Iaetsd literature review on traffic signal control system based on

LITERATURE REVIEW ON TRAFFIC SIGNAL CONTROL SYSTEM BASED ON
WIRELESS TECHNOLOGY
1
G.Krishnaiah 2
A.Rajani 3
P.Rajesh
M.Tech(DSCE), Student Assistant Professor Associate professor
Department of ECE Department of ECE
Annamacharya Institute of Technology and Sciences,Tirupati,India-517520
1
sreekrishna.g@gmail.com
2
rajanirevanth446@gmail.com
3
rajeshpatur.aits@gmail.com
Abstract – This paper presents a literature review on
different types of techniques used in the traffic signal
control system. We known to the fact one of the main
issues to be addressed by the today’s traffic
management schemes is, traffic congestion on city road
neetworks. Traffic congestion on city roads many times
leads to delay of our works. All these heavy traffic in
these day’s is due to the known fact that, number of
vehicles are increasing exponentially, and the limited
technology using for traffic control on roads. Traffic
police at cross roads and automatic traffic signal
scheme are the most used traffic control schemes in
India. Contrast to the regular schemes, intelligent
traffic management schemes based on Image processing
and Wireless sensor networks are using to control
traffic, from last five years. But besides their
advantagesthese schemes has some limitations. It is
found that using wireless system along with embedded
system has benefits over the existing techniques.
Key words: Automatic traffic signals, Intelligent traffic
management schemes, Image processing, Wireless
sensor networks, Wireless communication technology.
I. INTRODUCTION
The continuous increase in the congestion level,
especially at rush hours, on public roads , is a critical
problem in many countries and is becoming a major
concern to transportation specialists and decision
makers. The existing methods for traffic
management, surveillance and control are not
adequately efficient in terms of the performance,
cost, and the effort needed for maintenance and
support.
Many techniques has been used including,
ground level sensors like video image processing,
microwave radar, laser radar, passive infrared,
ultrasonic, and passive acoustic array. But, these
systems have a high equipment cost and their
accuracy is depends on environment conditions [1].
At another widely-used technique in conventional
traffic surveillance systems is based on intrusive and
non-intrusive sensors with inductive loop detectors,
in addition to video cameras for the efficient
management of public roads [2][3]. Among them,
intrusive sensors may cause disruption of traffic upon
installation and repair, and may result in a high
installation and maintenance cost. non-intrusive
sensors, On the other hand, tend to be large size,
power hungry, and affected by the road and weather
conditions; thus resulting in degraded efficiency in
controlling the traffic flow. Main problem occurs,
when this traffic congestion costs life of someone, if
in case any emergency vehicles like ambulance
strucks in traffic.
This paper gives a brief review of few techniques
that has been implemented in one or more than one
country around the world. In this paper traditional
traffic management schemes has been discussed,
below sub-section explains the traditional methods
used in traffic control system.
1.1 Traditional Traffic Control Scystem
We have different traditional traffic control
schemes, in our world, used around the world. A
traffic police standing at junction and later automatic
traffic control signals are among them.Each of which
are explained below.
A. Traffic Police standing at junction roads
A traffic police standing at junctions, or at cross
roads, is the simplest and the oldest method used for
the traffic management. It includes a human in the
traffic ssytem. A trffic officer is placed on each and
every cross sections of roads, and he manually
controls the traffic. A police officer stands at middle
of the road and monitoring the flow of traffic is
shown in fig.1. The police officer gives signals to the
vehicle driver whether to drive or start. And he
always monitors the every road, and decides which
lane has to give first priority. Based on his own
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knowledge on his own takes the decisions, that which
lane has to allow and which one to stop.
Fig.1. A Traffic poile officer standing in middle of
the road and controling the traffic.
This method is the most efficient among all other
ssytem, if traffic police officer monitors traffic
without error. As it includes a human as part of the
system, the efficiency depends on, that particular
officer. So, this might not be good for heavy traffic
conditions and all the day, as we know humans
always make mistakes.
B. Automatic Traffic signals
The drawback of the above system will be
removed with this automatic traffic signals system.
As like we seen every day, the automatic traffic
signal system includes simple 3 color traffic signals.
Normally 120 seconds of green light is onfor each
lane. A yellow light will be flashes, before the blue
light, for 20 seconds, sigling the vehicle owners to
strat their vehiles and be ready to go. When the green
light is on in one lane then all other lanes will display
a redlight, The automatic traffic signalling system is
shown in the fig.2. Where red signal indicates stop,
yellow light signal indicates ready to go, and green
light signal indicates go. The major problem with this
system is it cannot identify the amount of traffic in
one particular line, so there is a chance of traffic jam.
Fig.2. Automatic traffic signals
II. RELATED WORK
2.1 Existing Traffic control schemes
A. Controling traffic lights by Image Processing
Scheme
In this scheme the number of vehicles are
detected by the system through images rather using
electronic sensors. And along side the traffic lights,
cameras will be fixed, these cameras captures the
images of vehicles. It shows that it can avoid the time
being wasted by green light on an empty road, and so
decreases traffic congestion.
Image processing based on Intelligent traffic
controller, vikramaditya dangi, ss. Rathode and Amol
parab[4], a camera is fixed on tall poles to monitor
the traffic. Images are extracted from cameras will be
analysed to detect number of vehicles on the road, on
each lane, And depend on the signal cycle time is
allotted to each lane.
For this traffic control signaling system using
image processing requires matlab to perform the
opertaion on the images captured by the cameras
64

Fig.3. Block diagram of traffic control using image processing.
fixed on the tall poles. Image acquisition, edge
detection and Image enhancement are the major steps
in this scheme. The procedure of image processing
scheme is can be clearly understand with the fig.3.
Following 4 steps are the main blocks involved in the
process of traffic control:
1. Image acquisition
2. RGB to gray conversion
3. Image enhancement
4. Edge detection ( Image matching)
Image acquisition, primarily, is done with the
help of web camera. Initially image of the road is
captured when there is no traffic on the road, and that
empty road image is saved as reference image in the
specified program. On the reference image RGB to
gray conversion will be done.
Then the images of road, while traffic, is captured.
On the captured images, image acquisition is
performed and rgb to gray conversion as well.Then
after the edge detaction method the reference image
and original (traffic on road), are mtched. Based on
the percent of matching the time duration of the green
light will be allocated. Green light is on for 90
seconds, if the matching is between 0 to 10% . Green
light is on for 60 seconds, if the matching is between
10 to 50%. Green light is on for 30 second, if the
matching is between 50 to 70%. Green light is on for
20 seconds, if the matching is between 70 to 90%.
And Red light is on for 60 seconds, if matching is
between 90 to 100%.
B. Wireless Sensor Networks
Many studies suggested the use of WSN[5]
technology for traffic control [6, 7, 8, 9]. In [7], a
dynamic vehicle detection method and a signal
control algorithm to control the state of the signal
light in a road intersection using the WSN technology
was proposed. In [9], energyefficient protocols that
can be used to improve traffic safety using WSN
were proposed and used to implement an intelligent
traffic management system. In [10], Inter-vehicle
65

communication scheme between neighbouring
vehicles and in the absence of a central base station
(BS) was proposed.
In this paper, an intelligent and novel traffic light
control system based on WSN is presented. The
system has the potential to revolutionize traffic
surveillance and control technology because of its
low cost and potential for large scale deployment.
The proposed system consists of two parts: WSN and
a control box (e.g. base-station) running control
algorithms. The WSN, which consists of a group of
traffic sensor nodes (TSNs), is designed to provide
the traffic communication infrastructure and to
facilitate easy and large deployment of traffic
systems.
In this section, we present the system model
including some definitions and assumptions. We
assume a single intersection at urban areas with each
side having two legs. A configuration example for the
system is given in Fig. 4 for an urban intersection.
Vehicles arrive to the traffic light intersection (TLI)
according to certain random distribution and depart
after waiting for some time, which also follows a
certain random distribution. For simplicity, and
without loss of generality, we assume that each side
of the TLI is modeled as M/M/1 queue.
Fig. 4. Single intersection configuration example of
WSN
For urban areas with multiple intersections, we
assume a mesh network of intersections with
rectilinear topology. An open queuing network is
used to model the traffic flow between these multiple
intersections. In the mesh topology, the intersections
that are at the boundary are called edge intersections
while the remaining intersections are called receiving
and forwarding intersections. The average speeds for
all intersections are assumed to be constant. All
queues' lengths for all active directions are initialized
to zero. The distances (horizontal or vertical)
between any pair of the intersections are assumed
fixed and equal to a predefined base distance (d).
Fig.5. The in-house built traffic sensor node
The vehicle detection system requires four
components: a sensor to sense the signals generated
by vehicles, a processor to process the sensed data, a
communication unit to transfer the processed data to
the BS for further processing, and an energy source.
We adopt a simple time division multiple accesses
(TDMA) scheme at the MAC layer since it is more
power efficient as it allows the nodes in the network
to enter inactive states until their allocated time slots.
The scheme embodies a simple scheduling
algorithm that minimizes the time needed for
collecting data from all nodes back at the BS. The
algorithm assigns a group of non-conflicting nodes to
transmit in each time slot, in such a way that the data
packets generated at each node reaches the BS by the
end of the scheduling frame.
To streamline our presentation, we present some
useful notations and definitions that will be used
throughout the paper presented in the following
bulletins:
Traffic Phase: defined as the group of directions
that allow waiting vehicles to pass the intersection at
the same time without any conflict.
66

Traffic Phase Plan: defined as the sequence of
traffic phases in time.
The Traffic Cycle: defined as one complete series
of a traffic phase plan executed in a round robin
fashion.
The Traffic Cycle Duration (T): is the time of one
traffic cycle needed for the green and
red time durations for each traffic signal.
The design of WSN that is used as
communication infrastructure in the proposed traffic
light controller. We have designed, built, and
implemented a complete functional WSN and used it
to validate our proposed algorithms. Fig. 5 shows the
final product of the in-house developed TSN. The
functional TSN was built using some available of
the-shelf components (NB. commercial sensor nodes
like MICA motes were not available). The entire
TSN is encased in such a manner to be placed on
pavement made on the testing roads. For the system
components to be able to communicate (e.g., traffic
control box and the BS), a traffic WSN
communication and vehicle detection algorithms
were devised. To be specific, two algorithms are
developed, namely, the traffic system communication
algorithm (TSCA) that is presented in this section
and the traffic signals time manipulation algorithm
(TSTMA), which is presented in the next section.
These algorithms interact with each other and with
other system components for the successful operation
of the control system. The process starts from the
traffic WSN (which includes the TSNs and the traffic
BS), the TSCA, and the TSTMA, and ending by
applying the efficient time setting on the traffic
signals for traffic light durations. The TSCA is
developed to find and control the communication
routes between all.
The power restrictions of sensor nodes are raised
due to the their small physical size and lack of wires.
Since the absence of wires results in lack of a
constant power supply, not many power options exist.
Power limitations greatly affect security, since
encryption algorithms introdces a communication
over head between the nodes.
III. CONCLUSION
In this paper different existing traffic control
schemes(using Image Processing, using Wireless
Sensor Netwotks) are dicussed.
The new traffic control system based on wireless
communication have proposed . In the urban road
traffic control system generally includes signal
control machine, traffic lights, variable message
signs(VMS) and othe detectors. The wireless traffic
signal control system composed by master node and
slave node. The master node is the center of system,
it is a signal ccontrol machine and could provide
control signal to slave nodes; the slave node is the
end point devices of system, it recieves and executes
instructions from master node and then returns a
report. All of these devices communicated by
wireless communication models.
The performance of the proposed scheme for
traffic control sheme has benefits over the all other
existing schemes.
REFERENCES
1. The Vehicle Detector Clearinghouse, “A
summary of vehicle detection and
surveillance technologies used in intelligent
transportation systems,” Southwest
Technology Development Institute, 2000
2. Minnesota Department of Transportation,
“Portable non-intrusive traffic detection
system,”http://www3.dot.state.mn.us/guidest
ar/pdf/pnitds/techmemo-axlebased.pdf.
3. S. Coleri, S. Y. Cheung, and P. Varaiya,
“Sensor networks for monitoring traffic,” in
Proceedings of the 42nd Annual Allerton
Conference on Communication, Control,
and Computing, 2004, pp. 32-40.
4. Image Processing Based Intelligent Traffic
Controller by Vikramaditya Dangi, Amol
Parab, and S.S. Rathode. Undergraduate
Academic Research Journal, ISSN: 2278-
1129, Vol-1, Iss-1, 2012.
5. I. F. Akyildiz, W. Su, Y.
Sankarasubramaniam, and E. Cayirci, “A
survey on sensor networks,” IEEE
Communications Magazine, Vol. 40, 2002,
pp. 102-114.
6. A. N. Knaian, “A wireless sensor network
for smart roadbeds and intelligent
transportation systems,” Technical Report,
67

Electrical Science and Engineering,
Massachusetts Institute of Technology, June
2000.
7. W. J. Chen, L. F. Chen, Z. L. Chen, and S.
L. Tu, “A realtime dynamic traffic control
system based on wireless sensor network,”
in Proceedings of the 2005 Interna tional
Conference on Parallel Processing
Workshops, Vol. 14, 2005, pp. 258-264.
8. Y. Lai, Y. Zheng, and J. Cao, “Protocols for
traffic safety using wireless sensor
network,” Lecture Notes in Computer
Science, Vol. 4494, 2007, pp. 37-48.
9. J. S. Lee, “System and method for intelligent
traffic control using wireless sensor and
actuator networks,” Patent # 20080238720,
2008.
10. Z. Iqbal, “Self-organizing wireless sensor
networks for inter-vehicle communication,”
Master Thesis, Department of Computer and
Electrical Engineering, Halmstad
University, 2006.
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