Design And Construction Of A Smart Traffic Light

ABSTRACT

For today’s transportation professionals, traffic management, safety and security initiatives are an increasing priority. State and local agencies are searching for solutions to improve mobility, efficiency and safety of their operations for the driving public. Current transport facility is suffering with many issues.  Accident risk management Traffic rule violation control Traffic signal management.

This project is on building an intelligent traffic control system, that automatically takes care of collisions, congestions and traffics rules.

Chapter one.

Introduction

1.1 Background to the study

1.2 Statement of the problem

1.3 Aim of the study

1.4 Objectives of the study

1.5 Significance of the study

1.6 scope of the study

1.7 definition of term

Chapter two.

Literature review

2.1 conceptual frame work

2.2 Empirical Review

2.3 Theoretical framework

Chapter 3

Materials and method

3.1 Materials

3.2 Method or design

3.2.1 block diagram

3.2.2 construction Method

3.2.3 testing Method

3.2.4 General circuit diagram

– Principle of operation of the circuit

3.2 5 Bill of Engineering component

Chapter 4

4.1 Design analysis

4.1.1 signal pickup unit

4.2 construction

4.3 packaging and casing

– complete device in casing sealed

– isometric Design of casing with the dimensions

4.4 Analysis of testing

4.5 Discussion

Chapter 5

Summary, conclusions and recommendations

5.1 summary

5.2 conclusion

5.3 recommendations

5.4 limitations of the study

5.5 suggestions for further studies

References

CHAPTER ONE

1.0                                                        INTRODUCTION

• Background to the study

The increase in urbanization and traffic congestion create an urgent need to operate our transportation systems with maximum efficiency. Real-time traffic signal control is an integral part of modern Urban Traffic Control Systems aimed at achieving optimal Utilization of the road network. Providing effective real time traffic signal control for a large complex traffic network is an extremely challenging distributed control problem. Signal system operation is further complicated by the recent trend that views traffic signal system as a small component of an integrated multimodal transportation System. Optimization of traffic signals and other control devices for the efficient movement of traffic on streets and highways constitutes a challenging part of the advanced traffic management system of intelligent transportation system.

Simply defined, Intelligent Transport Systems and Services is the integration of information and communications technology with transport infrastructure, vehicles and users. For a large-scale traffic management system, it may be difficult or impossible to tell whether the traffic network is flowing smoothly and assess its current state. Over the past few years, multi-agent systems have become a crucial technology for effectively exploiting the increasing availability of diverse, heterogeneous and distributed information sources. Researchers over the Years have adopted numerous techniques and used various tools to implement multi-agent systems for their problem domains. As researchers gain a better understanding of these autonomous multi-agent systems, more features are incorporated into them to enhance their performance and the enhanced systems can then be used for more complex application domains.
Intelligent software agent is an autonomous computer program, which interacts with and assists an end user in certain computer related tasks. In any agent, there is always a certain level of intelligence. The level of the Intelligence could vary from pre-determined roles and responsibilities to a learning entity. Multi-Agent System is the aggregate of agents, whose object is to decompose the large system to several small systems which communicate and coordinate with each other and can he extended easily. Agent-based simulations are models where multiple entities sense and stochastically respond to conditions in their local environments, mimicking complex large scale system behavior. The urban traffic system is a much complex system, which involved many entities and the relationship among them are Complicated.

Therefore, the most important issues for a learner agent is the assessment of the behavior and the intelligence level of the other agents. By sharing vital information, Intelligent Traffic System allows people to get more from transport networks, with greater safety and with less impact on the environment. Intelligent Traffic System helps the whole transport system to work most effectively and efficiently. Intelligent Traffic System integrates users, transport systems, and vehicles through state-of-the-art information and communications technologies. Intelligent Traffic System can dramatically improve travelers’ safety, efficiency and comfort. Intelligent Traffic System helps shippers and carriers move freight to its destination reliably and efficiently. Intelligent Traffic System helps the people who run transport systems provide better service to their customers. Intelligent Traffic System helps get the best value from the road and rail systems we already have. Intelligent Traffic System helps traffic flow more smoothly, reducing delays, fuel consumption, and air and noise pollution. Intelligent Traffic System helps make public transport more convenient and affordable. Intelligent Traffic System often works behind the scenes. When emergency vehicles get to a crash site more rapidly than before, Intelligent Traffic System is detecting the crash, notifying emergency services, and getting the nearest response unit rapidly to the site. Technology in a vehicle prevents skidding and helps the vehicle to stop safely; the driver may not even realize that assistance was provided, but smart Traffic System is at work.

• Statement of the problem

Traffic congestion has become a major problem nowadays. Traffic congestion especially occurs in metropolitan cities. Increased air pollution, noise pollution, accidents, delay in travel time etc are some of the problems that are faced by people living in these mega cities. Traffic jams have severely impacted the lives of citizens. The traditional traffic lights deployed in cities are not sufficient to meet the demands of an over-growing city since these traffic lights have specific pre-determined time intervals for changing from red phase to green phase. In this regard several attempts were made to automate the traffic lights based on the density of vehicles on the road. Some authors suggested the use of sensors to determine vehicle count while several others suggested the use of video cameras to capture moving vehicles and perform preprocessing on the videos to obtain vehicle count. This paper summarizes a review on the various methods that were used for the development of an intelligent traffic management system. A detailed comparison of all the methods is provided in this paper along with the pros and cons of every method.

• Aim of the study

Intelligent Traffic System provides travel opportunities and additional travel choices for more people in more ways, wherever they live, work and play, regardless of age or disability. The main aim of this work is to make each of the traffic lights smart. That is, aware of the time of day, basic turn red, green or yellow rules, and perhaps what traffic looks like in all directions based upon locally mounted signals.

• Objectives of the study

In achieving these aims, the following objectives will also be followed:

• To design a simple system that is easily adaptable to the existing traffic conditions at the junction, involving a minimum of physical changes in the intersection.
• To provide the quickest possible clearance to vehicular and pedestrian traffic in all directions at a junction.
• To a design flexible artificial intelligence traffic light system that will take care of changes in the traffic density and character.
• To reduce the stress of the traffic warder.
• To reduce the occurrence of possible accident.
• To verify the efficacy of the program.
  • Significance of the study

The important of this research work are:

• It will help in reducing the occurrence of possible collision or accident and thereby improve the confidence of the driver and the pedestrian plighting through the highways.
• The project to allay the fear of time wastage at the junctions because of unevenly directions of traffic system.
• Since the system is capable of working for 24hours uninterrupted thereby assured constant availability of traffic control service hence reduce human effort and energy.
  • scope of the study

The scope is the design of an smart traffic control system. The modern method of traffic control system is indicating each light at a particular time interval to pass a vehicle at one lane and stop vehicle on the other lane. The light is broken into three (3) categories (Red, Yellow,  and Green) to signal to lane on what to do at a particular time where the red signify STOP, yellow signify READY, and green signify MOVE. Each light is designed to turn itself on whenever it is necessary and turn off the time elapse.

This smart Traffic light signalling system was designed using IR Sensors. In this system, we are working with IR sensors to know about the traffic density at traffic signals. For this purpose we will arrange IR sensors at each road in Traffic junction. These IR sensors will find out the density of the traffic density at that road. These sensors are Interfaced to Microcontroller. With the detection of traffic density from IR sensors microcontroller will control the traffic signals accordingly on basis of density of traffic.

1.7 definition of term

Traffic Light: A road signal for directing vehicular traffic by means of colour lights, typically red for stop, green for go, and yellow for proceed with caution.

Intelligent/smart Traffic System: refers to information and communication technology  that improve transport outcomes such as transport safety, transport productivity, travel reliability, informed travel choices, social equity, environmental performance and network operation resilience.