Abstract

Traffic congestion is an urban mobility problem, which generates stress to drivers as well as economic losses. Intelligent transportation systems can assist in the identification and reduction of vehicular traffic congestion. In this context, this work proposes a solution for the detection and control of congested roads based on inter-vehicle communication. The main goal of the proposed solution is to decrease CO2 emissions, the average trip time, and fuel consumption by avoiding congested roads. Simulation results show that the proposed solution yields (i) a high acceptance rate in the classification of congestion levels., (ii) reduction in average trip time, (iii) reduction in fuel consumption, and (iv) reduced CO2 emissions. In particular, the trip time decreased approximately 70%, the fuel consumption 46%, and the CO2 emission 58%.