A traffic control model on VANET environment for minimum road risk in a shortest way

Global warming and its related phenomena such as iceberg melting and sea level rising, is the result of human´s penchant to industrial living which leads to increase of greenhouse gas emission. Increase of greenhouse gas inside the atmosphere gets result in Greenhouse effect phenomenon. This problem has received increasing attention from scholars and industries in recent years under name of green. Controlling or decreasing of Green House Gas emissions is possible by green programs and technologies in future. These programs are considered as an effective solution of global warming prevention. The main reason of greenhouse gas emissions in urban environment is unnecessary deceleration and acceleration of moving vehicles as well as drivers´ risky actions such as reverse moves, fast speed zigzag moves. Therefore, a traffic management system is needed for providing smooth trips for drivers. By a periodic central abnormal and normal vehicles clustering, at each moment we can suggest less risk roads to vehicles for reaching to their destination with less risk. In addition potential hazards can be avoided. In this paper, we propose a model to calculate mobile vehicles risk by monitoring them and calculate the shortest path with minimum risk based on updated collected data in each moment. This model can use in both case of general and emergency vehicle.