센서 구성을 고려한 비전 기반 차선 감지 시스템 개발

Development of A Vision-based Lane Detection System with Considering Sensor Configuration Aspect

  • 박재학 (한양대학교 정밀기계공학과) ;
  • 홍대건 (한양대학교 정밀기계공학과) ;
  • 허건수 (한양대학교 기계공학부) ;
  • 박장현 (한양대학교 기계공학부) ;
  • 조동일 (서울대학교 전기컴퓨터 공학부)
  • Park Jaehak (Department of Precision Mech. Eng., Hanyang University) ;
  • Hong Daegun (Department of Precision Mech. Eng., Hanyang University) ;
  • Huh Kunsoo (School of Mechanical Engineering, Hanyang University) ;
  • Park Jahnghyon (School of Mechanical Engineering, Hanyang University) ;
  • Cho Dongil (School of Electrical Eng. And Computer Sci. Seoul National University)
  • 발행 : 2005.07.01

초록

Vision-based lane sensing systems require accurate and robust sensing performance in lane detection. Besides, there exists trade-off between the computational burden and processor cost, which should be considered for implementing the systems in passenger cars. In this paper, a stereo vision-based lane detection system is developed with considering sensor configuration aspects. An inverse perspective mapping method is formulated based on the relative correspondence between the left and right cameras so that the 3-dimensional road geometry can be reconstructed in a robust manner. A new monitoring model for estimating the road geometry parameters is constructed to reduce the number of the measured signals. The selection of the sensor configuration and specifications is investigated by utilizing the characteristics of standard highways. Based on the sensor configurations, it is shown that appropriate sensing region on the camera image coordinate can be determined. The proposed system is implemented on a passenger car and verified experimentally.

키워드

참고문헌

  1. M. Bertozzi and A. Broggi, 'GOLD: A Parallel Real- Time Stereo Vision System for Generic Obstacle and Lane Detection,' IEEE Trans. on Image Processing, Vol.7, No.1, pp.62-81, 1998 https://doi.org/10.1109/83.650851
  2. D. Pomerleau, 'RALPH: Rapidly Adapting Lateral Position Handler,' Proc. IEEE IVS, pp.506-511, 1995
  3. A. Takahashi and Y. Ninomiya, 'Model-Based Lane Recognition,' Proc. IEEE IVS, pp.162-166, 1996
  4. J. Goldbeck and B. Huertgen, 'Lane Detection and Tracking by Video Sensors,' IEEE International Conference on ITS, pp.74-79, 1999
  5. E. D. Dickmanns and B. D. Mysliwetz, 'Recursive 3-D Road and Relative Ego-state Recognition,' IEEE Trans. on PAMI, Vol.14, No.2, pp.199-213, 1992 https://doi.org/10.1109/34.121789
  6. C. F. Lin and A. G. Ulsoy, 'Lane Geometry Reconstruction: Least Square Curve Fit Versus Kalman Filter,' ASME Advanced Automotive Technologies, DSC-Vol.56/DE- Vol.86, pp.6370, 1995
  7. K. Huh and Y. Park, 'Development of a Robust Lane Sensing System using Vision Sensors,' Proc. of AVEC, pp.769-774, 2002
  8. J. Park, J. Lee, K. Jhang, J. Jung and K. Ko, 'The Detection of the Lane Curve using the Lane Model on the Image Coordinate Systems,' Transactions of KSAE, Vol.11, No.1, pp.193-200, 2003
  9. S. Ernst, C. Stiller, J. Goldbeck and C. Roessig, 'Camera Calibration for Lane and Obstacle Detection,' IEEE Int. Conf. on Intelligent Transportation Systems, pp.356-361, 1999
  10. Z. Zhang, 'Flexible Camera Calibration By Viewing a Plane From Unknown Orientations,' 7th IEEE Int. Conf. on Computer Vision, pp.666-673, 1999
  11. J. Heikkila, O. Silven, 'A Four-step Camera Calibration Procedure with Implicit Image Correction,' IEEE Computer Society Computer Vision and Pattern Recognition Conf., pp.1106-1112, 1997