Hybrid algorithm: Fuzzy Logic-Genetic Algorithm on traffic light intelligent system

Abstract

This paper presents a hybrid algorithm that combines Fuzzy Logic Controller (FLC) and Genetic Algorithms (GA) and its application on a traffic light system. FLCs have been widely used in many applications in diverse areas, such as control system, pattern recognition, signal processing and forecasting. They are, essentially, ruled-based systems, in which the definition of these rules and fuzzy membership functions is generally base on verbally formulated rules that overlap through the parameter space. They have a great influence over the performance of the system. On the other hand, the Genetic Algorithm is a metaheuristic that provides a robust search in complex spaces. In this work, it was use to adapt the decision rules of FLCs that define an intelligent traffic light system, obtaining a higher performance than a classical FLC-based control. The simulation results yielded by the hybrid algorithm show an improvement of up to 34% in the performance with respect to a standard traffic light controller - Conventional traffic controller (CTC) -, and up to 31% in the comparison with a traditional logic FLC Controller.