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Author:

Hu, Dun-Ii (Hu, Dun-Ii.) | Zhao, Xiao-Hua (Zhao, Xiao-Hua.) | Mu, Zhi-Chun (Mu, Zhi-Chun.) | Sun, De-Hui (Sun, De-Hui.) | Liu, Kang (Liu, Kang.)

Indexed by:

EI Scopus

Abstract:

Being a direct reflection of the drivers' states, the driving behavior research is getting widely attention recently. This paper presents a new identification method of fatigue driving state, which is obtained from driving behavior data analysis both about normal driving state and the fatigues ones. PERCLOS80 is utilized as reference to distinguish two different states. During identification process, the driving behavior data is dealt with wavelet transform. Then modulus maxima values and Lipschitz exponents which reflected smooth level of data signal are performed as index to identify driving states: Normal or fatigue. Among various experimental driving behavior data, the error to driving center line is chosen as information source here, and the result shows remarkable identified effect. © 2013 TCCT, CAA.

Keyword:

Wavelet analysis Wavelet transforms Behavioral research Fatigue of materials

Author Community:

  • [ 1 ] [Hu, Dun-Ii]School of Information Engineering, University of Science and Technology, Beijing 100083, China
  • [ 2 ] [Hu, Dun-Ii]Beijing Key Laboratory of Fieldbus Technology and Automation, North China University of Technology, Beijing 100144, China
  • [ 3 ] [Zhao, Xiao-Hua]Transportation Research Center, Beijing University of Technology, Beijing 100022, China
  • [ 4 ] [Mu, Zhi-Chun]School of Information Engineering, University of Science and Technology, Beijing 100083, China
  • [ 5 ] [Sun, De-Hui]School of Information Engineering, University of Science and Technology, Beijing 100083, China
  • [ 6 ] [Liu, Kang]Beijing Key Laboratory of Fieldbus Technology and Automation, North China University of Technology, Beijing 100144, China

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Source :

ISSN: 1934-1768

Year: 2013

Page: 3590-3596

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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