自動車のタイヤ騒音を用いた路面状況の自動検出 Automatic Detection of Road Surface Conditions using Tire Noise from Vehicles

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Author(s)

Abstract

This paper proposes a new method for automatically detecting the states of the road surface from tire noises of vehicles. The methods are based on a Fast Fourier Transform analysis, an artificial neural network, and the mathematical theory of evidence. The proposed classification is carried out in sets of multiple neural networks using the learning vector quantization networks. The outcomes of the networks are then integrated using the voting decision making scheme. It seems then feasible to detect passively and readily the states of the surface: i.e., as a rule of thumb, dry, wet, snowy and slushy state, automatically. Preliminary classification results for an independent validation set yielded 81.6% correct classification. This was improved to 91% by addition of information about the early state in a final decision.

Journal

  • IEICE technical report

    IEICE technical report 108(411), 55-60, 2009-01-22

    The Institute of Electronics, Information and Communication Engineers

References:  7

Codes

  • NII Article ID (NAID)
    110007131924
  • NII NACSIS-CAT ID (NCID)
    AN10164817
  • Text Lang
    ENG
  • Article Type
    ART
  • ISSN
    09135685
  • NDL Article ID
    9794941
  • NDL Source Classification
    ZN33(科学技術--電気工学・電気機械工業--電子工学・電気通信)
  • NDL Call No.
    Z16-940
  • Data Source
    CJP  NDL  NII-ELS 
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