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지능형자동차의 적응형 제어를 위한 차선인식

Title
지능형자동차의 적응형 제어를 위한 차선인식
Translated Title
Lane Detection for Adaptive Control of Autonomous Vehicle
Authors
김현구주영환이종훈박용완정호열
DGIST Authors
김현구; 주영환; 이종훈; 박용완; 정호열
Issue Date
2009-12
Citation
대한임베디드공학회논문지, 4(4), 180-189
Type
Article
Article Type
Article
ISSN
1975-5066
Abstract
Currently, most automobile companies are interested in research on intelligent autonomous vehicle. They are mainly focused on driver’s intelligent assistant and driver replacement. In order to develop an autonomous vehicle, lateral and longitudinal control is necessary. This paper presents a lateral and longitudinal control system for autonomous vehicle that has only mono-vision camera. For lane detection, we present a new lane detection algorithm using clothoid parabolic road model. The proposed algorithm in compared with three other methods such as virtual line method, gradient method and hough transform method, in terms of lane detection ratio. For adaptive control, we apply a vanishing point estimation to fuzzy control. In order to improve handling and stability of the vehicle, the modeling errors between steering angle and predicted vanishing point are controlled to be minimized. So, we established a fuzzy rule of membership functions of inputs (vanishing point and differential vanishing point) and output (steering angle). For simulation, we developed 1/8 size robot (equipped with mono-vision system) of the actual vehicle and tested it in the athletics track of 400 meter. Through the test, we prove that our proposed method outperforms 98 % in terms of detection rate in normal condition. Compared with virtual line method, gradient method and hough transform method, our method also has good performance in the case of clear, fog and rain weather.
URI
http://hdl.handle.net/20.500.11750/6507
http://uci.or.kr/G704-SER000010426.2009.4.4.001
Publisher
대한임베디드공학회
Related Researcher
  • Author Lee, Jonghun  
  • Research Interests Radar, AI, DL/ML, signal processing
Files:
There are no files associated with this item.
Collection:
Division of Automotive Technology1. Journal Articles


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