible for controlling the speed and handling

high priority and emergency vehicles by clearing the lane.

6. Experimental Study The performance of the system with MATLB

agent and MATLB agent in co-ordination with PCM

agent have been simulated on a particular day during

the peak hours from 8.00 AM to 10.00 AM covering

locations from Avinashi Road to Palladam in

Coimbatore linking areas like AR(Avinashi Road),

LM(Lakshmi Mills), PR(Puliakulam Road),

OP(Ondipudur), LT(L&T Bye Pass Road), SL (Sulur)

and PD(Palladam). The simulation has been carried

out using Qualnet network simulator tool and the

results show strong improvement in handling

congestion, high priority and emergency vehicles.

Table 1: Simulated Results of MATLB without PCM Agent

Date & Time Road Status Locati

on

Duration

(min)

Action

28/06/2012,

08:00:01 AM

Normal AR n/a

28/06/2012,

08:15:02 AM

Normal

(termination

area)

LM n/a

28/06/2012,

08:20:10 AM

Congested

(activity area)

PR Msg to

Control

Room

28/06/2012,

08:25:34

Normal PR 5 Traffic

Cleared

28/06/2012,

08:30:17 AM

Normal OP n/a

28/06/2012,

08:45:45 AM

Congested LT Msg to

Control

Room

28/06/2012,

08:52:19 AM

Normal LT 7 Traffic

Cleared

28/06/2012,

09:15:18 AM

Congested

(with

Emergency

Vehicle

SL Msg to

Control

Room

28/06/2012,

09:26:28 AM

Normal SL 11 Traffic

Cleared

28/06/2012,

09:49:54 AM

Normal PD n/a



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Table 2: Simulated Results of MATLB in co-

ordination with PCM Agent

Date &

Time

Road

Status

Locatio

n

Speed

Contro

l

(Y/N)

Dur

atio

n

(min

)

Action

28/06/20

12,

08:00:01

AM

Normal AR N n/a

28/06/20

12,

08:15:02

AM

Normal

(terminatio

n area)

LM Y Msg to HEBS

28/06/20

12,

08:20:10

AM

Normal

(activity

area)

PR Y Msg to HEBS

28/06/20

12,

08:30:17

AM

Congested OP Y Msg to HEBS

28/06/20

12,

08:32:19

AM

Normal OP N 2 Traffic cleared

28/06/20

12,

08:45:45

AM

Normal

(transition

area)

LT Y Msg to HEBS

28/06/20

12,

08:55:19

AM

Normal SL N n/a

28/06/20

12,

09:25:18

AM

Congested

(with

Emergency

Vehicle

PD Y(othe

r

vehicle

s),

N(eme

rgency

vehicle

Msg to HEBS &

RFID tag for lane

clearance

28/06/20

12,

09:27:28

AM

Congested PD Y Lane cleared for

emergency vehicle

28/06/20

12,

09:29:54

AM

Normal PD N 4 Traffic Cleared

0 0 0 0 0

2

0 0 0 0 0 0 0 0

4

00 0 0

5

0 0 0 0

7

0 0 0

11

0 0 00

1

2

3

4

5

8:00

:01

8:20

:10

8:30

:17

8:40

:45

8:52

:19

9:15

:18

9:26

:28

9:29

:54

T ime

Du

rati

on

of

Co

ng

es

tio

n

0

2

4

6

8

10

12

Duration of C onges tion with P C M(Min)

Duration of C onges tionwith MA TL B (Min)

Fig 3: Performance Evaluation of PCM with

MATLB

From the Analysis, it is found out that PCM

Agent in coordination with the MATLB provides

efficient congestion Management and instant

handling of High priority & emergency vehicles. In

case of congestion the PCM Agent consumes

minimum time duration for clearing the vehicle.[5]

7. Related Work

In this paper the MATLB agent that works in co-

ordination with the proposed Mobile Agent PCM is

an approach defined by us in the paper Mobile Agent

Approach for Traffic Load Balancing Using Sensors.

This MATLB agent can be combined to work

together with the PCM agent by providing appropriate road status information. Based on the

information provided by the MATLB agent the PCM

agent controls the speed of vehicles in case of

warning area, activity area, termination area and

interconnection area. The PCM agent also identifies

emergency or high priority vehicles and gives

clearance signal to these vehicles using RFID tags.

The MATLB agent along with SALSA

middleware counts the number of vehicles in each

type in a lane and compares it with a predetermined

threshold value.[3] If the threshold value is less than

the traffic intensity, then the traffic is considered

normal else congested. This agent hence capable of

determining the road status as normal or congested

and this status is provided to the PCM agent for

further processing [5].

According to Vikramaditya Dangi,Amol



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ISSN:2229-6093

Parab,KshitijPawar & S.S.Rathod, the paper Image

processing Based Intelligent Traffic Controller

applies Image processing Egde detection methods to

implement real time Emergency vehicle detection

without considering the speed control factor.[9]

8. Conclusion

This paper highlights on functioning of Agent

Technology along with sensors, SALSA middleware

and RFID Technology considering real time traffic issues in metropolitan cities. This paper proposed

architecture with Mobile agent PCM in coordination

with MATLB [5] for traffic control and handling high

priority or emergency vehicles effectively. The PCM

agent implemented in this architecture is based on the

combination of two technologies (i) Hall Effect

Based Sensors located in the wheels of the vehicles

for high accuracy speed measurement.(ii)RFID

tagging of traffic signals for controlling the active

signal and clearing the lane for high priority or

emergency vehicles. The experimental study

described in this paper has been carried out using

traffic signals, MATLB agent, PCM Agent, RFID

technology and Sensors. The simulation results

showed that the proposed architecture with PCM

Mobile agent handles unexpected traffic

circumstances successfully by reducing congestion

and time period of congestion clearance thereby providing an effective way for dynamic transportation

services.

9. References

[1]Assaf M.H (2011), RFID for Optimization of Public Transportation System, ISSNIP-2011-The Seventh

International Conferenceon Intelligent Sensors, Sensor

Networks and Information Processing, Adelaide, Australia, [2] Bo Chen, Harry H. Cheng, (2010), A Review of the Applications of Agent Technology in Traffic and

Transportation Systems, IEEE Transaction on Intelligent

Transportation System, Volume 11, No.2.

[3] Cucchiara, A. Prati, R. Vezzani (2005), Ambient Intelligence for Security in Public Parks: the LAICA

Project, Proceedings of IEEE International Symposium on

Imaging for Crime Detection and Prevention, London, UK,

pp. 139-144. [4] Dejan Milojicic (1999), Mobile Agent Applications,

IEEE Concurrency.

[5] T.Karthikeyan, S.Sujatha, N.Sudha

Bhuvaneswari(2012), Mobile Agent Based Approach for Traffic Load Balancing using Sensors, International Journal

of Computer Applications, Volume 47, Number 6.

[6] National Spotlight on Maricopa County Test Site for

High-Tech Traffic Management Prototype,Department of Transportation Maricopa ,2011.

[7]P.Pongpaibool,,P.Tangamchit & K.Noodwong (2007),

Evaluation of Road Traffic Congestion Using Fuzzy

Techniques,Proceedings of IEEE, TENCON ,Taiperi,

Taiwan. [8]N.Sudha Bhuvaneswari, S.Sujatha (2010), Vibrant

Ambient Intelligent System for traffic congestion control in

Coimbatore city(VAISTC4), Proceedings of the 12th

International Conference on Networking, VLSI and Signal Processing, Pg.No. 288-293.

[9] Vikramaditya Dangi, Amol Parab, Kshitij Pawar, S.S

Rathod(2012), Image Processing Based Intelligent Traffic

Controller, Academic Research Journal, Volume 1, Issue 1. [10] Wiroon Sriborrirux,Sorakrai Kraipui,Nakorn Indra-

Payoong (2009), B-VIS Servic –Oriented Middleware for

RFID Sensor Network,World Academy of

Science,Engineering and Technology.



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