An Empirical Research in Autonomous Vehicles Control
Ngo Tung Son1, Tran Binh Duong2, Bui Ngoc Anh3, Luong Duy Hieu4
1Ngo Tung Son, Computing Fundamental Department, FPT University, Hanoi, India.
2Tran Binh Duong, Software Engineering Department, FPT University, Hanoi, Vietnam, India.
3Bui Ngoc Anh, Information Technology Specialty, FPT University, Hanoi, Vietnam, India.
4Luong Duy Hieu, Computing Fundamental Department, FPT University, Hanoi, Vietnam, India.
Manuscript received on June 22, 2017. | Revised Manuscript received on June 29, 2017. | Manuscript published on July 05, 2017. | PP: 52-46 | Volume-7 Issue-3, July 2017. | Retrieval Number: C3037077317/2017©BEIESP
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©The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/
Abstract: Recent years have witnessed a growing attention to automatic-driving vehicles as this is one of the key technologies for the future industry. Even though being successful at many aspects, there has been a long interest in designing an efficient control system for automatic driving vehicles. This paper empirically demonstrates the efficiency of our system which only employs low cost camera for visual sensing. Our approach puts the focus on 2 main objectives in autonomous vehicle control: (1) lane detection and (2) speed and direction decisions for the sake of fast processing. This is to help the vehicle always moves in the right lane while keeping a suitable speed. For decision making fuzzy logic is used for effective reasoning. We test our system in mini automatic-vehicles to show that it is not only efficient but also reliable. At a practical test, the system has won third place at the Vietnam Digital Race challenge 2017.
Keywords: Image Processing, Lane Detection, Support Vector Machine, Automatic-Car Control, Fuzzy Logic.