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
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.
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
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
N Sudha Bhuvaneswari et al ,Int.J.Computer Technology & Applications,Vol 3 (4), 1545-1549
IJCTA | July-August 2012 Available [email protected]
1547
ISSN:2229-6093
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
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
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.
N Sudha Bhuvaneswari et al ,Int.J.Computer Technology & Applications,Vol 3 (4), 1545-1549
IJCTA | July-August 2012 Available [email protected]
1549
ISSN:2229-6093