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On-Board Lane Detection System for Intelligent Vehicle Based on Monocular Vision

Open Access
|Dec 2012

References

  1. Liu Yuan, Wang Yuhao, Chen Siyue. “A hybrid MAC mechanism for multiple load intelligent vehicle transportation network”, International Journal on Smart Sensing and Intelligent Systems, 2011,Vol. 4, no. 4, pp. 662-674.10.21307/ijssis-2017-461
  2. A Broggi, S Berte. “A Vision Based Road Detection in Automotive Systems: A Real Time Expectation Driven Approach”. Journal of Artificial Intelligence Research, 1995, no. 3: 325348.10.1613/jair.185
  3. J Goldbeck, B Huertgen, S Ernst, L Kelch. “Lane following combining vision and DGPS”. Image and Vision Computing, 2000, Vol. 18, no. 5, 425-433.10.1016/S0262-8856(99)00037-2
  4. Chen M, Jochem T, Pomerlean D. “Aurora: a vision-based roadway departure system”. Proc. IEEE Conf. Intell. Robots and Systems, 1995, pp. 243-248.
  5. Kluge K, Lakshmanan S. “A deformable-template approach to lane detection”. Proc. IEEE Intell. Vehicle Symp, 1995, pp. 54-59
  6. Bertozzi M., Broggi A. “Gold: a parallel real-time stereo vision system for generics obstacle and lane detection”, IEEE Trans. Image Process, 1998. Vol. 7, no. 1, pp. 62 – 81.10.1109/83.650851
  7. Kreucher C, Lakshmannan S. “Lana: a lane extraction algorithm that uses frequency domain features”. IEEE Trans. Robot. Autom. 1999, Vol. 15, no.2, pp. 343-350.
  8. Wang Y., Teoh E.K, Shen D. “Lane detection using B-snake”.Int. Conf. Information Intelligent and Systems, Bethesda, MD, USA, 1999, pp. 438-443.
  9. Wang Y., Shen D, Teoh E.K. “Lane detection using spline model”, Pattern Recognit. Lett., 2000, Vol. 21, no. 8, pp. 677-689.10.1016/S0167-8655(00)00021-0
  10. Yim Y.U., Oh S.Y. “Three-feature based automatic lane detection algorithm (TFALDA) for autonomous driving”, IEEE Trans. Intell. Transp. Syst, 2003, Vol. 4 , no. 4,pp. 219-225.10.1109/TITS.2003.821339
  11. Mccall J.C, Trivedi M.M. “Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation”, IEEE Trans. Intell. Transp. Syst., 2006, Vol. 7, no. 1, pp. 20-37.10.1109/TITS.2006.869595
  12. Crisman J.D, Thorpe C.E. “SCARF: a color vision system that tracks roads and intersections”, IEEE Trans. Robot. Autom. , 1993, Vol. 9, no. 1, pp. 49-58.10.1109/70.210794
  13. Rasmussen C. “Grouping dominant orientations for ill-structured road following”. Proc. IEEE Comp. Soc. Conf. Computer Vision and Pattern Recognition, July 2004, pp. 470-477.
  14. Gao Q, Luo Q, Moli S. “Rough set based unstructured road detection through feature learning”. IEEE Int. Conf. Automation and Logistics, August 2007, pp. 101-106.10.1109/ICAL.2007.4338538
  15. Huang J, Kong B, Li B., Zheng F. “A new method of unstructured road detection based on HSV color space and road feature”. Int. Conf. Information Acquisition, July 2007, pp. 596 – 601.10.1109/ICIA.2007.4295802
  16. Liu H.J, Zhang H.F, Lu J.F, Yang J.Y. “Quantitative evaluation and information fusion of road edges for accurate unstructured road tracking”. Int. Conf. ITS Telecommunications, June 2006, pp. 318-321.
  17. Dahlkamp H, Kaehler A, Stavens D, Thrun S, Bradski G. “Self-supervised monocular road detection in desert terrain”. Robotics: Science a nd Systems, Philadelphia, PA, June 2006.10.15607/RSS.2006.II.005
  18. D Pomerleau, T Jochem. “Rapidly Adapting Machine Vision for Automated Vehicle Steering”. Machine Vision. 1996, Vol. 11, no. 2, pp.19-17.
  19. Y Wang, E K Teoh, D Shen. “Lane detection and tracking using B-snake”. Image Visual Compute, 2004, Vol. 22, no. 4, pp.269-280.10.1016/j.imavis.2003.10.003
  20. Z W Kim. “Robust Lane Detection and Tracking in Challenging Scenarios”. IEEE Transactions on Intelligent Transportation System, 2008, Vol. 9, no. 1, pp.16-26.10.1109/TITS.2007.908582
  21. Kun Qian, Xudong Ma, Xian Zhong Dai, et al. “Spatial-temporal Collaborative Sequential Monte Carlo for Mobile Robot Localization in Distributed Intelligent Environments”. International Journal on Smart Sensing and Intelligent Systems, 2012, Vol. 5, no. 2, pp. 295314.10.21307/ijssis-2017-482
  22. Cretu, A.-M.; Payeur, P. Biologically-inspired visual attention features for a vehicle classification task. International Journal on Smart Sensing and Intelligent Systems, 2011,Vol. 4, no. 3, pp. 402-423.10.21307/ijssis-2017-447
  23. Shen Huan,Li Shunming, Miao Xiaodong, et al. “Intelligent Vehicles Oriented Lane Detection Approach under Bad Road Scene”. IEEE the Ninth International Conference on Computer and Information Technology. Xiamen, China, 2009, pp.177-182.10.1109/CIT.2009.25
  24. S. S. Huang, C. J. Chen, P. Y. Hsiao, and L. C. Fu, “On-Board Vision System for Lane Recognition and Front-Vehicle Detection to Enhance Driver’s Awareness”, IEEE International Conference on Robotics and Automation, 2004, 2456-2461.
  25. Z. Zhang. “A Flexible New Technique for Camera Calibration”. Transactions on Pattern Analysis and Machine Intelligence, 2000, Vol. 19, no. 11, pp.1330-1334.10.1109/34.888718
  26. Yingying Huang, Ross McMurran. “Development of an automated testing system for vehicle infotainment system”. Advanced Manufacturing Technology. 2010. Vol. 51, no. 14, pp.233246.
Language: English
Page range: 957 - 972
Submitted on: Aug 15, 2012
Accepted on: Sep 22, 2012
Published on: Dec 1, 2012
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year

© 2012 Xiaodong Miao, Shunming Li, Huan Shen, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.