Iswara, Adre Johan (2020) Deteksi Rambu Lalu Lintas untuk Navigasi Prototipe Autonomous Car menggunakan YOLO. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Autonomous Car merupakan bentuk dari inovasi teknologi Artificial Intelligence dalam bidang berkendara. Banyak fitur yang ada pada Autonomous Car dengan memanfaatkan sensor. Salah satunya fitur navigasi yang memanfaatkan sensor kamera untuk navigasi menggunakan Rambu Lalu Lintas. Akan tetapi, fitur navigasi yang menggunakan Rambu Lalu Lintas di Indonesia masih belum banyak ditemukan. Maka pada tugas akhir ini akan dikembangkan sebuah Sistem Pendeteksian rambu lalu lintas untuk navigasi pada Autonomous Car, sehingga Autonomous Car dapat berjalan sesuai dengan Rambu Lalu Lintas yang dikenali. Dengan menggunakan sensor kamera dan metode Deep Learning YOLO akan dapat mengenali Rambu Lalu Lintas dan diklasifikasikan menurut fungsinya. Dari hasil klasifikasi ini, akan dihasilkan respon yang sesuai dengan definisi perintah Rambu Lalu Lintas yang terlihat dan akan mengaktifkan melalui Aktuator pada Autonomous Car.
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Autonomous Car is one of Artificial Technology's innovation in driving field. Many features in Autonomous Car which is using a sensor. One of it's navigation feature which use camera sensor to navigate using the traffic sign. But this navigation feature which use Traffic Sign is very unlikely to be found in Indonesia. So, in this Final Assignment, it will be developed a Detection System for Autonomous Car to navigate using the Traffic Sign, so Autonomous Car can navigate according to the Traffic Sign, which is detected with the Autonomous Car. Using camera sensor and YOLO Deep Learning, Autonomous Car will recognize the Traffic Sign and classified Traffic Sign as with it's function. From this classification, Autonomous Car will respond as the detected Traffic Sign means and will activate Autonomous Car's Actuator.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSKom 006.42 Isw d-1 |
| Uncontrolled Keywords: | Autonomous Car, Sistem Pendeteksi, Rambu Lalu Lintas, YOLO, Aktuator. Autonomous Car, Detection System, Traffic Sign, YOLO, Actuator. |
| Subjects: | Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science) T Technology > TJ Mechanical engineering and machinery > TJ211.415 Mobile robots T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL589.2.N3 Navigation computer |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Computer Engineering > 90243-(S1) Undergraduate Thesis |
| Depositing User: | Adre Johan Iswara |
| Date Deposited: | 18 Mar 2025 07:36 |
| Last Modified: | 18 Mar 2025 07:36 |
| URI: | http://repository.its.ac.id/id/eprint/78415 |
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