Skip to main content
SpringerLink
Log in

Experimental Verification of a Drift Controller for Autonomous Vehicle Tracking: a Circular Trajectory Using LQR Method

  • Published:
International Journal of Control, Automation and Systems Aims and scope Submit manuscript

Abstract

This study develops an autonomous vehicle control method that enables it to perform a drift maneuver which is an expert driving technique consisting of sliding the rear wheel intentionally for fast cornering. By developing an autonomous control algorithm for such an agile maneuver, the safety of the future autonomous vehicle on extreme conditions such as slippery road, will be increased. Drift equilibrium states are derived to find the suitable feedforward control input for the scale car to enter the drifting region. In addition, a feedback controller is designed based on the linear quadratic regulator method in order to track the circular trajectory and maintain drift equilibrium states. To validate the performance of the developed control algorithm a 1:10 scale car experimental platform is developed with on-board control and sensor system. The feasibility of the developed method for the autonomous vehicle is confirmed through both simulation and experiments following circular trajectories while maintaining the desired equilibrium states.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. C. Choi and Y. Kang, “Simultaneous braking and steering control method based on nonlinear model predictive control for emergency driving support,” International Journal of Control, Automation, and Systems, vol. 15, no. 1, pp. 345–353, 2017.

    Article  Google Scholar 

  2. L. Etienne, C. A. Lúa, S. D. Gennaro, and J. P. Barbot, “A super-twisting controller for active control of ground vehicles with lateral tire-road friction estimation and CarSim validation,” International Journal of Control, Automation, and Systems, vol. 18, no. 5, pp. 1177–1189, 2020.

    Article  Google Scholar 

  3. B. Song, J. K. Hedrick, and Y. Kang, “Dynamic surface control and its application to lateral vehicle control,” Mathematical Problems in Engineering, vol. 2014, Article ID 693607, 2014.

  4. J. Lee and Y. Kang, “An experimental study of model predictive control method for autonomous vehicles under severe steering and braking maneuver,” Transactions of the Korean Society of Automotive Engineers A, vol. 42, no. 3, pp. 221–230, 2018.

    Article  Google Scholar 

  5. V. Nguyen, Vehicle Handling, Stability, and Bifurcation Analysis for Nonlinear Vehicle Models, Master’s Thesis, University of Maryland, 2005.

  6. M. Abdulrahim, “On the dynamics of automobile drifting,” Proc. of SAE World Congress & Exhibition, SAE Technical Paper, 2006-01-1019, 2006.

  7. C. Voser, R. Y. Hindiyeh, and J. C. Gerdes, “Analysis and control of high sideslip manoeuvres,” Vehicle System Dynamics, vol. 48, pp. 317–336, 2010.

    Article  Google Scholar 

  8. R. Y. Hindiyeh, Dynamics and Control of Drifting in Automobiles, Ph.D. Thesis, Stanford University, 2013.

  9. V. Robin, S. D. Bruyne, M. Zanon, J. V. Frasch, and M. Diehl, “Towards time-optimal race car driving using nonlinear MPC in real-time,” Proc. of IEEE Conference on Decision and Control, Dec. 15–17, 2014.

  10. J. Gonzales, F. Zhang, K. Li, and F. Borrelli, “Autonomous drifting using onboard sensors,” Proc. of 13th International Symposium on Advanced Vehicle Control, 2016.

  11. B. Goldfain, P. Drews, C. You, M. Barulic, O. Velev, P. Tsiotras, and J. Rehg, “AutoRally: An open platform for aggressive autonomous driving,” http://arxiv.org/abs/1806. 00678, 2018.

  12. F. Zhang, J. Gonzales, S. E. Li, F. Borrelli, and K. Li, “Drift control for cornering maneuvers of autonomous vehicles,” Mechatronics, vol. 54, pp. 167–174, 2018.

    Article  Google Scholar 

  13. E. Jelavic, J. Gonzales, and F. Borrelli, “Autonomous drift parking using a switched control strategy with onboard sensors,” Proc. of IFAC World Congress, 2017.

  14. F. Zhang, J. Gonzales, K. Li, and F. Borrelli, “Autonomous drift cornering with mixed open-loop and closed loop control,” Proc. of IFAC World Congress, 2017.

  15. A. Liniger, Path Planning and Control for Autonomous Racing, Ph.D. Thesis, ETH Zurich, 2018.

  16. M. Kim, T. Lee, and Y. Kang, “Experimental verification of the power slide driving technique for control strategy of autonomous race cars,” International Journal of Precision Engineering and Manufacturing, vol 21, pp. 337–386, 2020.

    Google Scholar 

  17. J. Y. Goh and J. C. Gerdes, “Simultaneous stabilization and tracking of basic automobile drifting trajectories,” Proc. of IEEE Intelligent Vehicle Symposium, June 19–22, 2016.

  18. E. Joa, K. Yi, and Y. Hyun, “Autonomous drift control using vehicle lateral dynamics with self-rotation and revolution,” Proc. of the 14th International Symposium on Advanced Vehicle Control, 2018.

  19. E. Bakker, L. Nyborg, and H. B. Pacejka, “Tyre modelling for use in vehicle dynamics studies,” SAE Transactions, vol. 96, pp. 190–204, 1987.

    Google Scholar 

  20. K. Kritayakirana and J. C. Gerdes, “Design of a feedback-feedforward steering controller for accurate path tracking and stability at the limits of handling,” Vehicle System Dynamics, vol. 53, no. 12, pp. 1687–1704, 2015.

    Article  Google Scholar 

  21. N. R. Kapania, Trajectory Planning And Control for an Autonomous Race Vehicle, Ph.D.Thesis, Stanford University, 2016.

  22. Y. Kwak, T. Lee, and Y. Kang, “Development of vision-based bode slip angle estimation method for scale car-based autonomous driving environment,” Proc. of Korea Society of Automotive Engineering (KSAE) Annual Fall Conference and Exhibition, 2016.

  23. UCB-MPC (2015). Berkeley autonomous race car project. http://cars.it.uu.se/

Download references

Author information

Authors and Affiliations

  1. Department of Secured Smart Electric Vehicle (SSEV), Kookmin University, 77 Jeongneung-dong, Seongbukgu, Seoul, 02707, Korea

    Mincheol Park

  2. Department of Automotive Engineering, Kookmin University, 77 Jeongneung-dong, Seongbuk-gu, Seoul, 02707, Korea

    Yeonsik Kang

Authors
  1. Mincheol Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yeonsik Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yeonsik Kang.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Recommended by Associate Editor Yingmin Jia under the direction of Editor Myo Taeg Lim.

This work was supported by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology NRF2018R1A2B6001888), and the Competency Development Program for Industry Specialists of Korean Ministry of Trade, Industry and Energy (MOTIE), operated by Korea Institute for Advancement of Technology(KIAT). (No. N0002428, HRD program for Future Car), partly.

Mincheol Park received his B.S. degree in Control and Instrumentation Engineering from Korea University. He is currently pursuing his M.S. degree in SSEV (Secured Smart Electric Vehicle) at Kookmin University. His research interests are localization and autonomous driving.

Yeonsik Kang received his B.S. and M.S. degrees from Seoul National University, Seoul, Korea, and his Ph.D. degree in mechanical engineering in 2006 from the University of California Berkeley. He served as a senior scientist from 2007 to 2010 at the Korea Institute of Science and Technology (KIST). He is currently a professor at the Department of Automotive Engineering, Kookmin University, Seoul, Korea. His research interests include automated vehicles, model predictive control, obstacle avoidance, radar and lidar signal processing.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Park, M., Kang, Y. Experimental Verification of a Drift Controller for Autonomous Vehicle Tracking: a Circular Trajectory Using LQR Method. Int. J. Control Autom. Syst. 19, 404–416 (2021). https://doi.org/10.1007/s12555-019-0757-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12555-019-0757-2

Keywords

Search

Navigation