Design and simulation of an artificially intelligent VANET for solving traffic congestion

Abstract

Traffic congestion has been plaguing motorists for years, and it progressively continues to get worse as the population continues to increase, resulting in an increase in the number of vehicles on the road. There are many factors that contribute to traffic congestion, however; there is one that plays a major role in giving rise to a phenomenon called “Traffic Waves”, and that is driver behavior. Traffic waves also called “stop waves” or “traffic shocks”, and they are travelling disturbances in the distribution of cars on a highway, which seems to appear without any reason, propagating backwards and severely slowing traffic flow on roads. The proposed research aims at reducing/eliminating traffic waves by integrating Artificial Intelligence, and Vehicular Ad-hoc Network (VANET) to create a driver aid that helps in combating traffic congestion as well as embedding safety awareness by dynamically rerouting traffic depending on road conditions.