디지털융복합연구 (Journal of Digital Convergence)

  • 제13권1호
  • /
  • Pages.297-304
  • /
  • 2015
  • /
  • 2713-6434(pISSN)
  • /
  • 2713-6442(eISSN)
한국디지털정책학회 (The Society of Digital Policy and Management)
권호 표지
DOI QR코드

DOI QR Code

PRT 차량을 위한 자기표지 기반 무인 자율주행 시스템

Magnetic Markers-based Autonomous Navigation System for a Personal Rapid Transit (PRT) Vehicle

  • 변윤섭 (한국철도기술연구원 신교통연구본부 미래교통시스템연구실) ;
  • 엄주환 (한국철도기술연구원 신교통연구본부 미래교통시스템연구실) ;
  • 정락교 (한국철도기술연구원 신교통연구본부 미래교통시스템연구실) ;
  • 김백현 (한국철도기술연구원 신교통연구본부 미래교통시스템연구실) ;
  • 강석원 (한국철도기술연구원 신교통연구본부 미래교통시스템연구실)
  • Byun, Yeun-Sub (Future Transportation Systems Research Division, New Transportation Systems Research Center, Korea Railroad Research Institute) ;
  • Um, Ju-Hwan (Future Transportation Systems Research Division, New Transportation Systems Research Center, Korea Railroad Research Institute) ;
  • Jeong, Rag-Gyo (Future Transportation Systems Research Division, New Transportation Systems Research Center, Korea Railroad Research Institute) ;
  • Kim, Baek-Hyun (Future Transportation Systems Research Division, New Transportation Systems Research Center, Korea Railroad Research Institute) ;
  • Kang, Seok-Won (Future Transportation Systems Research Division, New Transportation Systems Research Center, Korea Railroad Research Institute)
  • 투고 : 2014.11.11
  • 심사 : 2015.01.20
  • 발행 : 2015.01.28
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

최근 들어 무인 자율주행 기반의 수요응답형 순환교통(PRT)시스템에 대한 수요가 증가하고 있다. 이에 따라 유형 궤도 및 일반적인 도로에서 운용 가능한 PRT 시스템의 적용이 다양하게 검토되고 있다. 유형 궤도가 없이 일반 도로 상에서 운행되는 무인자동 차량의 경우, 실시간으로 차량의 위치 정보를 계측하는 것은 무인 차량의 자동안내를 위해 매우 중요하다. 위성항법장치(GPS)는 차량의 위치 확인을 위해 상업적으로 적용되어 활용되고 있다. 하지만 터널 또는 빌딩 등의 실내 환경에서 적용될 수 없다. 본 논문에서는 이러한 환경적 제약을 극복할 수 있는 자기표지 기반의 PRT 차량 무인운전 시스템의 구성장치와 제어시스템에서 사용하기 위한 차량의 주행제어 모델을 제시하였다. 또한 차량의 주행중 실시간 위치를 추정하기 위해 개발된 자기검출센서를 제시하였고 차량의 무인운전에 필요한 지령을 생성하기 위한 제어SW와 이를 통한 제어시험 결과를 제시하였다.

Recently, the demand for a PRT(Personal Rapid Transit) system based on autonomous navigation is increasing. Accordingly, the applicability investigations of the PRT system on rail tracks or roadways have been widely studied. In the case of unmanned vehicle operations without physical guideways on roadways, to monitor the position of the vehicle in real time is very important for stable, robust and reliable guidance of an autonomous vehicle. The Global Positioning System (GPS) has been commercially used for vehicle positioning. However, it cannot be applied in environments as tunnels or interiors of buildings. The PRT navigation system based on magnetic markers reference sensing that can overcome these environmental restrictions and the vehicle dynamics model for its H/W configuration are presented in this study. In addition, the design of a control S/W dedicated for unmanned operation of a PRT vehicle and its prototype implementation for experimental validation on a pilot network were successfully achieved.

키워드

참고문헌

  1. J.H. Irving, H. Bernstein, C.L. Olson, and J. Buyan, Fundamentals of Personal Rapid Transit, D.C. Health and Company, Lexington M.A., 1979.
  2. T. Upadhyay, S. Cotterill, and A.W. Deaton, Autonomous GPS/INS Navigation Experiment for Space Transfer Vehicle," IEEE transactions on Aerospace and Electronic Systems, Vol. 29, No. 3, pp. 772-758, 1993. https://doi.org/10.1109/7.220929
  3. B.-M. Jung, I.-J. Yeo, and C.-S. Cho, Autonomous Traveling of Unmanned Golf-Car using GPS and Vision System, Journal of the Korean Society for Precision Engineering, Vol. 26, No. 6, pp. 74-80, 2009.
  4. J.C. Andersen, N.A. Andersen, and O. Ravn, Vision Assisted Laser Scanner Navigation for Autonomous Robots, Experimental Robotics. Springer Berlin Heidelberg, 2008.
  5. Y.-J. Ryoo and Y.-C. Lim, Visual Control of Autonomous Vehicle by Neural Networks using Fuzzy-Supervised Learning, Journal of Electrical Engineering and Information Science, Vol. 2, No. 2, pp. 77-85, 1997.
  6. http://www.2getthere.eu/
  7. Rag-Gyo Jeong, et al., "Development of Technologies for On-demand Circulator Transit System (PRT)," Korea Railroad Research Institute (KRRI) 1st year report, 2012.
  8. S. Se, D. Lowe, and J. Little, "Vision-based mobile robot localization and mapping using scale-invariant features," in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seoul, Korea, pp. 2051-2058. , May. 2001.
  9. D. I. B. Randeniya, S. Sarkar, and M. Gunaratne, "Vision-IMU integration using a slow-frame-rate monocular vision system in an actual roadway setting," IEEE Trans. Intell. Transp. Syst., vol. 11, no. 2, pp. 256-266, Jun. 2010. https://doi.org/10.1109/TITS.2009.2038276
  10. L. Bai and Y. Wang, "A sensor fusion framework using multiple particle filters for video-based navigation," IEEE Trans. Intell. Transp. Syst., vol. 11, no. 2, pp. 348-358, Jun. 2010. https://doi.org/10.1109/TITS.2010.2043431
  11. E. Abbott and D. Powell, "Land-vehicle navigation using GPS," proceedings of the IEEE, vol. 87, Iss.1, pp. 145-162, Jan. 1999.
  12. D. Mc Neil, "Multi-rate sensor fusion for GPS Navigation using Kalman filtering," M. Sc. Report. Virginia Polytechnic Institute., May. 1999.
  13. P. Bonnifait, P. Bouron, P. Crubille, D. Meizel, "Data fusion of four ABS Sensors and GPS for an enhanced localization of car-like vehicles," Proceedings 2001 ICRA, IEEE International Conference on Robotics and Automation, vol. 2, pp. 1597-1602. 2001.
  14. K. Jo,K. Chu, and M. Sunwoo, "Interacting Multiple Filter-Based Sensor Fusion of GPS With In-Vehicle Sensors for Real-Time Vehicle Position," IEEE Trans. Intell. Transp. Syst., vol. 13, no. 1, pp. 329-343, Mar. 2012. https://doi.org/10.1109/TITS.2011.2171033