Distributed and collaborative system to improve traffic conditions using fuzzy logic and V2X communications

Abstract

Nowadays, the increase in the number of vehicles on the roads has brought about several problems such as an increase in traffic congestion and, consequently, in polluting emissions. These problems are especially severe in urban environments. It is crucial to perform a sustainable urban mobility plan to improve the traffic and therefore, reduce the negative impacts caused by traffic jams. To this end, this paper presents a smart mobility plan that employs a collaborative driving strategy. Each vehicle tries to infer traffic conditions using its own status and the information shared by other peers. Using a fuzzy logic approach, vehicles perform decisions in accordance with the traffic levels inferred in real time. The designed mobility plan has been tested through a simulation environment and considering two types of urban areas in a typical European city (a peripheral area and a more congested city centre). If we compare the performance of traffic with and without the system designed, with our approach average speeds increase by up to 11.20 % and CO₂ emissions are reduced by up to 12.27 %. Thus, our results show that the mobility plan has helped to enhance the ability of cars to be able to solve problems caused by traffic congestion and traffic jams.