Dominant driving operations in curve sections differentiating skilled and unskilled drivers

Shuguang Li, Shigeyuki Yamabe, Yoichi Sato, Takayuki Hirasawa, Suda Yoshihiro, P. N. Chandrasiri, Kazunari Nawa, Takeshi Matsumura, Koji Taguchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


Our objective is to develop a new driving assist system that can help low-skilled drivers improve their driving skill. In this paper, we describe a statistical method we have developed to extract distinctions between high- and low-skilled drivers. There are three key contributions. The first is the introduction of wavelet transform to analyze the frequency character of driver operations. The second is a feature extraction technology based on AdaBoost, which selects a small number of critical operation features between high- and low-skilled drivers. The third is a simple definition for high- and low-skilled drivers. We performed a series of experiments using a driving simulator on a specially designed course including several curves and then used the proposed method to extract driving operation features showing the difference between the two groups.

Original languageEnglish
Title of host publicationProceedings of the FISITA 2012 World Automotive Congress
PublisherSpringer Verlag
Number of pages14
EditionVOL. 12
ISBN (Print)9783642338373
Publication statusPublished - 2013
Externally publishedYes
EventFISITA 2012 World Automotive Congress - Beijing, China
Duration: 2012 Nov 272012 Nov 30

Publication series

NameLecture Notes in Electrical Engineering
NumberVOL. 12
Volume200 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119


ConferenceFISITA 2012 World Automotive Congress


  • Curve sections
  • Driver behavior
  • Driving simulator
  • Driving skill
  • Features extraction

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering


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