Kristy, Felicia and Widjaja, Benny and Rusyadi, Rusman (2019) Adaptive Tuning Steering Control for Self-Driving Car. Bachelor thesis, Swiss German University.

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Abstract

Human beings always strive for increased productivity from time to time. In order to achieve that, one of the most recently developed technologies is self-driving car. Therefore, there is a need to start tapping into this specific field of study. While car manufacturers choose to develop the system as a built-in feature in their newest products, it will be more budget-friendly to develop a module that can be retrofitted into any existing car models while enabling users to enjoy such advanced technology. In order to do that, one of the main concepts to ensure flexibility and adaptability as well as reliability is to use adaptive tuning system. The online estimator is able to learn and predict behaviour of different types of car real-time with an absolute error of less than 0.004 radians, through the help of data fed by RTK GNSS module, with a standard deviation of less than 276.18mm. Moreover, the car is finally able to navigate itself with a standard deviation of less than 50cm. It is hoped that in the future, this research project can be explored and develop further by employing vision system for obstaclesensing, so that it contributes to the overall improvement of similar technology.

Item Type:	Thesis (Bachelor)
Uncontrolled Keywords:	Adaptive Tuning System ; Self-Driving Car ; Online Estimator ; RTK GNSS ; Steering Control
Subjects:	T Technology > TJ Mechanical engineering and machinery T Technology > TJ Mechanical engineering and machinery > TJ163.12 Mechatronics T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL259 Automobiles--Steering-gear
Divisions:	Faculty of Engineering and Information Technology > Department of Mechatronics Engineering
Depositing User:	Adityatama Ratangga
Date Deposited:	20 May 2020 06:27
Last Modified:	21 May 2020 14:31
URI:	http://repository.sgu.ac.id/id/eprint/678

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