Discovering automobile congestion and volume using vanet’s

Automobile traffic congestion is a major problem all over world, resulting in wastage of valuable time and money. Vehicular ad hoc networks (VANET) play a major role in discovering and disseminating congestion. Provision of more information on road conditions to drivers will help them decide on the most effective route. Traffic volume is a valuable parameter for drivers to anticipate the state of the congestion. The moderate amount of research that has been done to date on discovering congestion has been based on GPS. We propose an alternative to GPS based systems to discover congestion and traffic volume. The proposed idea is based on discovering congestion by observing the neighbor beacons and a tree based counting algorithm is used to count the total number of nodes in congestion. Tree based counting algorithms are also used in sensor networks. In sensor networks nodes are fixed, where as in VANET nodes have high mobility. Congestion keeps the node more or less fixed and provides the opportunity to run a tree based algorithm. With the simulation results we have shown that the proposed idea can be used to discover emergent congestion and to count the number of vehicles in congestion.