Autonomous agent oriented traffic control system

Emerging trends in software development has been changed due to the huge amount of data, growth of internet, mobile, dynamic and smart applications. Most of such applications consist of small, intelligent, flexible and distributed components known as agents. Number of agent methodologies has been presented but few of these are evaluated and verified. Due to the invention of agent technology, the way to analyze, design and build the systems has been changed. Agents take input from the multiple sources and have real time response. Vehicle traffic management especially in large cities is rapidly becoming one of the major challenges due to heavy growth in population and vehicles. Our research proposed a solution for traffic control and management system using intelligent/ autonomous agents technology. These agents have the ability to observe, act and learn from their experience. Our system uses the knowledge of flow of previous signal to predict the incoming flow for the next signal. The proposed architecture involves the video analysis and exploration using some machine learning techniques to estimate and guess the flow of traffic.