A lane departure warning system using lateral offset with uncalibrated camera

In this paper, we propose an automatic method for determining the lateral offset of the vehicle with respect to the center of the lane. Initially, a linear-parabolic model is used to detect lane boundaries. The linear part of the model is then used to obtain an estimation of the lateral offset, without the knowledge of any intrinsic or extrinsic camera parameter. Finally, the analysis the offset across time is then used to determine a lane departure measure, allowing lane crossings to be detected in advance.

[1]  Massimo Bertozzi,et al.  GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection , 1998, IEEE Trans. Image Process..

[2]  Alexander Zelinsky,et al.  Robust vision based lane tracking using multiple cues and particle filtering , 2003, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683).

[3]  Massimo Bertozzi,et al.  Real-time lane and obstacle detection on the GOLD system , 1996, Proceedings of Conference on Intelligent Vehicles.

[4]  Dinggang Shen,et al.  Lane detection and tracking using B-Snake , 2004, Image Vis. Comput..

[5]  Tang-Hsien Chang,et al.  A vision-based vehicle behavior monitoring and warning system , 2003, Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems.

[6]  Gerd Wanielik,et al.  A new approach for lane departure identification , 2003, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683).

[7]  Antonio Guiducci.  Camera Calibration for Road Applications , 2000, Comput. Vis. Image Underst..

[8]  Joon Woong Lee,et al.  A lane-curve detection based on an LCF , 2003, Pattern Recognit. Lett..

[9]  E. Teoh,et al.  LANE DETECTION USING CATMULL-ROM SPLINE , 1998 .

[10]  Luis Magdalena,et al.  A Color Vision-Based Lane Tracking System for Autonomous Driving on Unmarked Roads , 2004, Auton. Robots.

[11]  Michalis E. Zervakis,et al.  A survey of video processing techniques for traffic applications , 2003, Image Vis. Comput..

[12]  Ernst D. Dickmanns,et al.  EMS-vision: application to hybrid adaptive cruise control , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[13]  A. Aeron-Thomas,et al.  ESTIMATING GLOBAL ROAD FATALITIES , 2000 .

[14]  C.R. Jung,et al.  A lane departure warning system based on a linear-parabolic lane model , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[15]  A.G. Ulsoy,et al.  CAPC: A Road-Departure Prevention System , 1996, IEEE Control Systems.

[16]  Wilfried Enkelmann,et al.  A video-based lane keeping assistant , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[17]  N. Kaempchen,et al.  Multiple-model tracking for the detection of lane change maneuvers , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[18]  Michel Bilodeau,et al.  Road segmentation and obstacle detection by a fast watershed transformation , 1994, Proceedings of the Intelligent Vehicles '94 Symposium.

[19]  Se-Young Oh,et al.  A driver adaptive lane departure warning system based on image processing and a fuzzy evolutionary technique , 2003, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683).

[20]  Cláudio Rosito Jung,et al.  A robust linear-parabolic model for lane following , 2004, Proceedings. 17th Brazilian Symposium on Computer Graphics and Image Processing.

[21]  Joon Woong Lee,et al.  A Machine Vision System for Lane-Departure Detection , 2002, Comput. Vis. Image Underst..

[22]  Sukhan Lee,et al.  A vision based lane departure warning system , 1999, Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289).

[23]  Antonio Guiducci,et al.  Parametric Model of the Perspective Projection of a Road with Applications to Lane Keeping and 3D Road Reconstruction , 1999, Comput. Vis. Image Underst..

[24]  J. Goldbeck,et al.  Lane detection and tracking by video sensors , 1999, Proceedings 199 IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems (Cat. No.99TH8383).