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Development of an Improved Geometric Path Tracking Algorithm with Real Time Image Processing Methods

실시간 이미지 처리 방법을 이용한 개선된 차선 인식 경로 추종 알고리즘 개발

  • 서은빈 (대구경북과학기술원(DGIST) 융복합대학) ;
  • 이승기 (대구경북과학기술원(DGIST) 융복합대학) ;
  • 여호영 (대구경북과학기술원(DGIST) 융복합대학) ;
  • 신관준 (대구경북과학기술원(DGIST) 융복합대학) ;
  • 최경호 (대구경북과학기술원(DGIST) 융합전공) ;
  • 임용섭 (대구경북과학기술원(DGIST) 로봇공학전공)
  • Received : 2021.02.02
  • Accepted : 2021.03.18
  • Published : 2021.06.30

Abstract

In this study, improved path tracking control algorithm based on pure pursuit algorithm is newly proposed by using improved lane detection algorithm through real time post-processing with interpolation methodology. Since the original pure pursuit works well only at speeds below 20 km/h, the look-ahead distance is implemented as a sigmoid function to work well at an average speed of 45 km/h to improve tracking performance. In addition, a smoothing filter was added to reduce the steering angle vibration of the original algorithm, and the stability of the steering angle was improved. The post-processing algorithm presented has implemented more robust lane recognition system using real-time pre/post processing method with deep learning and estimated interpolation. Real time processing is more cost-effective than the method using lots of computing resources and building abundant datasets for improving the performance of deep learning networks. Therefore, this paper also presents improved lane detection performance by using the final results with naive computer vision codes and pre/post processing. Firstly, the pre-processing was newly designed for real-time processing and robust recognition performance of augmentation. Secondly, the post-processing was designed to detect lanes by receiving the segmentation results based on the estimated interpolation in consideration of the properties of the continuous lanes. Consequently, experimental results by utilizing driving guidance line information from processing parts show that the improved lane detection algorithm is effective to minimize the lateral offset error in the diverse maneuvering roads.

Keywords

Acknowledgement

본 연구는 과학기술정보통신부에서 지원하는 DGIST 기관고유사업에 의해 수행되었다(21-BRP-08 & 21-BRP-09).

References

  1. Park, M., Lee, S., and Han, W., 2014, "Development of lateral control system for autonomous vehicle based on adaptive pure pursuit algorithm", 2014 14th International Conference on Control, Automation and Systems (ICCAS 2014), Seoul, pp. 1443~1447.
  2. Wallace, R. S., Stentz, A., Thorpe, C. E., Moravec, H. P., Whittaker, W., and Kanade, T., 1985, "First Results in Robot Road-Following", International Joint Conference on Artificial Intelligence (IJCAI), pp. 1089~1095.
  3. Hoffmann, G. M., Tomlin, C. J., Montemerlo, M., and Thrun, S., 2007, "Autonomous automobile trajectory tracking for off-road driving: Controller design, experimental validation and racing", 2007 American Control Conference, pp. 2296~2301.
  4. Wit, J., Crane III, C. D., and Armstrong, D., 2004, "Autonomous ground vehicle path tracking", Journal of Robotic Systems, Vol. 21, No. 8, pp. 439~449. https://doi.org/10.1002/rob.20031
  5. Martinez, J. L., Morales, J., Mandow, A., and Garcia-Cerezo, A., 2008, "Steering limitations for a vehicle pulling passive trailers", IEEE Transactions on Control Systems Technology, Vol. 16, No. 4, pp. 809~818. https://doi.org/10.1109/TCST.2007.916293
  6. Wang, W. J., Hsu, T. M., and Wu, T. S., 2017, "The improved pure pursuit algorithm for autonomous driving advanced system", 2017 IEEE 10th International Workshop on Computational Intelligence and Applications (IWCIA), pp. 33~38.
  7. Wang, R., Li, Y., Fan, J., Wang, T., and Chen, X. 2020, "A Novel Pure Pursuit Algorithm for Autonomous Vehicles Based on Salp Swarm Algorithm and Velocity Controller", IEEE Access, 8, pp. 166525~166540. https://doi.org/10.1109/access.2020.3023071
  8. Hou, Y., Ma, Z., Liu, C., and Loy, C. C., 2019, "Learning lightweight lane detection cnns by self attention distillation", In Proceedings of the IEEE International Conference on Computer Vision, pp. 1013~1021.
  9. Gasca, M., and Sauer, T., 2000, "Polynomial interpolation in several variables", Advances in Computational Mathematics, Vol. 12, No. 4, p. 377. https://doi.org/10.1023/A:1018981505752