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Small size vehicle application with lane tracking capability via CHEVP algorithm

Yıl 2020, , 76 - 85, 08.06.2020
https://doi.org/10.18245/ijaet.639025

Öz

Humans are living things that make mistakes. Failure of drivers while driving can cause life, cost, organ loss. Some accidents may remain traumatic in people's memory and adversely affect their future lives. Traffic rules have been developed to prevent such accidents. Traffic is formally organized in many jurisdictions, with marked lanes, junctions, intersections, interchanges, traffic signals, or signs. Rules of the road and driving etiquette are the general practices and procedures that road users are required to follow. Thanks to these guides placed on the roads, drivers can go on the road in harmony. Despite all these precautions, there are many traffic accidents caused by the driver's carelessness, sleeplessness and tiredness. In today's technology, it is possible to utilize methods of processing images from cameras located in the vehicle to minimize driver-induced accidents. In this study, a prototype system was established in order to use the technologies used in autonomous vehicles and to teach these technologies. Camera and computer are placed on a battery-powered vehicle. Using the OpenCV library, lane tracking is performed successfully using the Canny/Hough Estimation of Vanishing Points (CHEVP) method. The developed system is suitable for the use and development of image processing technologies that are used in autonomous vehicle technology. The system is tested in real-time on a designed runway. From the real-time experimental studies, high-performance results were obtained.

Destekleyen Kurum

Karabük University, Scientific Research Projects

Proje Numarası

KBÜ-BAP-18-YL-163

Teşekkür

Karabük University supported this study within the scope of Scientific Research Projects (KBÜ-BAP-18-YL-163). We would like to thank KBÜELAR electric vehicle and ROBOTAXI team for their contributions.

Kaynakça

  • Definition of: self-driving car”, 2019. [Online]. Available: https://www.pcmag.com/encyclopedia/term/65738/self-driving-car. [Accessed: 03-Sep-2019].
  • J. Berrada and F. Leurent, “Modeling Transportation Systems involving Autonomous Vehicles: A State of the Art”, Transp. Res. Procedia, 27, 215–221, 2017.
  • P. Davidson and A. Spinoulas, “Autonomous vehicles: what could this mean for the future of transport”, in Australian Institute of Traffic Planning and Management (AITPM) National Conference, Brisbane, Queensland, 2015.
  • K. Kluge and S. Lakshmanan”, A deformable-template approach to lane detection,” in Proceedings of the Intelligent Vehicles’ 95. Symposium, 54–59,1995.
  • S. Lakshmanan and D. Grimmer, “A deformable template approach to detecting straight edges in radar images”, IEEE Trans. Pattern Anal. Mach. Intell., 18: 4, 438–443, 1996.
  • K. Kaliyaperumal, S. Lakshmanan, and K. Kluge “, An algorithm for detecting roads and obstacles in radar images”, IEEE Trans. Veh. Technol., 50:1, 170–182, 2001.
  • D. J. Kang, J. W. Choi, and I. S. Kweon, “Finding and tracking road lanes using” line-snakes”, in Proceedings of Conference on Intelligent Vehicles, 189–194,1996.
  • S.-P. Liou and R. C. Jain, “Road following using vanishing points”, Comput. vision, Graph. image Process., 39:1, 116–130, 1987.
  • S. Lakshmanan and K. C. Kluge, “Lane detection for automotive sensors”, in 1995 International Conference on Acoustics, Speech, and Signal Processing, 5,2955–2958, 1995.
  • Kaske, R. Husson, and D. Wolf, “Chi-square fitting of deformable templates for lane boundary detection”, in IAR Annual Meeting, 95,1995.
  • Kaske, D. Wolf, and R. Husson, “Lane boundary detection using statistical criteria”, in International Conference on Quality by Artificial Vision, QCAV9, 28–30, 1997.
  • Y. Wang, E. K. Teoh, and D. Shen, “Lane detection and tracking using B-Snake”, Image Vis. Comput., 22:4, 269–280, 2004.
  • G. C. Verghese, “Estimation with Minimum Mean Square Error”, in ignals, Systems and Inference, 139–160, 2010.
  • P. T. Mandlik and L. Tracking, “A Review on Lane Detection and Tracking Techniques”, 3:5, 37–44, 2016. Y. Wang, D. Shen, and E. K. Teoh, “Lane detection using catmull-rom spline”, in IEEE International Conference on Intelligent Vehicles, 1, 51–57,1998.
  • Y. Wang, D. Shen, E. K. Teoh, and H. Wang, “A Novel Lane Model for Lane Boundary Detection.”, in MVA, 27–30, 1998.
  • Y. Wang, D. Shen, and E. K. Teoh, “Lane detection using spline model”, Pattern Recognit. Lett., 21:8, 677–689, 2000.
  • J. D. Cook, “Three algorithms for converting color to grayscale”, 2009.
  • [Online]. Available: https://www.johndcook.com/blog/2009/08/24/algorithms-convert-color-grayscale/. [Accessed: 10-Dec-2019].
  • S. Irandoust-Pakchin, A. Ayanzadeh, and S. Beikzadeh, “Gaussian Three-Dimensional kernel SVM for Edge Detection Applications”, arXiv Prepr. arXiv1710.01260, 2017.
  • L. G. Shapiro and G. C. Stockman, Computer Vision. Prentice Hall, 2001.
  • J. Canny, “A computational approach to edge detection”, IEEE Trans. Pattern Anal. Mach. Intell., 6, 679–698, 1986.
  • J. Illingworth and J. Kittler, “A survey of the Hough transform”, Comput. vision, Graph. image Process., 44:1, 87–116, 1988.
  • M. Hazewinkel, “Theory of errors.”, Encyclopedia of mathematics, 62, 2001.
Yıl 2020, , 76 - 85, 08.06.2020
https://doi.org/10.18245/ijaet.639025

Öz

Proje Numarası

KBÜ-BAP-18-YL-163

Kaynakça

  • Definition of: self-driving car”, 2019. [Online]. Available: https://www.pcmag.com/encyclopedia/term/65738/self-driving-car. [Accessed: 03-Sep-2019].
  • J. Berrada and F. Leurent, “Modeling Transportation Systems involving Autonomous Vehicles: A State of the Art”, Transp. Res. Procedia, 27, 215–221, 2017.
  • P. Davidson and A. Spinoulas, “Autonomous vehicles: what could this mean for the future of transport”, in Australian Institute of Traffic Planning and Management (AITPM) National Conference, Brisbane, Queensland, 2015.
  • K. Kluge and S. Lakshmanan”, A deformable-template approach to lane detection,” in Proceedings of the Intelligent Vehicles’ 95. Symposium, 54–59,1995.
  • S. Lakshmanan and D. Grimmer, “A deformable template approach to detecting straight edges in radar images”, IEEE Trans. Pattern Anal. Mach. Intell., 18: 4, 438–443, 1996.
  • K. Kaliyaperumal, S. Lakshmanan, and K. Kluge “, An algorithm for detecting roads and obstacles in radar images”, IEEE Trans. Veh. Technol., 50:1, 170–182, 2001.
  • D. J. Kang, J. W. Choi, and I. S. Kweon, “Finding and tracking road lanes using” line-snakes”, in Proceedings of Conference on Intelligent Vehicles, 189–194,1996.
  • S.-P. Liou and R. C. Jain, “Road following using vanishing points”, Comput. vision, Graph. image Process., 39:1, 116–130, 1987.
  • S. Lakshmanan and K. C. Kluge, “Lane detection for automotive sensors”, in 1995 International Conference on Acoustics, Speech, and Signal Processing, 5,2955–2958, 1995.
  • Kaske, R. Husson, and D. Wolf, “Chi-square fitting of deformable templates for lane boundary detection”, in IAR Annual Meeting, 95,1995.
  • Kaske, D. Wolf, and R. Husson, “Lane boundary detection using statistical criteria”, in International Conference on Quality by Artificial Vision, QCAV9, 28–30, 1997.
  • Y. Wang, E. K. Teoh, and D. Shen, “Lane detection and tracking using B-Snake”, Image Vis. Comput., 22:4, 269–280, 2004.
  • G. C. Verghese, “Estimation with Minimum Mean Square Error”, in ignals, Systems and Inference, 139–160, 2010.
  • P. T. Mandlik and L. Tracking, “A Review on Lane Detection and Tracking Techniques”, 3:5, 37–44, 2016. Y. Wang, D. Shen, and E. K. Teoh, “Lane detection using catmull-rom spline”, in IEEE International Conference on Intelligent Vehicles, 1, 51–57,1998.
  • Y. Wang, D. Shen, E. K. Teoh, and H. Wang, “A Novel Lane Model for Lane Boundary Detection.”, in MVA, 27–30, 1998.
  • Y. Wang, D. Shen, and E. K. Teoh, “Lane detection using spline model”, Pattern Recognit. Lett., 21:8, 677–689, 2000.
  • J. D. Cook, “Three algorithms for converting color to grayscale”, 2009.
  • [Online]. Available: https://www.johndcook.com/blog/2009/08/24/algorithms-convert-color-grayscale/. [Accessed: 10-Dec-2019].
  • S. Irandoust-Pakchin, A. Ayanzadeh, and S. Beikzadeh, “Gaussian Three-Dimensional kernel SVM for Edge Detection Applications”, arXiv Prepr. arXiv1710.01260, 2017.
  • L. G. Shapiro and G. C. Stockman, Computer Vision. Prentice Hall, 2001.
  • J. Canny, “A computational approach to edge detection”, IEEE Trans. Pattern Anal. Mach. Intell., 6, 679–698, 1986.
  • J. Illingworth and J. Kittler, “A survey of the Hough transform”, Comput. vision, Graph. image Process., 44:1, 87–116, 1988.
  • M. Hazewinkel, “Theory of errors.”, Encyclopedia of mathematics, 62, 2001.
Toplam 23 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Article
Yazarlar

Abdulhamit Sevgi 0000-0003-3567-848X

Emel Soylu 0000-0003-2774-9778

Raif Bayır 0000-0003-3155-8771

Proje Numarası KBÜ-BAP-18-YL-163
Yayımlanma Tarihi 8 Haziran 2020
Gönderilme Tarihi 28 Ekim 2019
Yayımlandığı Sayı Yıl 2020

Kaynak Göster

APA Sevgi, A., Soylu, E., & Bayır, R. (2020). Small size vehicle application with lane tracking capability via CHEVP algorithm. International Journal of Automotive Engineering and Technologies, 9(2), 76-85. https://doi.org/10.18245/ijaet.639025
AMA Sevgi A, Soylu E, Bayır R. Small size vehicle application with lane tracking capability via CHEVP algorithm. International Journal of Automotive Engineering and Technologies. Haziran 2020;9(2):76-85. doi:10.18245/ijaet.639025
Chicago Sevgi, Abdulhamit, Emel Soylu, ve Raif Bayır. “Small Size Vehicle Application With Lane Tracking Capability via CHEVP Algorithm”. International Journal of Automotive Engineering and Technologies 9, sy. 2 (Haziran 2020): 76-85. https://doi.org/10.18245/ijaet.639025.
EndNote Sevgi A, Soylu E, Bayır R (01 Haziran 2020) Small size vehicle application with lane tracking capability via CHEVP algorithm. International Journal of Automotive Engineering and Technologies 9 2 76–85.
IEEE A. Sevgi, E. Soylu, ve R. Bayır, “Small size vehicle application with lane tracking capability via CHEVP algorithm”, International Journal of Automotive Engineering and Technologies, c. 9, sy. 2, ss. 76–85, 2020, doi: 10.18245/ijaet.639025.
ISNAD Sevgi, Abdulhamit vd. “Small Size Vehicle Application With Lane Tracking Capability via CHEVP Algorithm”. International Journal of Automotive Engineering and Technologies 9/2 (Haziran 2020), 76-85. https://doi.org/10.18245/ijaet.639025.
JAMA Sevgi A, Soylu E, Bayır R. Small size vehicle application with lane tracking capability via CHEVP algorithm. International Journal of Automotive Engineering and Technologies. 2020;9:76–85.
MLA Sevgi, Abdulhamit vd. “Small Size Vehicle Application With Lane Tracking Capability via CHEVP Algorithm”. International Journal of Automotive Engineering and Technologies, c. 9, sy. 2, 2020, ss. 76-85, doi:10.18245/ijaet.639025.
Vancouver Sevgi A, Soylu E, Bayır R. Small size vehicle application with lane tracking capability via CHEVP algorithm. International Journal of Automotive Engineering and Technologies. 2020;9(2):76-85.