KENDALI KECEPATAN PADA AUTONOMOUS ELECTRIC VEHICLE MENGGUNAKAN FUZZY LOGIC DENGAN INPUT BERBASIS COMPUTER VISION

SINULINGGA, REGITA FORTUNA and Dwijayanti, Suci (2023) KENDALI KECEPATAN PADA AUTONOMOUS ELECTRIC VEHICLE MENGGUNAKAN FUZZY LOGIC DENGAN INPUT BERBASIS COMPUTER VISION. Undergraduate thesis, Sriwijaya University.

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Abstract

In an autonomous electric vehicle system, a speed control system is needed to regulate the car's speed to ensure safety goals are met. As autonomous vehicles operate, they must be able to adjust their speed according to the surrounding environment. However, existing methods generally only consider ideal road conditions and have not been implemented in real-time. Therefore, in this research, object and road detection using a computer vision approach are utilized to measure the distance between the car and objects. This allows the autonomous vehicle to make accurate decisions on whether to move fast, moderately, or slowly based on the road it is traversing. Consequently, the autonomous vehicle can adjust its speed according to the environmental conditions it encounters. Fuzzy logic with Mamdani and Sugeno methods is employed in this study to automatically and stably control the speed of the autonomous electric vehicle from the starting location to the destination, considering various road conditions such as left sloping, straight, and right sloping, with or without objects encountered in real-time. The testing is conducted using 5 members during simulation and 3 members for real conditions, with inputs in the form of distance and steering angle. The speed, represented by the servo angle ranging from 0 to 1800, serves as the output. Throughout all the tests performed for different speed output representations using the servo, it is demonstrated that the Mamdani method is more accurate compared to the Sugeno method, which utilizes only singleton output. The results obtained align with the predefined rules for the speed control system.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	fuzzy logic controller, speed control system, autonomous vehicle, steering angle, distance
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1-9971 Electrical engineering. Electronics. Nuclear engineering > TK1 Electrical engineering--Periodicals. Automatic control--Periodicals. Computer science--Periodicals. Information technology--Periodicals. Automatic control. Computer science. Electrical engineering. Information technology.
Divisions:	03-Faculty of Engineering > 20201-Electrical Engineering (S1)
Depositing User:	Regita Fortuna Sinulingga
Date Deposited:	28 Jul 2023 07:44
Last Modified:	28 Jul 2023 07:44
URI:	http://repository.unsri.ac.id/id/eprint/123456

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