Journal of Auto-vehicle Safety Association (자동차안전학회지)

Korean Auto-vehicle Safety Association (한국자동차안전학회)
권호 표지
DOI QR코드

DOI QR Code

A Development of the Autonomous Driving System based on a Precise Digital Map

정밀 지도에 기반한 자율 주행 시스템 개발

  • Received : 2017.04.21
  • Accepted : 2017.06.27
  • Published : 2017.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

An autonomous driving system based on a precise digital map is developed. The system is implemented to the Hyundai's Tucsan fuel cell car, which has a camera, smart cruise control (SCC) and Blind spot detection (BSD) radars, 4-Layer LiDARs, and a standard GPS module. The precise digital map has various information such as lanes, speed bumps, crosswalks and land marks, etc. They can be distinguished as lane-level. The system fuses sensed data around the vehicle for localization and estimates the vehicle's location in the precise map. Objects around the vehicle are detected by the sensor fusion system. Collision threat assessment is performed by detecting dangerous vehicles on the precise map. When an obstacle is on the driving path, the system estimates time to collision and slow down the speed. The vehicle has driven autonomously in the Hyundai-Kia Namyang Research Center.

Keywords

References

  1. J. Levinson, J. Askeland, J. Becker, J. Dolson, D. Held, S. Kammel, J. Z. Kolter, D. Langer, O. Pink, V. Pratt, M. Sokolsky, G. Stanek, D. Stavens, A. Teichman, M. Werling, and S. Thrun, 2011, "Toward Fully Autonomous Driving: Systems and Algorithms," IEEE Intelligent Vehicles Symposium, pp. 163-168.
  2. J. Wei, J. M. Snider, J. Kim, J. M. Dolan, R. Rajkumar and B. Litkouhi, 2013, "Toward a Viable Autonomous Driving Research Platform," IEEE Intelligent Vehicles Symposium, pp. 763-770.
  3. A. U. Peker, O. Tosun, and T. Acarman, 2011, "Particle Filter Vehicle Localization and Map-Matching Using Map Topology," IEEE Intelligent Vehicles Symposium, pp. 248-253.
  4. C. Mertz, L. E. Navarro-Serment, R. MacLachlan, P. Rybski, A. Steinfeld, A. Suppe, C. Urmson, N. Vandapel, M. Hebert, C. Thorpe, D. Duggins, and J. Gowdy, 2013, "Moving Object Detection with Laser Scanners," Journal of Field Robotics, Vol. 30, No. 1, pp. 17-43. https://doi.org/10.1002/rob.21430
  5. S. Blackman, and R. Popoli, 1999, Design and Analysis of Modern Tracking Systems, Artech House.
  6. E. Mazor, A. Averbuch, Y. Bar-Shalom, and J. Dayan, "Interacting Multiple Model Methods in Target Tracking: A Survey," 1999, IEEE Transactions on aerospace and electronic systems, Vol. 34, No. 1, pp. 103-123.
  7. N. Kaempchen, K. Weiss, M. Schaefer, K. C. J. Dietmayer, 2004, "IMM Object Tracking for High Dynamic Driving Maneuvers," IEEE Intelligent Vehicles Symposium, pp. 825-830.
  8. N. Dalal and B. Triggs, 2005, "Histograms of Oriented Gradients for Human Detection," IEEE Computer Vision and Pattern Recognition, pp. 886-893.
  9. C. M. Bishop, 2006, Pattern Recognition and Machine Learning, Springer.
  10. J. M. Snider, 2009, Automatic Steering Methods for Autonomous Automobile Path Tracking, Carnegie Mellon University.