{"id":3451,"date":"2024-08-28T20:24:02","date_gmt":"2024-08-28T20:24:02","guid":{"rendered":"http:\/\/journal.ziu-university.net\/?p=3451"},"modified":"2024-08-28T20:24:03","modified_gmt":"2024-08-28T20:24:03","slug":"%d8%af%d9%85%d8%ac-%d9%85%d8%aa%d8%ad%d9%83%d9%85-%d8%a7%d9%84%d9%85%d9%86%d8%b7%d9%82-%d8%a7%d9%84%d8%b6%d8%a8%d8%a7%d8%a8%d9%8a-%d9%81%d9%8a-%d8%a7%d9%84%d8%aa%d8%b7%d8%a8%d9%8a%d9%82-%d8%a7%d9%84","status":"publish","type":"post","link":"https:\/\/journal.ziu.edu.sy\/?p=3451","title":{"rendered":"\u062f\u0645\u062c \u0645\u062a\u062d\u0643\u0645 \u0627\u0644\u0645\u0646\u0637\u0642 \u0627\u0644\u0636\u0628\u0627\u0628\u064a \u0641\u064a \u0627\u0644\u062a\u0637\u0628\u064a\u0642 \u0627\u0644\u0639\u0645\u0644\u064a: \u062f\u0631\u0627\u0633\u0629 \u0639\u0644\u0649 \u0623\u0646\u0638\u0645\u0629 \u0627\u0644\u0642\u064a\u0627\u062f\u0629 \u0627\u0644\u0630\u0627\u062a\u064a\u0629"},"content":{"rendered":"\n

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Abstract
<\/strong>This research aims to integrate fuzzy logic controllers into autonomous driving systems to enhance their performance in complex driving scenarios. The article reviews the concept of the fuzzy logic controller and its basic components, including fuzzy sets, membership functions, and inference rules, with a focus on selecting input and output variables. A simulation methodology was used to evaluate the effectiveness of fuzzy logic controllers in handling uncertainties and ambiguities in dynamic environments, emphasizing tasks such as navigation and collision avoidance. Simulation results demonstrated that fuzzy logic controllers improved the ability of the autonomous driving system to make quick and accurate decisions under challenging conditions, leading to overall system performance enhancement. These findings suggest that fuzzy logic controllers can be an effective tool to enhance the capability of autonomous driving systems to handle real-world challenges in complex driving environments, thereby improving system safety and applicability. The study highlights the advantages of fuzzy logic in handling imprecise data and discusses future research directions and the development of fuzzy logic controllers to ensure their performance improvement and increasing benefit in various fields, including intelligent control and systems requiring management of uncertainty and imprecise variables.
Keywords: Fuzzy Logic, Autonomous Control, Artificial Intelligence, Inference Rules, Fuzzy System.<\/p>\n\n\n\n

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