Discovering Dynamic Vehicular Congestion using VANETs

There are several centralized approaches to discover automobile congestion. Centralized approaches have significant problems. Decentralized approaches like Vehicular Ad hoc Networks (VANET) play a major role in discovering congestion and disseminating congestion information. No of vehicles that have got stuck in congestion is a valuable parameter for drivers to anticipate the state of the congestion. We propose an alternative to GPS based systems to discover congestion and its state. We assume all the vehicles are equipped with short range wireless devices and each vehicle has a unique id. The proposed approach 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. Congestion keeps the node more or less fixed and provides the opportunity to run a tree based algorithm. Construction of the tree and counting happens at the same time and it eliminates the possibility of building circular loops. Vehicle with the highest node id becomes the root. We have developed a mobility model that detects the buildup of congestion near a color light in a single road with two lanes in same direction that enables to take a count of the vehicles.