DOI QR코드

DOI QR Code

MPC based Steering Control using a Probabilistic Prediction of Surrounding Vehicles for Automated Driving

전방향 주변 차량의 확률적 거동 예측을 이용한 모델 예측 제어 기법 기반 자율주행자동차 조향 제어

  • Lee, Jun-Yung (School of Mechanical and Aerospace Engineering, Seoul National University) ;
  • Yi, Kyong-Su (School of Mechanical and Aerospace Engineering, Seoul National University)
  • 이준영 (서울대학교 기계항공공학부) ;
  • 이경수 (서울대학교 기계항공공학부)
  • Received : 2014.11.15
  • Accepted : 2014.12.30
  • Published : 2015.03.01

Abstract

This paper presents a model predictive control (MPC) approach to control the steering angle in an autonomous vehicle. In designing a highly automated driving control algorithm, one of the research issues is to cope with probable risky situations for enhancement of safety. While human drivers maneuver the vehicle, they determine the appropriate steering angle and acceleration based on the predictable trajectories of surrounding vehicles. Likewise, it is required that the automated driving control algorithm should determine the desired steering angle and acceleration with the consideration of not only the current states of surrounding vehicles but also their predictable behaviors. Then, in order to guarantee safety to the possible change of traffic situation surrounding the subject vehicle during a finite time-horizon, we define a safe driving envelope with the consideration of probable risky behaviors among the predicted probable behaviors of surrounding vehicles over a finite prediction horizon. For the control of the vehicle while satisfying the safe driving envelope and system constraints over a finite prediction horizon, a MPC approach is used in this research. At each time step, MPC based controller computes the desired steering angle to keep the subject vehicle in the safe driving envelope over a finite prediction horizon. Simulation and experimental tests show the effectiveness of the proposed algorithm.

Keywords

References

  1. S. Huang, W. Ren, and S. Chan, "Design and performance evaluation of mixed manual and automated control traffic," IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol. 30, no. 6, pp. 661-673, 2000.
  2. S. Moon and K. Yi, "Human driving data-based design of a vehicle adaptive cruise control algorithm," Vehicle System Dynamics, vol. 46, no. 8, pp. 661-690, Aug. 2008. https://doi.org/10.1080/00423110701576130
  3. S. Moon, I. Moon, and K. Yi, "Design, tuning, and evaluation of a full-range adaptive cruise control system with collision avoidance," Control Engineering Practice, vol. 17, no. 4, pp. 442-455, 2009. https://doi.org/10.1016/j.conengprac.2008.09.006
  4. T. Pilluti, G. Ulsoy, and D. Hrovat, "Vehicle steering intervention through differential braking," Proc. of the American Control Conference, Seattle Washington, USA, vol. 3, pp. 1667-1671, Jun. 1995.
  5. N. Minoiu, M. Netto, S. Mammar, and B. Lusetti, "Driver steering assistance for lane departure avoidance," Control Engineering Practice, vol. 17, pp. 642-651, 2009. https://doi.org/10.1016/j.conengprac.2008.10.012
  6. J. Lee, J. Choi, K. Yi, M. Shin, and B. Ko, "Lane-keeping assistance control algorithm using differential braking to prevent unintended lane departures," Control Engineering Practice, vol. 23, pp. 1-13, 2014. https://doi.org/10.1016/j.conengprac.2013.10.008
  7. J. Pohl, W. Birk, and L. Westervall, "A driver-distraction based lane keeping assistance system," Proc. of the Institution of Mechanical Engineers. Part I:J.Systems and Control Engineering, vol. 221, pp. 541-552, 2007. https://doi.org/10.1243/09596518JSCE218
  8. J. Yoon, W. Cho, B. Koo, and K. Yi, "Unified chassis control for rollover prevention and lateral stability," IEEE Transactions on Vehicular Technology, vol. 58, no. 2, pp. 596-609, Feb. 2009. https://doi.org/10.1109/TVT.2008.927724
  9. W. Cho, J. Choi, C. Kim, S. Choi, and K. Yi, "Unified chassis control for the improvement of agility, maneuverability, and lateral stability," IEEE Transactions on Vehicular Technology, vol. 61, no. 3, Mar. 2012.
  10. Y. Kou, H. Peng, and D. Jung, "Development of an integrated chassis control system for worst case studies," Proc. of AVEC, pp. 47-52, 2006.
  11. http://www.extremetech.com/extreme/132147-ford-self-drivingcars-2017
  12. http://www.digitaltrends.com/cars/cadillac-super-cruise/
  13. http://pressroom.toyota.com/releases/toyota+advanced+driving+support+system+technology.htm
  14. B. Kim and K. Yi, "Probabilistic states prediction algorithm using multi-sensor fusion and application to smart cruise control systems," IEEE Intelligent Vehicles Symposium, Gold Coast, Australia, pp. 888-895, Jun. 2013.
  15. M. Althoff, O. Stursberg, and M. Buss, "Model-based probabilistic collision detection in autonomous driving," IEEE Transaction on Intelligent Transportation System, vol. 10, no. 2, pp. 299-310, 2009. https://doi.org/10.1109/TITS.2009.2018966
  16. D. Ferguson and D. Dolgov, "Modifying behavior of autonomous vehicle based on predicted behavior of other vehicles," Pat. no. 20130261872A1, United States, 2013.
  17. A. Gray, M. Ali, Y. Gao, J. Hedrick, and F. Borrelli, "Semiautonomous vehicle control for road departure and obstacle avoidance," IFAC Control of Transportation Systems, 2012.
  18. A. Gray, Y. Gao, J. Hedrick, and F. Borrelli, "Robust predictive control for semi-autonomous vehicles with an uncertain driver model," IEEE Intelligent Vehicles Symposium, Gold Coast, Australia, pp. 208-213, 2013.
  19. P. Falcone, F. Borrelli, J. Asgari, H. Tseng, and D. Hrovat, "Predictive active steering control for autonomous vehicle systems," IEEE Transactions on Control Systems Technology, vol. 17, no. 5, pp. 1105-1118, 2009. https://doi.org/10.1109/TCST.2008.2012116
  20. P. Falcone, F. Borrelli, J. Asgari, H. Tseng, and D. Hrovat, "A model predictive control approach for combined braking and steering in autonomous vehicles," Presented at the 15th Med. Conf. Control & Automation, Athens, Greece, pp. 1-6, Jun. 2007.
  21. S. Erlien, S. Fujita, and J. Gerdes, "Safe driving envelopes for shared control of ground vehicles," in 7th IFAC Symposium Advances in Automotive Control, Tokyo, Japan, 2013.
  22. S. Erlien, J. Funke, and J. Gerdes, "Incorporating non-linear tire dynamics into a convex approach to shared steering control," American Control Conference, Portland Oregon, USA, pp. 3468-3473, 2014.
  23. J. Yeu, W. Kim, J. Im, D. Lee, and G. Jee, "Obstacle parameter modeling for model predictive control of the unmanned vehicle," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 18, no. 12, pp. 1132-1138, Dec. 2012. https://doi.org/10.5302/J.ICROS.2012.18.12.1132
  24. D. Zhang, K. Li, and J. Wang, "A curving ACC system with coordination control of longitudinal car-following and lateral stability," Vehicle System Dynamics, vol. 50, no. 7, Mar. 2012.
  25. T. Lee, K. Yi, and C. Jeong, "Integrated stochastic driver model for evaluation of the vehicle active safety systems," Fast-zero 2011, Tokyo, Japan, 2011.
  26. B. Vanholme, D. Gruyer, B. Lusetti, S. Glaser, and S. Mammar, "Highly automated driving on highways based on legal safety," IEEE Transactions on Intelligent Transportation System, vol. 14, no. 1, pp. 333-347, Mar. 2013. https://doi.org/10.1109/TITS.2012.2225104
  27. J. Mattingley and S. Boyd, "CVXGEN: a code generator for embedded convex optimization," Optimization and Engineering, vol. 13, no. 1, pp. 1-27, Mar. 2012. https://doi.org/10.1007/s11081-011-9176-9
  28. R. Rajamani, Vehicle Dynamics and Control, New York: Springer-Verlag, 2005.
  29. G. Song, and J. Lee, "Path planning for autonomous navigation of a driverless ground vehicle based on waypoints," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 20, no. 2, pp. 211-217, Feb. 2014. https://doi.org/10.5302/J.ICROS.2014.13.1961
  30. G. Jin, "Development of a traversability map for safe navigation of autonomous mobile robots," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 20, no. 4, pp. 449-455, Apr. 2014. https://doi.org/10.5302/J.ICROS.2014.13.1967