Design and Simulation of Vehicle Lane Tracking Using Matlab
Keywords:
Vehicle lane detection, Lane tracking, Hough transform, Video processing, SimulinkAbstract
This paper presents Vehicle Lane Tracking System based on real-time video to track lanes with minimal hardware and software requirements. The proposed system was designed to use low cost cameras and processing power of an on-board commodity laptop. The developed system was tested on different drives varying from a high speed drive on a high way to a low speed drive on the city roads. The system was able to detect the lane markings under various lighting conditions and on many types of roads ranging from unmarked roads to multi-lane national highways. The implemented system has an overall success rate of over 97% for lane detection.
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References
Joel C. McCall and Mohan M. Trivedi, “Video Based Lane Estimation and Tracking for Driver Assistance: Survey, System, and Evaluationâ€, IEEE Transactions on Intelligent Transportation Systems, Vol. 7, No. 1, pp. 20-37, 2006.
Daniel J. Dailey, F. W. “Cathey and Suree Pumrin, An Algorithm to Estimate Mean Traffic Speed Using Uncalibrated Camerasâ€,IEEE Transactions on Intelligent Transportation Systems, Vol. 1, No. 2, pp. 98-107, 2000.
Mario Bellino, Frederic Holzmann, Sascha Kolski, Yuri Lopez de Meneses and Jacques Jacot, “Calibration of an Embedded Camera for Driver- Assistant Systemsâ€, Proceedings of IEEE Conference on Intelligent Transportation Systems, pp. 354-359, 2005.
Wen Wu, Xilin Chen and Jie Yang, “Incremental Detection of Text on Road Signs from Video with Application to a Driving Assistant Systemâ€, Proceedings of 12th Annual ACM International Conference on Multimedia, pp. 852-859, 2004.
Joel C. McCall and Mohan M. Trivedi, “Performance Evaluation of a Vision Based Lane Tracker Designed for Driver Assistance Systemsâ€, Proceedings of IEEE Intelligent Vehicles Symposium, 2005
B. Lamprecht and S. Fuchs, “Computer Vision and Artificial Intelligence On-Roadâ€, OGAI Journal, Vol. 25 No. 3, pp. 19-23, 2006.
Mohammad Osiur Rahman, Fouzia Asharf Mousumi, Edgar Scavino, Aini Hussain and Hassan Basri, “Real Time Road Sign Recognition System Using Artificial Neural Networks for Bengali Textual Information Boxâ€, European Journal of Scientific Research, Vol. 25, No. 3, pp. 478-487, 2009.
Fabien Moutarde and Alexandre Bargeton, Anne Herbin and Lowik Chanussot, Modular Traffic Signs Recognition Applied to On-Vehicle Real Time Visual Detection of American and European Speed Limit Signs, Robotics Laboratory.
Marcin L. Eichner, Toby P. Breckon, “Integrated Speed Limit Detection and Recognition from Real- Time Videoâ€, Proceedings of IEEE Intelligent Vehicles Symposium, 2008.
R. Risack, P. Klausmann, W. Kruger and W. Enkelmann, “Robust Lane Recognition Embedded in a Real-time Driver Assistance Systemâ€, Proceedings of IEEE International Conference on Intelligent Vehicles, Vol. 1, pp. 35-40, 1998.
Ruyi Jiang, Reinhard Klette, Shigang Wang and Tobi Vaudrey, “Low-level Image Processing for Lane Detection and Trackingâ€, Proceedings of ArtsIT 2009, LNICST Vol. 30, pp. 190-197, 2009.
Yong Zhou, Rong Xu, Xianofeng Hu and Qingtai Ye, “A Robust Lane Detection and Tracking Method Based on Computer Visionâ€, Measurement Science and Technology, Vol. 17, 736-745, 2006.
Yue Wang, Eam Khwang Teoh and Dinggang Shen, “Lane Detection and Tracking using B-Snakeâ€, Image and Vision Computing, Vol. 22, pp. 269- 280, 2004.
SIFT Tutorials, http://www.vlfeat.org/ Accessed on 26.02.2010.
M. A. Fischler and R. C. Bolles, Random Sample Consensus: “A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartographyâ€, Communications of the ACM, Vol. 24, No. 6, pp. 381-395, 1981.
Simulink, Image and Video Processing Blockset Tutorials and References http://www.Mathworks.com/ access/ helpdesk/help/t oolbox/images, Accessed on 26.02.2010.
Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, 3rd edition, Pearson, 2008.
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