VANETs Embedded Novel Traffic Management Paradigm for Smart City Milieu

In the existing milieu of contemporarily smart cities, the traffic situation is very saturated explicitly in the advanced industrial and populated cities that becomes worst at the rush hours. As population and correspondingly required number of vehicles are also increasing in cities, it is problematic for citizens at the major traffic points of these big cities. It is not only causing travelling delays, accidents and their corresponding emergency response services, traffic jams, parking availability but also contributing heavily to environmental air and noise pollution as well as health threats due to pollution produced by vehicle combustion. Many urban societies are now actualizing smart frameworks for traffic control that work on the standards of traffic automation with prevention of the previously mentioned issues, to keep away from such serious problems but, as per best of our knowledge, no single model deals with such issues comprehensively. The prime idea lies in collecting the current locations of vehicles immediately and suggesting the optimal route to the vehicle from departure node to destination node using optimal path finding algorithm before starting the journey, mainly focusing on reducing the Congestion, greenhouse gases emission and fuel expenditure and also providing the alternate plan to vehicles at any point of journey. In this context, a smart traffic monitoring and controlling framework has been proposed that can perform fast information communication and their concerning actions. In the said model, under a VANET (Vehicular Ad-hoc Network) scenario, the proposed Traffic management paradigm implements a smart signaling system along with optimal path finding algorithm to control congestion to regularly unify the traffic flow by avoiding the congestion at the smart township zones. The Paradigm includes other unique modules such as prevention of accidents, signaling control module, smart car parking module, Law Enforcement and Emergency response services controlling module those all collectively contribute to reduce carbon emission rate.