Lane detection and tracking by video sensors

Describes a video sensor system for vehicle environment sensing. The system comprises a high dynamic range CMOS camera, dedicated image evaluation circuitry and image processing software for capturing vehicle environment data. The main part of the paper is concerned with the description of a real-time lane detection and tracking algorithm which is able to determine the course of the road ahead of the vehicle together with the position of the vehicle relative to the road with high accuracy. The key feature of the presented system is its ability to adapt to nearly all weather conditions and road types without any external adjustments together with its self-assessment capabilities, both of which are crucial for automotive applications.

[1]  U. Franke,et al.  Real time 3D-road modeling for autonomous vehicle guidance , 1992 .

[2]  Christoph Stiller,et al.  Camera calibration for lane and obstacle detection , 1999, Proceedings 199 IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems (Cat. No.99TH8383).

[3]  G. Bierman.  Factorization methods for discrete sequential estimation , 1977 .

[4]  Mohinder S. Grewal,et al.  Kalman Filtering: Theory and Practice , 1993 .

[5]  J. Geisler,et al.  ROMA - a system for model-based analysis of road markings , 1995, Proceedings of the Intelligent Vehicles '95. Symposium.

[6]  Dean A. Pomerleau,et al.  RALPH: rapidly adapting lateral position handler , 1995, Proceedings of the Intelligent Vehicles '95. Symposium.

[7]  R Risack.  ROBUST LANE RECOGNITION EMBEDDED IN A REAL-TIME DRIVER ASSISTANCE SYSTEM , 1998 .

[8]  Christoph Stiller,et al.  Vehicle Environment Sensing by Video Sensors , 1999 .

[9]  E. D. Dickmanns,et al.  A Curvature-based Scheme for Improving Road Vehicle Guidance by Computer Vision , 1987, Other Conferences.