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

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307002728	T123456	T1234562023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1234562023

Publisher

Inderalaya : Prodi Teknik Elektro, Fakultas Teknik Universitas Sriwijaya., 2023

Collation

xiv, 57 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

621.382 07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Teknik Komunikasi
Prodi Teknik Elektro

Specific Detail Info

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Statement of Responsibility

SEPTA

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