Thesis Abstract

Thesis Overview

1.0     INTRODUCTION
This project is about integration of intelligent traffic control system, for the types of collisions, congestions and traffics rules. The examples and perceptive in this project deal primarily with World computerized traffic control system and some civilized countries. Traffic light, also known as traffic signal, stop light, traffic lamp, stop and go light, robots or semaphore, are signaling devices positioned at road inspections, pedestrian crossing, and other locations to control competing flows of traffic.

1.1     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.