융합정보논문지 (Journal of Convergence for Information Technology)

중소기업융합학회 (Convergence Society for SMB)
권호 표지
DOI QR코드

DOI QR Code

졸음운전 감지 및 방지 시스템 연구

Study for Drowsy Driving Detection & Prevention System

  • 투고 : 2018.05.24
  • 심사 : 2018.06.20
  • 발행 : 2018.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

최근, 자동차 교통사고의 인명 피해가 급속히 증가하고 있으며 경상보다는 중상 및 사망이 많은 대형사고가 증가하고 있다. 대형사고의 70% 이상은 졸음운전으로 발생한다. 따라서, 본 논문에서는 교통사고의 대형 참사를 방지하기 위한 졸음운전 방지 시스템을 연구하였다. 본 논문에서는 졸음운전 감지 시스템을 위한 실시간 눈 깜빡임 인식 방법과 이산화탄소 증가에 따른 졸음 인식을 감지하도록 제안한다. 졸음운전 감지 시스템은 기존의 영상 검출과 딥러닝을 적용하였고 이산화탄소 증가 감지는 사물인터넷 기반으로 개발하였다. 이러한 두 가지 기법을 동시에 이용한 졸음운전 방지 시스템은 기존의 제품에 비해 정확성이 향상되었다.

Recently, the casualties of automobile traffic accidents are rapidly increasing, and serious accidents involving serious injury and death are increasing more than those of ordinary people. More than 70% of major accidents occur in drowsy driving. Therefore, in this paper, we studied the drowsiness prevention system to prevent large-scale disasters of traffic accidents. In this paper, we propose a real-time flicker recognition method for drowsy driving detection system and drowsy recognition according to the increase of carbon dioxide. The drowsy driving detection system applied the existing image detection and the deep running, and the carbon dioxide detection was developed based on the IoT. The drowsy prevention system using both of these techniques improved the accuracy compared to the existing products.

키워드

참고문헌

  1. Y. S. Jeong, Y. H. & Yon J. H. Ku. (2017). Hash-chain-based IoT authentication scheme suitable for small and medium enterprises. Journal of Convergence for Information Technology, 7(4), 105-111. DOI : 10.22156/CS4SMB.2017.7.4.105
  2. Taner Danisman, Ian Marius Bilasco lan, Chabane Djeraba. (2010). Drowsy driver detection system using eye blink patterns. Machine and Web Intelligence (ICMWI), 2010 International Conference, 10, 3-5. DOI : 10.1109/icmwi.2010.5648121
  3. R. Lienhart & J. Maydt. (2002). An Extended set of Haar-like Features for Rapid Object Detection. IEEE ICIP, 1, 900-903.
  4. H. J. Kim & W. Y. Kim. (2008). Eye Detection in Facial Images Using Zernike Moments with SVM. ETRI Journal, 30, 335-337. DOI : 10.4218/etrij.08.0207.0150
  5. Z. H. Zhou & X. Gen. (2004). Projection Functions for Eye Detection. Pattern Recognition, 37(5), 1049-1056. DOI : 10.1016/j.patcog.2003.09.006
  6. J. Qiang & Y. Xiaojie. (2002). Real-time eye, gaze, and face pose tracking for monitering driver vigilance. Real-time Imaging, 8(5), 357-377. DOI : 10.1006/rtim.2002.0279
  7. D. F. Dinges & R. Grace. (1998). PERCLOS: A Valid Psychophysiological Measure of Alertness As Assessed by Psychomotor Vigilance. Federal Highway Administration, Office of Motor Carriers. DOI : 10.1037/e509282006-001
  8. J. H. Skipper & W. W. Wierwille. (1985). AnInvestigation of Low-Level Stimulus-Induced Measures of Driver Drowsiness. Proceedings of the Conference on Vision in Vehicles, 139-148.
  9. David J. Mascord, Jeannie Walls and Graham A Starmer. (1995). Fatigue and Alcohol: interactive effects on human performance in driving-related tasks. Fatigue and Driving. Taylor & Francis, 189-205.
  10. S. Boverie, J. Leqellec & A. Hirl. (1998). Intelligent systems for video monitoring of vehicle cockpit. International Congress and Exposition ITS: Advanced Controls and Vehicle Navigation Systems, 1-5, 1998. DOI : 10.4271/980613
  11. H. Ueno, M Kaneda & M. Tsukino. (1994). Development of drowsiness detection system. Proceedings of Vehicle Navigation and Information Systems conference, Yokohama, Japan, 15-20.
  12. T. E. Hutchinson. (1998). Eye movement detection with improved calibration and speed. United States Patent, (4,950,069)
  13. H. Takchito, M. Katsuya, S. Kazunori & M. Yuji. (2002). Detecting Drowsiness while Driving by Measuring Eye Movement-A Polot Study. International Conference on Intelligent Transportation Systems, IEEE, 3-6. DOI : 10.1109/itsc.2002.1041206
  14. C. Dixon. (1999). Unobtrusive eyelid closure and visual of regard measurement system. Conference on ocular measures of driver alertness.
  15. T. Ishii. M. Hirose & H. Iwata. (1987). Automatic recognition of driver's facial expression by image analysis. Journal of the Society of Automotive Engineers of Japan, 41, 1398-1403.