Abstract
This study combines fuzzy logic with a modified genetic algorithm (GA) to provide a novel method of dynamic traffic management in urban settings. The study fills in a vacuum in the literature by reviewing the body of work and focusing on the integration of fuzzy logic and modified GAs for dynamic traffic management. A fuzzy logic system enables real-time decision-making, and the proposed methodology formulates the optimization problem, defines the objective function, and encodes solutions (chromosomes) for the modified GA. The approach's effectiveness is demonstrated by experimental evaluations carried out in a simulation environment, which exhibit notable enhancements in traffic flow when compared to conventional methods. The adaptability of the fuzzy logic system in handling dynamic traffic scenarios can be understood through an analysis of the evolution of its parameters. An analysis of the findings reveals the approach's advantages, disadvantages, and possible directions for future study. It propels the field by giving a suitable methodology to compelling traffic stream improvement in metropolitan settings.
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