Kontrol Hierarkis pada Sistem Autonomous Emergency Braking (AEB) Mobil Otonom dengan Mempertimbangkan Kemiringan Jalan

Tsalatin, Rochim Fajri (2024) Kontrol Hierarkis pada Sistem Autonomous Emergency Braking (AEB) Mobil Otonom dengan Mempertimbangkan Kemiringan Jalan. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 5022201011-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 April 2026. Download (7MB) | Request a copy

Abstract

Pada tugas akhir ini, skema kontrol hierarkis akan dikembangkan pada sistem Autonomous Emergency Braking (AEB). Pada upper layer digunakan metode Rule-Based Supervisory dimana berbasis jarak aman untuk menentukan percepatan yang diinginkan dalam menghindari tabrakan berkendara. Metode ini menggunakan bentuk sederhana dari AI (Artificial Intelligence) dimana sistem akan meniru penalaran manusia dalam memecahkan permasalahan berdasarkan input sistem. Sedangkan pada lower layer, dirancang Linear Quadratic Tracking (LQT) untuk melakukan tracking perlambatan dimana memiliki kemampuan tracking setpoint yang tinggi, robustness dan kemampuan beradaptasi yang relatif tinggi, serta intensitas komputasi yang sedang. Model dinamis non-linier juga diimplementasikan. Selanjutnya hasil rancangan akan divalidasi secara software dengan berbagai skenario tes dan variasi kemiringan jalan. Hasil pengujian dari sistem yang dirancang mampu membuat mobil Ego terhindar dari tabrakan untuk semua skenario dengan jarak minimum terkecil sebesar 11.75 cm. Kontroler yang digunakan cukup baik dimana menghasilkan MSE yang kecil dalam tracking kecepatan yaitu dengan rata-rata sebesar 0.0039. Slip pada roda depan dan belakang yang dihasilkan juga kecil yaitu di bawah 5% kecuali untuk beberapa skenario dengan kecepatan awal mobil Ego sebesar 25 m/s.
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In this final project, a hierarchical control scheme will be developed for Autonomous Emergency Braking (AEB) system. In the upper layer, Rule-Based Supervisory with safe distance-based is used to determine the desired acceleration to avoid a driving collision. This method uses a simple form of AI (Artificial Intelligence) where the system will imitate humans in solving problems based on system input. Meanwhile, on the lower layer, Linear Quadratic Tracking (LQT) is designed to track deceleration which has high setpoint tracking capability, relatively high robustness and adaptability, and moderate computing intensity. A non-linear dynamic model is also implemented. Furthermore, the design results will be validated using software with variations in slope. The test results of the designed system were able to prevent the Ego Vehicle from colliding in all scenarios, with the smallest minimum distance of 11.75 cm. The controller used is quite good, producing a small MSE in speed tracking with an average of 0.0039. Slip on the front and rear wheels is also small, at under 5% except for several scenarios with the initial speed of the Ego Vehicle being 25 m/s.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Autonomous Emergency Braking, Hierarchical Control, Linear Quadratic Tracking, Rule-Based Supervisory, Kontrol Hierarkis
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ217 Adaptive control systems T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3070 Automatic control T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL152.8 Vehicles, Remotely piloted. Autonomous vehicles.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User:	Rochim Fajri Tsalatin
Date Deposited:	02 Feb 2024 03:07
Last Modified:	02 Feb 2024 03:07
URI:	http://repository.its.ac.id/id/eprint/105933

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