Intelligent traffic light controller using embedded system

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 02 | Feb -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 2013
INTELLIGENT TRAFFIC LIGHT CONTROLLER USING EMBEDDED SYSTEM
Sayali Ambekar1, Shraddha Jawalkar2, Anagha Patil3, Shweta Patil4
1 Student, Dept. of Computer Engineering, Sinhgad College of Engineering, Maharashtra, India
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Abstract - Present Traffic Light Controllers (TLC) based on
microcontroller and microprocessor. These TLC have
limitations because it is functioning according totheprogram
that does not have the flexibility of modification on real time
basis. Due to the fixed time intervals of green, orange and red
signals the waiting time is more and car uses more fuel. To
make traffic light controlling more efficient, there is a new
technique called as “Intelligent traffic light controller”. This
new technique makes the use of Sensor Networks along with
embedded technology. The timings of Red, Greenlightsateach
crossing of road will be intelligently decidedbasedonthetotal
traffic on all adjacent roads. Thus, optimization of trafficlight
switching increases road capacity and traffic flow, and can
prevent traffic congestions.
Key Words: IR sensors, microcontroller, k-means
algorithms, MAX-232
1. INTRODUCTION
This system is developed using embedded system. It is used
for controlling the traffic signal that is why it is used with
roads, bikes and traffic. For this we are creating a hardware
kit and server. In this project we are using clustering
algorithm that is K-Mean algorithm. We can also maintain
the database using MySQL. With the help of IR sensors we
are going to take vehicle count as input to system. According
to vehicle count, we are decided the time ranges for all
signals. For implementing this system we are using
hardwares like 4 IR sensors, ADC, atmega8 microcontroller
etc. and softwares like NetBeans, java language, MySQL
database and glassfish server.
2. MANUSCRIPTS
2.1 Motivation
The motivations for using intelligent traffic light controllers
are to implement hardware which is suitable for real life
implementations. They include minimizing the delay or
waiting time on road, design of safe and efficient traffic flow,
assigning the right way and avoiding the overhead of traffic
police. The traffic jam will be reduced by increasing the
green signal time on heavy road and decrease the red signal
time in non-heavy road.
2.2 Organization of report
The report is divided into three chapters. Chapter 2
discusses about literature review that covers fundamentals
of topic, existing method, its meritsanddemerits,algorithms
and actual working of system. Chapter 3 discusses about
result, conclusion and future work.
2.3 Literature Survey
In “Dynamic Traffic Signal Timing Optimization Strategy
Incorporating Various Vehicle Fuel Consumption
Characteristics” paper proposes a dynamic traffic signal
timing optimization strategy (DTSTOS) based on various
vehicle fuel consumption and dynamic characteristics to
minimize the combined total energyconsumptionandtraffic
delay for vehicles passing through an intersection. The
proposed timing plan was compared with consistent results
were obtained [1].
In “SmartRoad:Smartphone-BasedCrowd SensingforTraffic
Regulator Detection and Identification” article they present
Smart Road, a crowd-sourced road sensing system that
detects and identifies traffic regulators, traffic lights, and
stop signs. The resulting traffic regulator informationcanbe
used for many assisted-driving or navigation systems but
limitation is the mobile crowdsensing paradigm is quickly
raising interests and funds [2].
In “Optimizing Traffic Signal Settings in Smart Cities”
proposes a bi-level optimization framework to settle the
optimal traffic signal setting problem. The upper-level
problem determines the traffic signal settings to minimize
the driver average travel time,whilethelower-level problem
aims for achieving the network equilibrium using the
settings calculated at the upper level. The Dynamic Traffic
Assignment (DTA) to decouple the complexbi-level problem
into tractable single-level problems which are solved
sequentially. The bi-level problem can be expressed as a
mathematical program converting the lower-level problem
as a set of additional constraints of the upper-level problem.
[3].

The “Real Time VehicleTrackingSystemBasedonARM7 GPS
and GSM Technology” paper has describedthedesignedand
development of the system in real time successfully. The
system provides positioning and navigational informationin
terms of number of parameters. Also if we want then
information regarding the satellites which are beingtracked
by the system is also displayed. The developed system is
compact, low cost and reliable. Since this systemcan beused
anywhere on the planet provided that signals from at least
four satellites are received. Furthermore, the
implementation is low-cost. [4].
The “Design and Implementation ofVehicleTrackingSystem
Using GPS/GSM/GPRS Technology and Smartphone
Application” paper has described the design and
implementation of our vehicletrackingsystem.Anin-vehicle
device, a server and a Smartphone application are used for
the vehicle tracking system. In this work, the in-vehicle
device is composed ofa microcontrollerandGPS/GSM/GPRS
module to acquire the vehicle's location information and
transmit it to a server through GSM/GPRS network. [5]
2.4 MeritsofIntelligenttrafficlightcontrollerusing
embedded system:
 Control the traffic.
 We can analyze the whole day traffic using log system.
 To reduce possibilities of accidents.
 To reduce waiting time.
 To reduce overhead of traffic police.
Demerits of Intelligent traffic lightcontrollerusing
embedded system:
 We have to choose proper position for sensors
otherwise it will count any object as vehicle.
 Cost effective.
 Ineffective during heavy rain.
2.5 Fundamentals
There are different fundamentals used in intelligent traffic
light controller using embedded system, they are:
1. IR-Sensor:
IR sensor uses the infrared light to sense object in front of
them & gauge their distance. Our hardware kit is consists of
4 IR sensors, atmega8, microcontroller, 4 traffic lights.IR
transmitter looks like an LED. This IR transmitter always
emits IR rays from it. The operating voltage of this IR
transmitter is 2 to 3v.These IR (infra-red) rays are invisible
to human eye. But we can view these IR rays through
camera. IR receiver receives IR rays that are transmitted by
IR transmitter. Normally IR receiver has high resistance in
order of mega ohms, when it is receiving IR rays the
Resistance is very low. The operating voltage of IR Receiver
is also 2 to 3V.
Fig -1: IR Sensor [6]
2. ADC:
ADC stands for Analog to digital convertor. In our system IR
sensor take vehicle count from real world which is in the
form of analog. From this we can say that ADC takes analog
data as input and it converts that analog data into digital
data without any data loss. ADC gives us digital output .And
this digital data is forward to system for algorithm
implementation.
Fig -2: ADC [6]
3. Microcontroller:
Here we are going to use atmega8 microcontroller. There
many microcontroller families like ARM, AVR, etc. This
atmega8 is belongs to AVR microcontroller family. Here
atmega8 takes the input from ADC which is in the form of
digital.
Fig -3: atmega8 [6]

4. System Database:
We are going to use MySQL database. Here the count of
vehicle and its timer this all things present in database as
log. So at the end of data if we want to check total vehicles or
traffic on street with the help of these logs we cancheck data
from database. And suppose we want to provide that data to
user using android app then with the help of this data user
can see the traffic of signal.
Fig -4: MySQL Database [6]
5. MAX-232:
The MAX-232 IC is an integrated circuit which consistsof 16
pins and it is a resourceful IC mostly used in thevoltagelevel
signal problems. Generally, the MAX-232 IC is used in the
RS232 communication system for the conversion of voltage
levels on TTL devices that are interfaced with the PC serial
port and the Microcontroller. This IC is used as a hardware
layer converter like to communicate two systems
simultaneously. The image of MAX232 is shown below.
Fig -5: MAX-232 [6]
2.6 Related Work
In this section we are going to see the actual working flow of
our project. Here any object like demo vehicles place
between IR sensor’s transmitter and receiver. These objects
are counting by using IR sensors. In this system, initially
sensors are work. Sensors take count of objects i.e. vehicle
count and send it to microcontroller. This count is in the
form of analog data. But microcontroller understandsdigital
data not the analog data. So there is need of converting
analog data into digital data. For this purpose ADC is used
into the system which is placed between IR sensors and
microcontroller. Here our microcontroller is atmega8 from
AVR microcontroller family.
The microcontroller takes digital data as input and passes it
to server i.e. PC. To connect both PC and microcontroller
together we require mediator for translation process and
this can be done by using MAX-232 IC as bridge between
them. The MAX232 is a dual transmitter / dual receiver that
typically are used to convert the signals. The MAX232 IC is
used to convert the TTL logic levels to RS232 logic levels
during serial communication of microcontrollerswithPC. So
the digital data is send to the server through MAX-232 IC.
Fig -6: Working of Intelligent System
On the server side, K-Mean algorithm is implemented for
calculate the timings to each traffic signals on road. After
calculating time, they are sending to traffic signal through
microcontroller using driver. The signal timings can be
optimized on server side only. After sending calculated time
to signals, it will glow LED lights on traffic signals according
to calculated timings. All the information like vehicle count,
traffic signal and related timings are stored into database
using MySQL. The system will performed actions by using
this entire process.
2.7 Algorithm of Intelligent Traffic LightController
Using Embedded System
K-Mean algorithm is clustering algorithm. Togetthecountof
vehicles from different area it is necessary to use cluster
algorithm. So we are using K-Mean algorithm here.

K-Mean Algorithm:-
Step 1:
Begin with a decision on the value of k = No of clusters.
Step 2:
Put any initial partition that classifies the data into k
clusters. You may assign the training samples randomly, or
systematically as the following:
1. Take the first k training sample as single-elementclusters.
2. Assign each of the remaining (N-k) training samplesto the
cluster with the nearest centroid. After each assignment, re
compute the centroid of the gaining cluster.
Step 3:
Take each sample in sequence andcomputeitsdistancefrom
the centroid of each of the clusters. If a sample is not
currently in the cluster with the closest centroid, switch this
sample to that cluster and update the centroid of the cluster
gaining the new sample and the cluster losing the sample.
Step 4:
Repeat step 3 until convergence is achieved, that is until a
pass through the training sample causes no new
assignments.
3. CONCLUSIONS
It is observed that the proposed Intelligent Traffic Light
Controller is more efficient than the conventional controller
in respect of less waiting time, an efficient operation in
emergency mode. Moreover, the system has simple
architecture, fast response time, user friendliness and scope
for further expansion.
ACKNOWLEDGEMENT
Every work is source which requires support from many
people and areas. It gives me proud privilegetocompletethe
seminar on “INTELLIGENT TRAFFIC LIGHT CONTROLLER
USING EMBEDDED SYSTEM” under valuable guidance and
encouragement of my guide Prof. D. P. Salapurkar. I am also
extremely grateful to our respected H.O.D. Prof. Dr. P. R.
Wankhede for providing all facilities and every help for
smooth progress of seminar. I would alsoliketothank all the
Staff Member of Computer Engineering Department for
timely help and inspiration for completionoftheseminar.At
last I would like to thank all the unseen authors of various
articles on the internet, helping me become aware of the
research currently ongoing in this fieldandall mycolleagues
for providing help and support in my work.
REFERENCES
[1] Junfeng Zhao,Wan Li, Junmin Wang, Xuegang Ban
“Dynamic Traffic Signal Timing Optimization Strategy
Incorporating Various Vehicle Fuel Consumption
Characteristics” June 2016, IEEE.
[2] SHAOHAN HU, LU SU, HENGCHANG LIU, HONGYAN
WANG and TAREK F. ABDELZAHER “SmartRoad:
Smartphone-Based Crowd Sensing for Traffic Regulator
Detection and Identification” ACM Transactions on
Sensor Networks, Vol. 11, No. 4, Article 55, Publication
date: July 2015.
[3] Zhiyi Li, Mohammad Shahidehpour, Shay Bahramirad,
Amin Khodaei “Optimizing Traffic Signal Settings in
Smart Cities” 2015 IEEE.
[4] Pradip V Mistary, R H Chile “Real Time Vehicle Tracking
System Based On ARM7GPS AndGSMTechnology”2015
IEEE.
[5] SeokJu Lee, Girma Tewolde, Jaerock Kwon “Design and
Implementation of Vehicle Tracking System Using
GPS/GSM/GPRS Technology and Smartphone
Application”, Electrical and Computer Engineering
Kettering University Flint, MI, USA, 2014 IEEE.
[6] Courtesy: Google images or information.
[7] P. Pyyknen*, J. Laitinen, J. Viitanen “Finland IoT for
Intelligent Traffic System” VTT Technical Research
Centre of Finland Tampere, Finland, 2013 IEEE.
[8] Muhammad Hassam Malhi, Muhammad Hassan Aslam,
Faisal Saeed, Owais Javed, Muhammad Fraz “Vision
Based Intelligent Traffic Management System”, 2011
IEEE.

Intelligent traffic light controller using embedded system

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