NAVOPT: Navigator Assisted Vehicular Route OPTimizer

The number of vehicles has been growing compared to limited road capacity, leading to severe traffic congestion during rush hour. Urban planners are looking for solutions to reduce traffic congestion. Real time traffic information obtained from vehicles can help reduce congestion exploiting the wireless communications architecture recently established for safety and traffic control purposes. In this paper, we propose NAVOPT, a vehicular routing strategy assisted by the on board navigator as well as the navigation server. The on board navigator equipped with area map and GPS monitor, reports its own position to the server via wireless connection (WiFi or 3G), in turns, it acquires from the Server a minimum cost path (i.e. path with shortest travel time) under the current traffic conditions. Under NAVOPT, the Server uses a flow deviation (FD) algorithm to compute optimal vehicle routes by load balancing vehicle traffic over alternate routes. We establish an analytic model of NAVOPT, we also simulate it using a SUMO simulator to verify its accuracy. From the simulation results, the NAVOPT model shows robustness to delay and speed and efficacy in controlling the traffic as the number of vehicles increases.