Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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Design and Implementation of a System to Detect Zigzag Driving using Sensor

센서를 이용한 사행 운전 검출 시스템 설계 및 구현

  • Jeong, Seon-Mi (Department of Computer Science & Engineering, Gyeongnam National University of Science and Technology) ;
  • Kim, Gea-Hee (Department of Computer Science & Engineering, Gyeongnam National University of Science and Technology) ;
  • Mun, Hyung-Jin (Division of Information and Communication Engineering, Baekseok University) ;
  • Kim, Chang-Geun (Department of Computer Science & Engineering, Gyeongnam National University of Science and Technology)
  • 정선미 (경남과학기술대학교 컴퓨터공학과) ;
  • 김계희 (경남과학기술대학교 컴퓨터공학과) ;
  • 문형진 (백석대학교 정보통신학부) ;
  • 김창근 (경남과학기술대학교 컴퓨터공학과)
  • Received : 2016.09.30
  • Accepted : 2016.11.20
  • Published : 2016.11.28
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Abstract

Even though automakers have actively been conducting studies on autonomous navigation thanks to the development and application of wireless Internet technology, the traffic accident has been kept unsolved. The causes of the accident are drowsy driving, a mistake of a driver, environmental factors, and a wrong road structure; Driving manner and characteristics of a driver among the causes are significantly influential for the accident. In this paper, a study to measure characteristics of zigzag driving that can be seen before an occurrence of an accident regarding traffic accidents that can be incurred while driving manually or autonomously was conducted. While existing studies measured zigzag driving based on characteristics of the change of lateral angular velocity by imaging techniques or driving manner on the first and second lane, this study proceeded to measure zigzag driving by setting a lateral moving distance and a critical value range by utilizing the value of a sensor.

최근 자동차 업계는 무선 인터넷 기술의 발달과 응용의 확산으로 자율 주행의 연구가 활발히 진행 중에 있으나 교통사고는 아직도 해결되지 않는 부분이다. 사고의 요인으로는 졸음운전, 운전자의 실수, 환경적인 요소, 잘못된 도로 구조 등이 있으며 사고 원인의 하나인 운전자의 운전 행태와 특성은 교통사고에 큰 영향을 미친다. 본 논문에서는 자율 주행 및 자가 운전을 하는 경우에 발생 할 수 있는 교통사고에서 사고발생 전에 나타날 수 있는 사행운전의 특성을 판단하기 위한 연구를 수행하였다. 기존 연구에서는 영상기법이나 1,2차로의 운전행태로 횡방향 각속도 변화의 특성으로 사행 운전을 판단하였으나 본 논문은 센서의 값을 이용하여 횡방향의 이동거리와 임계 범위를 설정하여 사행 운전을 검출하는 연구를 진행하였다.

Keywords

References

  1. Hye G. Park, Hyong G. Lee and Soon H. Kwon, "Design of Autonomous Navigation Systems based on Wireless Networks", Journal of Korean Institute of Intelligent Systems, Vol. 22, No. 4, pp. 435-440, 2012. https://doi.org/10.5391/JKIIS.2012.22.4.435
  2. Hee Chang Moon, Hoon Je Woo and Jung Ha Kim, "Development of System Architecture and Communication Protocol for Unmanned Ground Vehicle", Journal of Institute of Control, Robotics and Systems Vol. 14, No.9, pp.873-880, 2008. https://doi.org/10.5302/J.ICROS.2008.14.9.873
  3. KwangOh Cho, JongDuck Moon, "Direction for Support of MOTIE R&D in Autonomous Driving Vehicle", Journal of the Korean Society of Automotive Engineers, Vol. 36, No. 7, pp. 20-25, 2014. https://doi.org/10.4491/KSEE.2014.36.1.20
  4. J. Y. Song, J. W. Park, K. Y. Jhang, J. W. Lee, I. S. Chang, "The Detection of Traffic Lanes and the Distance to The Forward Vehicle using the Machine Vision", Transactions of KSAE, Vol. 7, No. 3, pp. 310-320, 1999.
  5. L. N. Boyle and F. Mannering, "Impact of traveler advisory systems on driving speed: some new evidence", Transportation Research Part C12, vol. 12, pp. 57-72, 2004. https://doi.org/10.1016/j.trc.2003.09.001
  6. Gea-Hee Kim, Seon-Mi Jeong, Hyungjin Mun, Chang-Geun Kim, "Design of Curve Road Detection System by Convergence of Sensor", Journal of digital convergence, Vol. 14, No. 8, pp. 253-259, 2016. https://doi.org/10.14400/JDC.2016.14.8.253
  7. Jung-Mo Yang, Jeong-Ho Kim, "A Study on the Enhancement of Network Survivability through Smart Sensor Technologies Convergence", Journal of digital convergence, Vol. 14, No. 8, pp. 269-276, 2016. https://doi.org/10.14400/JDC.2016.14.8.269
  8. P. Li, X. Huang, Y. Fang, P. Lin, "Optimal placement of gateways in Vehicular Networks", IEEE Transactions on Vehicular Technology, Vol. 56, No. 6, pp. 3421-3430, 2007. https://doi.org/10.1109/TVT.2007.907230
  9. Ministry of Land, Transport and Maritime Affairs, "Road Disign Standards: Chapter 9", 2012.
  10. M. Eriksson and N. P. Papanikolopoulos, "Driver fatigue:a vision-based approach to automatic diagnosis", Transportation Research Part C9, Vol. 9, pp. 399-413, 2001. https://doi.org/10.1016/S0968-090X(00)00045-0
  11. Q. Ji, Z. zhu and P. Lan, "Real time and non-intrusive driver fatigue monitoring", In 7th IEEE Transactions on Vehicular Technology 4, 1052-1068, 2004.
  12. J. D. Wu and T. R. Chen, "Development of a drowsiness warning system based on the fuzzy logic images analysis", Expert Systems with Applications, Vol. 34, pp. 1556-1561, 2008. https://doi.org/10.1016/j.eswa.2007.01.019
  13. J. Wang, W. Xu and Y. Gong, "Real-time driving danger-level prediction", Engineering Applications of Artificial Intelligence, Vol. 23, pp. 1247-1254, 2010. https://doi.org/10.1016/j.engappai.2010.01.001
  14. N. Sharma and V. K. Banga, "Drowsiness arning system using artificial intelligence", World Academy of Science, Engineering and Technology 67, pp. 850-852, 2010.
  15. Hee-Sub Rim, Eun-Bi Jeong, Cheol Oh, Kyeong-Pyo Kang, "Detection of Unsafe Zigzag Driving Maneuvers using a Gyro Sensor", Review of KITS, Vol. 22, No 1, Vol. 10, No. 2, pp. 42-54, 2011.