Design of an Intelligent Traffic Control System

Design of an Intelligent Traffic Control System

 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.

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 Intelligent Traffic System is at work.

Traffic congestion is an increasing problem in cities and sub urban spend more of their time commuting to work, school, shopping, and social event as well as dealing with traffic light jambs and accidents. Traffic became heavy in all directions, more to and from cities as well as between sub urban locations. Sub urban business locations required huge parking lots because employees have to drive; there were few buses trains, or trolleys to carry scatter workers to their work place. The hope of reduced congestion in the sub urban had not been realized; long commutes and traffic jams could be found everywhere.

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 aims of this research work are:

The first objective is to make each of the traffic lights or semaphores 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. In achieving these aims, the following objectives will also be followed:

SIGNIFICANCE OF THE STUDY

The important of this research work are:

The scope is the design of an intelligent 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.

limitation of the study

Traffic congestion is a serious problem despite costly effort to create an integrated method of traffic control system. The number of private automobiles used mainly by people with middle and income, has increased faster than any form of transportation in Lagos (Nigeria) and this has increased a demand of expansion of roads, parking space and improved computerized traffic control system.

methodology

The designed method employed for the intelligent traffic control system for this case study was the use of Split Cycle and Offset Optimization Technique. This technique used was use for the signal timing optimization and also to make a series of frequent adjustment for signal timing to minimize the modeled vehicle delays of the case study. The method is developed to meet the need of today`s traffic management. Visual basic was the developed program used for designing the intelligent control system of the case study and its design analysis as a functional designed method for the specification that identifies whether a new replacement system is required. This is done so as to ensure proper accuracy, efficiency and effectiveness which is the basic of a traffic control system

DEFINITION OF TERMS

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 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.