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JACIII Vol.12 No.4 pp. 348-354
doi: 10.20965/jaciii.2008.p0348
(2008)

Paper:

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Implementation of a Real-Time FPGA-Based Intelligent Parallel Parking System

Mohamed Slim Masmoudi*, Willie Tsui**,
Insop Song***, Fakhreddine Karray**,
Mohamed Masmoudi*, and Nabil Derbel*

*Electrical Engineering Department, Ecole Nationale D’Ingenieurs de Sfax, B.P. W, 3038 Sfax, Tunisia

**Electrical and Computer Engineering Department, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, Canada, N2L 3G1

***Ericsson Inc., 5000 Ericsson Dr, Warrendale, PA 15086, USA

Received:
April 23, 2007
Accepted:
June 27, 2007
Published:
July 20, 2008
Creative Commons License
Keywords:
field programmable gate array, fuzzy logic controller, intelligent parking system, real-time system
Abstract
Parallel parking is a challenging maneuver for many drivers, especially in crowded cities with heavy traffic congestion and limited parking spaces. This research focuses on the development of an intelligent parallel parking system. Conventional vehicular control techniques generally require the use of analytical models. However, complexities due to nonlinear car dynamics create multiple challenges when modeling car motion. As fuzzy logic control is appropriate for nonlinear and complex systems where human expert knowledge is available, it is well-suited for the parking application. This paper presents the design and implementation of a real-time fuzzy logic based parallel parking system. Two control units consisting of a main controller and a secondary fuzzy logic controller are utilized. The latter controller is employed for the realization of the wall following task, which has an important role in the parking system. Based on performance and flexibility considerations, the control units are implemented onto a reconfigurable hardware platform, namely a Field Programmable Gate Array (FPGA). A prototype vehicle is developed to ensure the proposed algorithm provides vehicular systems with the parallel parking ability.
Cite this article as:
M. Masmoudi, W. Tsui, I. Song, F. Karray, M. Masmoudi, and N. Derbel, “Implementation of a Real-Time FPGA-Based Intelligent Parallel Parking System,” J. Adv. Comput. Intell. Intell. Inform., Vol.12 No.4, pp. 348-354, 2008.
Data files:
References
  1. [1] T. Li, S. Chang, and Y. Chen, “Implementation of autonomous fuzzy garage-parking control by an FPGA-based car-like mobile robot using infrared sensors,” IEEE Int. Conf. on Robotics and Automation, pp. 3776-3781, 2003.
  2. [2] S. Moon and S. Kong, “Block-based neural networks,” IEEE Transactions on Neural Networks, Vol.12, Issue. 2, pp. 307-317, 2001.
  3. [3] R. Krohling, Y. Zhou, and A. Tyrrell, “Evolving FPGA-based robot controllers using an evolutionary algorithm,” First Int. Conf. on Artificial Immune Systems, 2002.
  4. [4] Valeo Co., “Infos Valeo News,” 2003.[Online]. Available: http://www.valeo.com/
  5. [5] D. Graham-Rowe, “Self-parking car just around the corner,” New Scientist, 2001.
    [Online]. Available: http://www.newscientist.com/news/news.jsp?id=ns99991486.
  6. [6] E. Batista, “Park without dings – or drivers,” Wired News, 2003.
    [Online]. Available: http://www.wired.com/news/technology/0,1282,60154,00.html
  7. [7] Canadian Driver Communications Inc., “Radar-based parking assistance to debut in Mercedes-Benz CL-Class,” Canadian Driver, 2006.
    [Online]. Available: http://www.canadiandriver.com/news/060829-4.htm.
  8. [8] BMW of North America, LLC., “Park distance control,” 2006.
    [Online]. Available: http://www.bmwusa.com/vehicles/5/550iSedan/HighlightDetail.htm.
  9. [9] I. Song, F. Karray, Y. Dai, M. Masmoudi, and B. Ghaddar, “An intelligent car-like robot parking system design and implementation,” Proc. of Second IEEE Int. Conf. on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, 2005.
  10. [10] F. Karray and C. De Silva, “Soft Computing and Intelligent Systems Design,” Addison Wesley, 2004.
  11. [11] T. Lee, C. Tsai, and K. Song, “Fast parking control of mobile robots: A motion planning approach with experimental validation,” IEEE Transactions of Control Systems Technology, Vol.12, Issue.5, pp. 661-676, 2004.
  12. [12] K. Kodagoda, W. Wijesoma, and E. Teoh, “Fuzzy speed and steering control of an AGV,” IEEE Transactions on Control Systems Technology, Vol.10, Issue.1, pp. 112-120, 2002.
  13. [13] I. Paromtchik and C. Laugier, “Motion generation and control for parking an autonomous vehicle,” 1996 IEEE Int. Conf. on Robotics and Automation, pp. 3117-3122, 1996.
  14. [14] S. Chang and T. Li, “Design and implementation of fuzzy parallelparking control for a car-type mobile robot,” Journal of Intelligent and Robotic Systems, 34, pp.175-194, 2002.
  15. [15] J. Arroyable, G. Aranguren, L. Nozal, and J. Martin, “Autonomous vehicle guidance with fuzzy algorithm,” Proc. of IEEE Int. Conf. I.E.C.O.N., 2000.
  16. [16] D. Kim, “An implementation of fuzzy logic controller on the reconfigurable FPGA system,” IEEE Transactions on Industrial Electronics, Vol.47, Issue.3, pp. 703-715, 2002.
  17. [17] M. S. Masmoudi, I. Song, F. Karray and M. Masmoudi, “FPGA implementation of fuzzy wall-following control,” Int. Conf. on Microelectronics, pp. 133-139, 2004.
  18. [18] I. Song, F. Karray and H. Li, “A real-time scheduler design for fuzzy logic controller,” Proc. of IEEE Int. Conf. on Mechatronics and Automation, 2005.
  19. [19] C. Liu and J. Layland, “Scheduling algorithms for multiprogramming in a hard real-time environment,” Journal of the ACM, Vol.20, No.1, pp. 46-61, 1973.

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