Application Zadeh’s Implication in Designing Fuzzy Controller

Abstract

The article investigates the problem of traffic signal control within the framework of a fuzzy logic approach, with particular emphasis on the application of Zadeh’s fuzzy implication. The rapid development of artificial intelligence requires the processing of information of various types. Today, the mathematical foundation of artificial intelligence is based on binary logic and probability theory, which leads to information loss. According to the scientific literature, one of the theories that has contributed to the development of artificial intelligence is fuzzy logic. Based on logical inference and fuzzy implications, imprecise information can be effectively processed. For this reason, fuzzy implications are still widely used today. In this study, a conditional reasoning method based on fuzzy logic is employed and applied to controller design. Within the methodological framework, information processing is carried out using fuzzy inference, membership functions, and Zadeh’s implication. During model development, real traffic conditions are taken into account, and parameters such as the number of vehicles passing during the green light (Arrival Vehicles), the number of vehicles waiting at the red light (Waiting Vehicle in Queue), weather variability (Humidity or Fog), and green light duration are used. Computer simulations are performed based on data obtained from the scientific literature and are analyzed using a new approach. As a result, it is shown that the proposed method is an effective approach for evaluating traffic congestion and improving the efficiency of traffic signal control systems.