IRJET - Smart Traffic Control System using RFID

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 07 Issue: 03 | Mar 2020 www.irjet.net p-ISSN: 2395-0072
© 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 2416
SMART TRAFFIC CONTROL SYSTEM USING RFID
Dr Geetha S1, Sathish Kumar S2, Pradeep R3, Pradeep S4
1Assistant Professor, Department of Information Technology, Sri Manakula Vinayagar Engineering College,
Puducherry - 605107
2,3,4UG Students, Department of Information Technology, Sri Manakula Vinayagar Engineering College,
Puducherry - 605107
---------------------------------------------------------------------***----------------------------------------------------------------------
Abstract - Traffic problems include not just traffic jam
because of gain vehicle tightness, also include difficulty fo
emergency vehicles, red light traffic violation and accidents
causing blockage of roads and loss of lives. Previously
proposed systems for smart traffic management specialize
in vehicle density based traffic light control and provision
for emergency vehicle passage. These such systems are
limited to at least one or two focus areas. so as to create a
sensible city, a encompassing system for traffic management
has to be built that addresses all traffic related issues, not
just traffic jam . We propose a smart traffic control System
(STCS) using radio frequency Identification (RFID).
Key Words: Traffic congestion, Traffic density estimation,
Traffic management, Traffic Control, RFID, Radio
Frequency, Emergency.
1. INTRODUCTION
Traffic lights was in development since 1912, traffic lights
contains three colored lights. Nowadays, many countries
suffer from the traffic jam problems that affect the
transportation in cities and cause serious dilemma. The
rapid increase of the amount of automobiles and therefore
the constantly rising number of road users aren't
accompanied with promoted infrastructures with
sufficient resources. Various solutions was offered by
constructing new roads, flyovers and performing roads
rehabilitation.
However, the traffic problem is extremely complicated
thanks to the involvement of diverse parameters. First, the
traffic flow depends on the time of the day where the
traffic peak hours are generally within the morning and
within the afternoon The weekends have minimum load
while Mondays and Fridays have dense traffic and time of
the year as holidays and summer. Secondly, the present
traffic signal system is implemented with hard coded
delays where the lights transition time slots are fixed
regularly and don't depend upon real time traffic flow. The
third point cares with the state of 1 light at an intersection
that influences the flow of traffic at adjacent intersections.
Also, the traditional traffic system doesn't consider the
case of accidents, roadworks, and breakdown cars that
worsen traffic jam. additionally, an important issue is said
to the graceful motion through intersections of emergency
vehicles of upper priorities like ambulances, rescue
vehicles, fire brigade, police, and VIP persons that would
grind to a halt within the crowd. Pedestrians crossing the
road also tent to change the traffic flow.
RFID is a contact less wireless device consists of tag and
reader. The complexity of RFID systems differ from one
application to a different . RFID is extremely common in
access control applications where access control
information is typically stored in back-end database.
Traffic signals operate in Hard coded (pre-timed),
adaptive mode. Hard coded (Pre-timed) control consists of
a series of intervals that are fixed in duration. They repeat
a preset constant cycle. In comparison to Hard coded(pre-
timed) signals adaptive signals have the capability to
respond to the presence of vehicles or pedestrians at the
intersection. Vehicle actuated signals require actuation by
a vehicle on one or more approaches so as surely phases
or traffic movements to be serviced. They are equipped
with detectors and therefore the necessary control logic to
reply to the demands placed on them. Vehicle-actuated
control uses information on current demands and
operations obtained from detectors within the
intersection to change one or more aspects of the signal
timing on a cycle-by- cycle basis.
Regulation of the signals is controlled by traffic need.
Adaptive traffic control system is the latest period of
traffic control system. The adaptive traffic light systems
are operating with success in many countries since the
first 1970. Adaptive traffic light control systems are
normally complicated and include prediction and
estimation modules. More than twenty Adaptive traffic
light controls are available on the market. They are
significant thanks to their relative acceptance within the
field also because the relative extent of their world
implementation. Almost widely deployed control systems
are discussed here. In 1980, Nathan Gartner of University
of Massachusetts at Lowell proposed a system called as
Optimized Policies for Adaptive Control for the Federal
Highway Administration. The Split Cycle Offset
Optimization Technique (SCOOT) was also developed in
the early 1980 by the Transport Research Laboratory in
the United Kingdom. The Sydney Coordinated Adaptive
Traffic System (SCATS) is slightly newer, having been
created in the early 1990 by the Roads and Traffic
Authority of New South Wales, Australia. The RHODES
(Real- time Hierarchical Optimized Distributed Effective
System) is the newest of these four systems, is being
produced since mid-1990 at the University of Arizona at
Tucson.

A decentralized adaptive traffic signal control method
developed by Porche in 1997 known as Adaptive Limited
Look-ahead Optimization of Network Signals –
Decentralized (ALLONS-D). More recently, Yu and Recker
(2006) developed a stochastic adaptive traffic light control
model. An intersection traffic light control application
additionally to the amount of states is typically very large.
The dynamic programming algorithm to calculate the time
could make a significant problem.
At first Radio Freqency Identification tags were developed
to eventually substitute barcodes in supply chains. RFID
transponders (tags) contains Microchip, Antenna, Case
and Battery (for active tags only). We differentiate 3 types
of RFID tags in relation to power or energy i.e. Passive,
Semi-passive and Active. RFID tags fall under three
categories in reference to frequency.
Fig-1: Illustration working of RFID System.
As shown in figure 1, when a tag enters a read region, its
data is captured by the reader and then be transferred to a
host computer or programmable logic controller for
storage. The reader discharge Radio frequency signals to
activate the tag and to read and write data to it. The reader
emits radio waves in ranges of anywhere from 1 inch to
100 feet, based on its power output and the radio
frequency used. On passing the RFID tag through the
electromagnetic area, it identify the reader's activation
signal. The reader decodes the data in the tag's integrated
circuit and the data is passed to the host computer for
processing. The data sent by the tag provide information,
or specifics about the merchandise tagged, like price,
color, date of purchase, etc. RFID technology has been
employed by thousands of companies for a decade or
more. . RFID quickly gained attention due to its ability to
trace moving objects. Because the technology is refined,
more pervasive and invasive uses for RFID tags are within
the works. The simulated model used for the analysis of
efficiency of traffic signal controller. RFID reader has been
utilized in order to spot vehicles and hence we evaluate
the typical speed of the vehicles, queue length and waiting
time.
2. EXISTING SYSTEM
In general, our research cover the literature review from
various sources based on traffic control and vehicle
tracking. This method examine the adaptive fine tuning
algorithm to create a set of design parameters of two well-
defined mutually interacting modules of the traffic
responsive urban control(TUC)strategy for the large scale
urban road network of the city of China, Greece. Computer
simulation outcome are given, demonstrating that the
network performance in terms of the daily mean speed,
which is attained by the proposed adaptive optimization
methodology, is significantly better than the original TUC
System in the case in which the-aforementioned design
parameters are mutually fine-tuned to virtual perfection by
the system operation [1]. The system will develop the
traffic light configuration, which will be able to determine
three street case (empty street case, normal street case and
crowded street case) by using small associative memory.
The experiments presented provides promising results
when the proposed approach was applied by using a
program to monitor intersection in penesa island in
Malaysia. The program could determine the street cases
with different atmospheric conditions depending on the
stream of images, which are extracted from the street video
cameras[2]. To handle congestion in urban traffic flow
through next generation artificial intelligence techniques is
an important research area. Various intelligent and
approach have been developed using sot computing
techniques to tackle with this problem. This paper is an
attempt towards revisiting such approach in developing
modern traffic control systems[3].
This study focus on the utilization of RFID as a way of
traffic flow detection, which transmits collection
information connected to traffic flow straight to a control
system using an RS 232 interface, At the same time, the
sensor analyzes and Judges the information using an
extension algorithm designed to accomplish the subjective
of controlling the flow of traffic. In add-on, the traffic flow
condition is also transmitted to a remote monitoring
control system through ZigBee wireless network
communication technology. The traffic flow control system
developed in this study can execute remote transmission
and reduce traffic accidents. And it can also effectively
control traffic flow while reducing traffic delay time and
maintain the smooth flow of traffic [4]. The main subjective
of this system is that to control the traffic congestion,
allowing an ambulance to arrive at a particular location
without it having to stop anywhere until the designation is
reached. This system includes RFID technology and Lab
view software. The RFID reader reads the Identification
number from the related ambulance RFID tag and then it is
sends the data to micro controller LPC 1768H, which is
programmed, with the help of embedded C instructions.
Those microcontroller is capable of communicating with
input and output modules. The readers will provide the
data to the micro-controller so it compaers the received ID
with default ID‟s stored in its memory. If the readed ID gets
matched with any of the pre defined ID‟s, then a green
signal on the particular lane will be turned on untill the
ambulance crosses the traffic signal. The signal will not
change from green until the same tag is detected by the
other reader in another route [5]. On the traffic incident
management (TIM) makes a systematic effort to detect,
response to, and remove traffic accidents. It aims to offer
the rapid recovery of traffic safety and capacity and lead to

many measurable benefits, such as decrease in fuel
consumption, accident duration, secondary accidents, and
traffic jams. In the past thirty decades, ITS technologies
were recognized as valuable tools and being used word
wide in traffic accident detection, verification, response,
and communication [6].
On preemptive and predictive methodology, i.e., IT strategy
with reactive compensation (ITRC), to cut down network
delay time and eliminate unneeded stops for vehicles. With
anticipation for repetitive traffic flows based on historical
data, nominal traffic signals are tuned by IT controller over
repetitions. The reactive compensation, which is junction
based model predictive control strategy (JMPC), makes
adjustment on nominal traffic signals and compensates the
no repetitive elements. Exact analysis provide adequate
condition for guaranteeing the convergence of ITRC [7]. To
offer the idea of traffic light control using wireless sensor
network. It is a serious problem in the traffic congestion in
many major cities around the world and in this it has
become a nightmare for travelers. Conventional systems do
not control changeable flows coming near junctions. In
add-on, interconnection between adjacent traffic light
systems is not implemented in the current traffic system of
passage of vehicles, passage of emergency vehicles, and
passage of pedestrians. This leads to traffic jams and
hurried towards the crowd. Sometimes the high traffic
density on one side of the junction request more green
time than the standard allotted time. The system
architecture is isolated into three layers; the wireless
sensor network, the localised traffic flow model policy, and
the higher level coordination of the traffic lights agents [8].
The strength of the approach is its formal separation
between the low level image processing modules(used for
extracting visual data under various illumination
conditions) and the high level modules, which provides a
general purpose knowledge based framework for tracking
vehicles in the lane. The image-processing modules pull up
visual data from the scene by coordinate system analysis
during day time, and by morphologic analysis of headlamp
at night. The higher level module is planned as a forward
series of production regulation system, working on
symbolic data, i.e., vehicles and their attributes (area,
pattern, direction, and other) and exploiting a set of
heuristic concept tuned to urban traffic conditions [9].
A. K. Mittal and D. Bhandari proposed a system that could
provide clearance to any emergency vehicle by giving
green signals on the path of the emergency vehicle. In this
way, a vehicle passing through the lane will continue to
receive green signals. However, in this system, the wave
disturbances result in serious traffic problems due to lack
of synchronization [10]. P Maheshwari et al. proposed a
system in which cameras are installed at the red lights to
estimate the traffic. Based upon the need if density
increases, the vehicles in that lane were allowed to pass by
adjusting the timer for efficient traffic flow [11]. M. Kumaar
et al. used a obstruction gate and a GSM technology to
design a density based traffic light control system. In their
system the density of the traffic is used to alternate the
signal timing automatically and microcontroller is used to
provide the delay. However, this system fails to address the
problem of emergency vehicle [12]. Ghazal et al. Proposed
a PIC microcontroller based on traffic control system that
uses IR sensors to determine the traffic density. So the
dynamic time slots for different levels of traffic can be used
and also control device is used to track the emergency
vehicles. The disadvantage of this system is that the
portable device is to be carried along with the emergency
vehicle [13].
Vilarinho et al proposed a system which was based on
multi-agent system in which each isolated intersection
includes a multi-agent. These agents are configured for
intersections for creating, managing, and evolving its own
plans for traffic signal [14]. Younis and Moayeri proposed a
system in which a dynamic traffic light control (DTLC) is
located at the road junction to collect traffic data. It
includes few protocols to handle congestion and facilitate
efficient traffic flow by proposing low-overhead
algorithms. Though this system with efficiency manages
traffic rate of flow yet, it is not focusing towards the
emergency vehicles [15].
Table -1: Comparison with previously proposed systems.
3. PROPOSED SYSTEM
The solution we provide for Traffic management by
reading the RFID tag of each car by a RFID reader at traffic
junctions for real time traffic density calculation. It also
concentration on changing the traffic lights according to
vehicle tightness on the road, thereby intent at reducing
the traffic congestion on roads. In turn, it'll reduce fuel
consumption and waiting time. In case of emergency
vehicle like ambulance Radio Frequency module will be
used so that red traffic light signals will be turned to green
in order to provide a clear way for the emergency vehicles.
It will also provide significant data which can help in
future road planning and analysis. It is also used to detect
or track stolen vehicle. It also alerts the owner of the
Contributor
s
Dynamic
Traffic
Control
Emergenc
y vehicle
Tracking
of Stolen
Vehicle
Alert for
the
Topping up
the credit
for Tool
Booth.
A. K. Mittal
and
D.Bhandari.[
10]

P
Maheshwari
et al.[11]
 
M. Kumaar et
al.[12]

Ghazal et
al.[13]
 
Vilarinho et
al.[14]

younis et
al.[15]

Intelligent
Traffic
Control using
RFID
   

vehicle to top up the credit which is used in toll booth. In
further time period multiple traffic lights are often
synchronized with one another with an goal of even fewer
traffic jam and free flow of traffic. The vehicles are
detected by the system through RFID tag which is read by
the RFID reader. RFID reader is present in some meters
away from the signal and another RFID reader is placed
alongside the traffic light. It will capture the number of
vehicles in that particular lane. RFID is a better technique
to control the state change of the traffic light since RFID is
mandatory for all the vehicles in India. It shows that it can
decrease the traffic jam and avoids the nonce wasted by a
green light on an empty road. It is also more certain in
estimating vehicle existence.
Fig-2: Overview of the Proposed System.
3.1 Dynamic Traffic control using RFID reader
and tag
There are The STCS (Smart traffic control System) is
comprised of a group of two RFID readers, separated by a
long way , in each direction of a road crossing and have a
central computing system (CCS) to regulate all of them. As
a vehicle passes by a reader, it tracks the vehicle through
the RFID tag affiliated to the vehicle and fetch its
electronic product code (EPC) data. The EPC consists of
the vehicular identification number (VIN). The VIN is an
industry standard and every automobile features a unique
VIN. Through a table look-up procedure the VIN could also
be matched against individual vehicle records and every
one details like type, weight, length, registration, pollution
control status, and therefore the owner’s identification are
often retrieved. The data obtained is then sent
immediately to the CCS by wireless or wired channels, as
found convenient at that location. The CCS contains a
central database processing system (CDPS) for processing
vehicular data and a choice making section (DMS) for
controlling the traffic signals.
The volume of traffic is not calculated simply by the
number of vehicles but by a complex set of equations that
take into account predefined factors (obtained by
research) including:
• Vehicle type —whether it is a small vehicle like a scooter
or a car, or a large vehicle like a bus or a truck.
• Priority allotted to the vehicle — each type of vehicle is
allotted a particular priority based on its size, frequency of
that vehicle at the crossing, time of the day, and other
factors.
• Priority assigned to the path of travel—this factor
becomes essential when both the roads intersecting at the
crossing are not of the same importance (e.g., the
intersection of a national highway with an ordinary road).
• Time—the time of the day and day of the week. The
volume of traffic takes into account the priority assigned
to each vehicle at the present time of the day and also the
priority allotted to the two roads intersection at the
crossing.
Fig-3: A signal junction with RFID reader.
Fig-4: Block Diagram of the proposed system.
3.2 Emergency Vehicle Traffic clearance
Here, each emergency transport contains RF transmitter
component and the RF receiver will be enforced at the
traffic junction. The bell will be turned ON when the
vehicle is used for emergency purpose. This will send the
signal through the RF transmitter to the RF module
receiver. This will make the traffic signal to change to
green. Once the ambulance crosses the signal, the receiver
no longer receives the RF signal and the traffic light is
turned to red.

3.3 Identification of stolen vehicle
The Central Database will store all the Electronic Product
Code (EPC) of the vehicle which is read by the RFID reader
in the signal junction.It will store the In-time as well as the
Out-time of a particular vehicle in that junction. If a
vehicle is reported stolen the Traffic Department can
access the database and search the vehicle using Vehicle
Identification Pin which is in EPC. Here the information
about the particular vehicle is retrieved from the database
so it is helpful for identification of the stolen vehicle.
3.4 Alerting owner for topping up credit
As the Government of India has implemented the E-Toll in
all over the India as a result each vehicle will get a FasTag
which is the RFID Tag. It will be linked to the bank account
or to the wallet. Once the vehicle crosses the toll the
amount is reduced from the bank account. At the Junction
when a vehicle is reader by a RFID reader it will also check
for the credits. If the credit is less than the minimum
amount in the owner of the vehicle will get a message
notification once in 12 hours.
3.5 Red light violation detection.
If any of the vehicle violates the red light the fine will be
reduced from credit. While the signal is on red if any car
passes the red light It will be captured by the RFID reader.
The fine is placed automatically and the owner will get the
message through SMS.
4. EXPERIMENTAL RESULTS
The hardware implementation consist of arduino UNO
micro controller through which the RFID readers are
connected internally. The GSM module for sending the
SMS is also connected to the arduino. Both the arduino and
the GSM module is powered with 1 Ampere regulated
power supply each. A LCD panel was used to display the
current situation the junction. RF receiver is connected to
arduino to receive the signal passed from the transmitter
in the ambulance. RF transmitter is powered with 9v
battery. Four led lights is connected with arduino and used
for simulating the traffic signal.
Fig-5: Hardware Implementation.
Fig-6: Working of Dynamic Traffic Signal.
Fig-7: Working of Emergency Vehicle Clearance.
The results we obtained on the prototype is on showing
two or more than two tag under the RFID reader it take it
as a high density and allow the particular lane to have
green signal for some extra time. A tag which is already
denoted as the theft vehicle when the particular tag is

scanned in the RFID reader then it will make the beep on
and off for three time and will send the SMS to the control
room number and the vehicle owner number. When a tag
is scanned it will also check for the Fast Tag balance if it is
less then minimum balance the SMS alert will sent to the
vehicle owner. When the signal is in red a tag is passes
through another reader then it will be made as the rule
break. The fine will deducted removed from the Fast Tag
balance. Emergency vehicle has RF transmitter, on
pushing the button it will pass the signal to RF receiver
and make the particular lane green.
5. CONCLUSION
With automatic traffic light control supported the traffic
density within the route, the manual effort on a part of the
traffic policeman is saved. because the entire system is
automated, it requires very less human intervention. The
vehicle information is stored within the database so it's
easy to trace the stolen vehicle. Also SMS are going to be
sent in order that they will prepare to catch the stolen
vehicle at subsequent possible junctions. Emergency
vehicles like ambulance, fire trucks, got to reach their
destinations at the earliest. If they spend tons of your time
in traffic jams, precious lives of the many people could also
be at risk. With emergency vehicle clearance, the traffic
light turns to green as long because the emergency vehicle
is waiting within the traffic unction. The traffic signal
turns to red, only after the emergency vehicle passes
through traffic signal. also as if any vehicle violate the red
light is fined automatically. Further enhancements are
often done to the prototype by testing it with longer range
RFID readers.
REFERENCES
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EliasB.Kosmatopoulos and Markos Papageorgious,
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control.
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Wireless Sensor Networks”
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