International Journal of Automotive Technology

  • 제7권7호
  • /
  • Pages.827-832
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  • 2006
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  • 1229-9138(pISSN)
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  • 1976-3832(eISSN)
한국자동차공학회 (The Korean Society of Automotive Engineers)
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)
  • 발행 : 2006.12.01
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초록

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.

키워드

참고문헌

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