Journal of the Korean Society of Industry Convergence (한국산업융합학회 논문집)

The Korean Society of Industry Convergence (한국산업융합학회)
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A Study on the Detection Method of Lane Based on Deep Learning for Autonomous Driving

자율주행을 위한 딥러닝 기반의 차선 검출 방법에 관한 연구

  • 박승준 (국민대학교 자동차공학전문대학원 대학원) ;
  • 한상용 (국민대학교 자동차공학전문대학원 대학원) ;
  • 박상배 (폴리텍대학교 청주캠퍼스) ;
  • 김정하 (국민대학교 자동차IT융합학과)
  • Received : 2020.10.29
  • Accepted : 2020.11.23
  • Published : 2020.12.31
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Abstract

This study used the Deep Learning models used in previous studies, we selected the basic model. The selected model was selected as ZFNet among ZFNet, Googlenet and ResNet, and the object was detected using a ZFNet based FRCNN. In order to reduce the detection error rate of FRCNN, location of four types of objects detected inside the image was designed by SVM classifier and location-based filtering was applied. As simulation results, it showed similar performance to the lane marking classification method with conventional 경계 detection, with an average accuracy of about 88.8%. In addition, studies using the Linear-parabolic Model showed a processing speed of 165.65ms with a minimum resolution of 600 × 800, but in this study, the resolution was treated at about 33ms with an input resolution image of 1280 × 960, so it was possible to classify lane marking at a faster rate than the previous study by CNN-based End to End method.

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References

  1. Prajakta R. Yelwande and Prof. Aditi Jahagirdar, "Real-time Robust 차선 검출 and Warning System using Hough Transform Method", International Journal of Engineering Research & Technology (IJERT), vol. 8, Issue 08, pp.385-392, August 2019.
  2. Amartansh Dubey and K. M. Bhurchandi, "Robust and real time detection of curvy lanes (curves) with desired slopes for driving assistance and autonomous vehicles", ResearchGate, January 2015, DOI: 10.5121/csit.2015.50111
  3. Huifeng Wang, Yunfei Wang, Xiangmo Zhao, Guiping Wang, He Huang and Jiajia Zhang, "Lane Detection of Curving Road for Structural Highway with Straight-Curve Model on Vision", IEEE Transactions on Vehicular Technology, vol. 68, no: 6, pp. 5321-5330, June 2019. https://doi.org/10.1109/TVT.2019.2913187
  4. Dave Gershgorn, "The inside story of how AI got good enough to dominate Silicon Valley". Quartz. Retrieved 5 October 2018.
  5. Krizhevsky Alex, Sutskever Ilya, Hinton, Geoffrey E., "ImageNet classification with deep convolutional neural networks", Twenty-sixth Conference on Neural Information Processing Systems, pp.1?9. doi:10.1145/3065386. ISSN 0001-0782.
  6. Sang Bae Park, Gyehyun Kim, Hyun Jae Baek, Jong Hee Han and Joon Ho Kim, "Remote Pulse Rate Measurement from Near-Infrared Videos", IEEE Signal Processing Letters, vol.25, no.8, pp.1271-1275, August 2018. https://doi.org/10.1109/LSP.2018.2842639