Parametric Versus Non-parametric Models of Driving Behavior Signals for Driver Identification

  • Toshihiro Wakita
  • Koji Ozawa
  • Chiyomi Miyajima
  • Kazuya Takeda
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3546)


In this paper, we propose a driver identification method that is based on the driving behavior signals that are observed while the driver is following another vehicle. Driving behavior signals, such as the use of of the accelerator pedal, brake pedal, vehicle velocity, and distance from the vehicle in front, are measured using a driving simulator. We compared the identification rate obtained using different identification models and different features. As a result, we found the non-parametric models to be better than the parametric models. Also, the driver’s operation signals were found to be better than road environment signals and car behavior signals.


Gaussian Mixture Model Behavior Signal Driving Simulator Optimal Velocity Vehicle Velocity 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Toshihiro Wakita
    • 1
    • 2
  • Koji Ozawa
    • 2
  • Chiyomi Miyajima
    • 2
  • Kazuya Takeda
    • 2
  1. 1.Toyota Central R&D LabsNagakuteJapan
  2. 2.Graduate School of Information ScienceNagoya UniversityNagoyaJapan

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