International Journal of Automotive Technology

The Korean Society of Automotive Engineers (한국자동차공학회)
권호 표지

DEVELOPMENT OF OCCUPANT CLASSIFICATION AND POSITION DETECTION FOR INTELLIGENT SAFETY SYSTEM

  • Hannan, M.A. (Department of Electrical, Electronic & Systems Engineering, Faculty of Engineering, Universiti Kebangsaan Malaysia) ;
  • Hussain, A. (Department of Electrical, Electronic & Systems Engineering, Faculty of Engineering, Universiti Kebangsaan Malaysia) ;
  • Samad, S.A. (Department of Electrical, Electronic & Systems Engineering, Faculty of Engineering, Universiti Kebangsaan Malaysia) ;
  • Mohamed, A. (Department of Electrical, Electronic & Systems Engineering, Faculty of Engineering, Universiti Kebangsaan Malaysia) ;
  • Wahab, D.A. (Department of Mechanical & Materials Engineering, Faculty of Engineering, Universiti Kebangsaan Malaysia) ;
  • Ariffin, A.K. (Department of Mechanical & Materials Engineering, Faculty of Engineering, Universiti Kebangsaan Malaysia)
  • Published : 2006.12.01
Download PDF
⟨ Previous Next ⟩

Abstract

Occupant classification and position detection have been significant research areas in intelligent safety systems in the automotive field. The detection and classification of seat occupancy open up new ways to control the safety system. This paper deals with a novel algorithm development, hardware implementation and testing of a prototype intelligent safety system for occupant classification and position detection for in-vehicle environment. Borland C++ program is used to develop the novel algorithm interface between the sensor and data acquisition system. MEMS strain gauge hermatic pressure sensor containing micromachined integrated circuits is installed inside the passenger seat. The analog output of the sensor is connected with a connector to a PCI-9111 DG data acquisition card for occupancy detection, classification and position detection. The algorithm greatly improves the detection of whether an occupant is present or absent, and the classification of either adult, child or non-human object is determined from weights using the sensor. A simple computation algorithm provides the determination of the occupant's appropriate position using centroidal calculation. A real time operation is achieved with the system. The experimental results demonstrate that the performance of the implemented prototype is robust for occupant classification and position detection. This research may be applied in intelligent airbag design for efficient deployment.

Keywords

References

  1. AAP (American Academy of Pediatrics). (2006). Car safety seats: A guide for families. (Online) http://www.aap.org/family/carseatguide.htm (11 January 2006)
  2. Bob, B. (2005). The torsional sensing load cell for occupant positioning sensing. (Online) http://www.gagetek.com/autocell.pdf (15 April 2005)
  3. Devy, M., Giralt, A. and Marin-Hernandez, A. (2000). Detection and classification of passenger occupancy using stereovision. Proc. IEEE Intelligent Vehicles Symposium, Dearborn (MI), USA, 714-719
  4. Gautama, S., Lacorix, S. and Devy, M. (1999). Evaluation of stereo matching algorithms for occupant detection. Proc. Int. Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, 177-184
  5. John, D. (2000). Out of harm's way. Mechanical engineering. (Online) http://www.memagazine.org/ backissues/dec00/features/feat_toc.html (15 October, 2005)
  6. Jeff, K. and Candace, S. (2005). Auto sensors play small role in reducing child airbag deaths. (Online) http://stm.pennnet.com/articles/article_display.cfm?article_id=267590 (27 March 2005)
  7. Klomark, M. (2000). Occupant Detection Using Computer Vision. M. S. Thesis, Computer Vision, Linkoping University
  8. Krotosky, S. J., Cheng, S.Y. and Trivedi, M. M. (2004). Face detection and head tracking using stereo and thermal infrared cameras for 'smart' airbags: A comparative analysis. Proc. 7th Int. IEEE Conf. Intelligent Transportation Systems, 17-22
  9. Microfused Silicon Strain Gage (MSG), Hermetic Pressure Sensing. (2005). (Online) http://www.ti.com/snc/products/sensors/auto-msg.htm (21 March 2005)
  10. NuDAQ, PCI-9111DG/HR. 2000. Multi-Functions Data Acquisition Card User's Guide. (2003). (Online) http://www.ciclope.info/display/docs/manual.PCI9111.pdf (23 July 2003)
  11. NSC (National Safety Council). (2005). Crisis to progress: Airbag safety five year report. (Online) http://www.nsc.org/library/cristext.htm (28 April 2005)
  12. Owechko, Y., Srinivasa, N., Medasani, S. and Boscolo, R. (2003). High performance sensor fusion architecture for vision-based occupant detection. Proc. IEEE Int. Conf. Intelligent Transportation Systems, 2, 1128-1133
  13. Shigeyuki, N. (2004). Development of occupant classification system for advanced airbag requirements. Mitsubishi Motors Technical Review, 16, 61-64
  14. Stephen, L. (2005). New child car seat regulation. (Online) http://www.chop.edu/consumer/jsp/division/generic.jsp?id=77979 (26 December 2005)
  15. Timothy, D. S. and Trivedi, M. M. (2003). Real-time stereo-based vehicle occupant posture determination for intelligent airbag deployment. Proc. IEEE Int. Conf. Intelligent Vehicles, 570-574