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Development and Evaluation of a System to Determine Position and Attitudes using In-Vehivle Seonsors

차량 내부 센서를 이용한 위치·자세 결정 시스템 구축 및 평가

  • Received : 2013.10.29
  • Accepted : 2013.12.30
  • Published : 2013.12.31

Abstract

GPS based car navigation systems show significant problems in such environment as a tunnel, a road surrounded by high buildings. In this study, we thus propose a method to determine positions and attitudes using only in-vehicle sensory data without a GPS. To check the feasibility of this method, we constructed a system to acquire in-vehicle sensory data and reference data simultaneously. We acquired test data using this system, estimated the trajectory based on the proposed method and evaluated the accuracy of both the sensory data and the trajectory. The speed and angular velocities provided by the in-vehicle sensors include 1.1 km/h and 0.8 deg/s RMS errors, respectively. The estimated trajectory using these data shows 20.8 m RMS errors for a 15 minute drive. In future, if we further combine additional sensors such as a camera and a GPS, we can achieve a high accurate navigation system at a low cost without an expensive high-grade external IMU.

GPS 기반 차량 내비게이션은 신호 수신이 어려운 터널과 빌딩 숲 같은 곳에서 위치 정확도가 현저히 떨어진다. 이에 본 연구는 GPS 없이 차량의 내부 센서 데이터만을 이용하여 위치 자세를 결정하는 방법을 제안한다. 제안한 방법의 실현 가능성 확인하기 위하여 내부 센서 데이터와 기준 데이터를 동시에 취득할 수 있는 시스템을 구축하였다. 취득된 데이터와 이를 이용하여 제안된 방법으로 추정한 경로에 대한 정확도 평가를 수행하였다. 내부센서로 측정된 속력과 각속도는 각각 1.1 km/h와 0.8 deg/s정도의 RMS 오차를 보였고, 이를 이용하여 추정한 경로는 약 15분 정도 주행했을 때 20.8 m의 RMS 오차를 보였다. 향후 카메라와 GPS 등의 추가센서와 융합하면, 고가의 고정밀 외부 IMU가 없어도 높은 정확도의 저가 내비게이션으로 활용될 수 있을 것으로 판단된다.

Keywords

References

  1. Andrey, S; Donald, V. 2010, Integration of GPS and vision measurements for navigation in GPS challenged environments, Paper presented at the Position Location and Navigation Symposium, 2010 IEEE/ION, Indian Wells, California, May 3-6.
  2. Applanix. 2012, POSLV Specifications, Applanix, Accessed July 20. http://www.applanix.com/media/downloads/products/specs/poslv_specifications12032012.pdf.
  3. Bayoud, F. A. 2005, Vision-aided inertial navigation using a geomatics approach, Paper presented at the 18th International Technical Meeting of the Satellite Division, Long Beach, September.
  4. Byun, Y. S; Mok, J. K; Kim, Y. C. 2011, Kinematic model of 4ws vehicle for dead-reckoning, Paper presented at the 2011 Conference on Information and Control Systems, Gyeongju, October 20-22.
  5. Chang, H; Georgy, J; El-Sheimy, N. 2013, Monitoring Cycling Performance Using a Low Cost Multi-Sensors Navigation Solution, Paper presented at the 8th The International Symposium on Mobile Mapping Technology, Tainan, May 1-3.
  6. Dissanayake, G; Sukkarieh, S; Nebot, E. 2001, The aiding of a low-cost strapdown inertial measurement unit using vehicle model constraints for land vehicle applications, Robotics and Automation, IEEE Transactions on, 17(5):731-747. https://doi.org/10.1109/70.964672
  7. El-Sheimy, N; Nassar, S; Shin, E. H; Niu, X. 2006, Analysis of various kalman filter algorithms using different inertial navigation systems integrated with the global positioning system, Canadian Aeronautics and Space Journal, 52(2):59-67. https://doi.org/10.5589/q06-008
  8. Hasan, A. M; Samsudin, K; Ramli, A. R; Azmir, R. S. 2010, Comparative study on wavelet filter and thresholding selection for GPS/INS data fusion. International Journal of Wavelets, Multiresolution Information Processing, 8(3):457-473. https://doi.org/10.1142/S0219691310003572
  9. Jeon, H. 2011, Trend of LBS market and industry, National IT Industry Promotion Agency, January 19.
  10. Jo, K. C; Chu, K. Y; Lee, K. Y; Sunwoo, M. H. 2010, Integration of multiple vehicle models with an IMM filter for vehicle localization, Paper presented at the 2010 IEEE Intelligent Vehicles Symposium, San Diego, California, June 21-24.
  11. Jung, H. J; Lee, D. H; Kim, S. K; Kim, C. S; Huh, K. S. 2012, Development of Vehicle Position Estimator using Dead Reckoning Algorithm, Paper presented at the KSAE 2012 Annual Conference and Exhibition, Goyang, November 21-24.
  12. Kim, M. W; Lim, J. H; Park, J. D; Kim, H. S; Lee, H. K. 2012, Vehicle Displacement Estimation By GPS and Vision Sensor. The Journal of Korea Navigation Institute, 16(3):417-425. https://doi.org/10.12673/jkoni.2012.16.3.417
  13. Kim, S. B; Bazin, J. C; Lee, H. K; Choi, K. H; Park, S. Y. 2011, Ground vehicle navigation in harsh urban conditions by integration inertial navigation system, global positioning system, odometer and vision data. Radar, Sonar&Navigation, IET, 5(8):814-823. https://doi.org/10.1049/iet-rsn.2011.0100
  14. Kim, S. H; Lee, S. I; Lee, K. S; Cho, S. I; Park J. H; Choi, K. H. 2009, Understanding Lane Number for Video-based Car Navigation System. Journal of Korea Spatial Information System Society, 11(1):104-111.
  15. Kim, Y. K; Lee, K. S; Cho, S. I; Park, J. H; Choi, K. H. 2008, Real-time Identification of Traffic Light and Road Sign for the Next Generation Video-Based Navigation System. Journal of Korea Spatial Information System Society, 10(2):13-24.
  16. Langel S. E; Samer M; Chan F. C; Pervan B. S. 2010, Tightly coupled GPS/INS integration for differential carrier phase navigation systems using decentralized estimation, Paper presented at the Position Location and Navigation Symposium, 2010 IEEE/ION, Palm Springs, California, May 3-6.
  17. Park, K. C; Chung, H. Y; Lee, J. G. 1998, Dead Reckoning Navigation for Autonomous Mobile Robots, Paper presented at the Intelligent Autonomous Vehicle, Madrid, March 25-28.
  18. Retsher, G; Hecht, T; Mok, E. 2013, Location Capabilities and Performance of Smartphones for LBS Navigation Applications, Paper presented at the 8th The International Symposium on Mobile Mapping Technology, Tainan, May 1-3.
  19. Rogers, R. 1997, Land Vehicle Navigation Filtering for a GPS/Dead-Reckoning System, Paper presented at the 1997 National Technical Meeting of the Institude of Navigation, Santa Monica, January 14-16.
  20. Song, J. K; Park, J. S. 2011, Implementation of Access Control System Based on CAN Communication, The Journal of The Korean Institute of Electronic communication Sciences, 6(6):951-956.
  21. Yoo, J. J; Choi, J. H; Sung, K. B; Kim. J. S. 2005, Vehicular image based geographic information system for telematics environments, Paper presented at the 2005 Geoscience and Remote Sensing Symposium, IGARSS '05, IEEE International, Seoul, July 25-29.

Cited by

  1. 차량 내장 센서와 단영상 후방 교차법을 이용한 차량 위치 결정 알고리즘 개발 및 성능 평가 vol.25, pp.2, 2013, https://doi.org/10.7319/kogsis.2017.25.2.021