A Multi-Scenario Evaluation of Adaptive Fuzzy Logic Algorithms for Intelligent Traffic Signal Management in Urban Intersections

Abstract

The article presents a performance analysis of the advanced adaptive control systems of traffic lights that are based on the advanced fuzzy logic. They include Modified Intuitionistic Fuzzy Logic Algorithm (MIFLA) and the Modified Interval Type-2 fuzzy logic (MIT2FL) at a four-leg intersection. In this article, there is an integration of these fuzzy models with the SUMO platform with respect to the weaknesses of the traditional fixed-time traffic lights, particularly in rapidly urbanizing areas. This will be to achieve a real-time dynamic control system. The simulation matrix was a grid of the nine scenarios in which the performance of the controllers was assessed to some extent, depending on the traffic and directional imbalances. The results reveal that the MIT2FL is more effective than the MIFLA and the Modified Webster benchmark. MIT2FL is less divergent, has shorter queuing times, and is more flexible. This occurs when the demand is high, and the traffic conditions are not proportional. This work is significant because it provides fuzzy logic controllers that can deal with uncertainty. It also creates a benchmarking model of a typical multi-scenario. Moreover, it gives the opportunity for reproducibility of the findings in real traffic implementation. The innovations will assist in making the city smarter and easier to move around. They manage congestion, delays, and improve the sustainability of smart traffic control.