Journal of the Korea Institute of Military Science and Technology (한국군사과학기술학회지)

The Korea Institute of Military Science and Technology (한국군사과학기술학회)
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Development of Lane and Vehicle Headway Direction Recognition System for Military Heavy Equipment's Safe Transport - Based on Kalman Filter and Neural Network -

안전한 군용 중장비 수송을 위한 차선 및 차량 진행 방향 인식 시스템 개발 - 칼만 필터와 신경망을 기반으로 -

  • Published : 2007.09.30
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Abstract

In military transportation, the use of wide trailer for transporting the large and heavy weight equipments such as tank, armoured vehicle, and mobile gunnery is quite common. So, the vulnerability of causing traffic accidents for these wide military trailer to bump or collide with another car in adjacent lane is very high due to its broad width in excess of its own lane's width. Also, the possibility of these strayed accidents can be increased especially by the careless driver. In this paper, the recognition system of lane and vehicle headway direction is developed to detect the possible collision and warn the driver to prevent the fatal accident. In the system development, Kalman filtering is used first to extract the border of driving lane from the video images supplied by the CCD camera attached to the vehicle and the driving lane detection is completed with regression analysis. Next, the vehicle headway direction is recognized by using neural network scheme with the extracted parameters of the detected driving lane feature. The practical experiments for the developed system are also carried out in the real traffic road of Seoul city area and the results show us the more than 90% accuracy in recognizing the driving lane and vehicle headway direction.

Keywords

References

  1. 경찰청 : http://npa.korea.kr
  2. 건설교통부, '도로의 구조.시설 기준에 관한 규칙', p. 10, 1999
  3. Araki H., Yamada K. and Hiroshima Y., 'Development of rear-end collision avoidance system', Proceedings of the IEEE Intelligent Vehicles Symposium, pp. 224-229, 1996
  4. Russel, M. E., Crain, A., Curran, A., Campbell, R. A., Drubin C. A. and Miccioli, W. F., 'Millimeter wave radar sensor for automotive intelligent cruise control(ICC)', IEEE-MIT-S, Denver, CO, USA, pp. 1257- 1260, 1997
  5. 이형석, '레이저와 컴퓨터 비전을 이용한 Stop & Go 시스템', 고려대학교 석사 학위 논문, 2004
  6. 이광순, '버스 승객의 안전한 하차를 위한 컴퓨터 비전 기반의 차랑탐지 시스템 개발', 고려대 학교 석사 학위 논문, 2005
  7. Broggi, A., 'Robust real-time lane and road detection in critical shadow conditions', In Proceedings IEEE International Symposium on Computer Vision, pp. 19-21, 1995
  8. 권화중, 이준호, 'Hough 변환과 2차 곡선 근사화에 기반한 효율적인 차선 인식 알고리즘', 한국정보처리학회 논문지, 제6권, 제12호, pp. 3710-3717, 1999
  9. Gonzalez, J. P. and Ozgumer, U., 'Lane Detection Using Histogram-Based Segmentation and Detection Trees', IEEE Intelligent Transportation Systems Conference Proceedings Dearborn, pp. 346-351, 2000
  10. 이응주, '그룹화 블록 스네이크 알고리즘을 이용한 차선주출', 멀티미디어학회논문지, 제3권, 제5호, pp. 445-453, 2000
  11. Wong, S. M. and Xie, M., 'Lane Geometry Detection for the Guidance of Smart Vehicle', Proceedings of the IEEE/IEEJ/JSAI International Conference on Intelligent Transportation System, Tokyo, Japan, pp. 925-928, 1995
  12. 성민철, 이상화, 조남익, '체인코드를 이용한 새로운 에지 방향 결정 기법', 한국군사과학기술학회 논문지, 제10권, 제1호, pp. 101-106, 2007
  13. Welch, G., Bishop, G., 'An Introduction to the Kalman Filter', UNC-Chapel Hill, 2004
  14. 박종웅, 장경영, 이준웅, '차선의 회전 방향 인식을 위한 신경회로망 응용 화상처리', 한국자동차공학회논문집, 제7권, 제5호, pp. 178-185, 2003
  15. Moon, H. S., You, T. W., Yoo, H. W., Sohn, M. H. and Jang, D. S., 'A recovery system of broken relics using least squares fitting and vector similarity techniques', Expert Systems and Applications, Vol. 28, pp. 469-481, 2005 https://doi.org/10.1016/j.eswa.2004.12.009