Differentiating Skilled and Unskilled Drivers by Using an AdaBoost Classifier for Driver's Operations

Prior to developing driving assistance systems to improve driving skills, the differences between skilled and unskilled drivers must be clarified. Previous studies suggest that highly skilled drivers share certain characteristics in accelerator, brake, and steering operations. This paper proposes a statistical method to extract these characteristics from data obtained in driving simulator experiments of driving around curves. The proposed method is composed of wavelet transform and an AdaBoost algorithm, a machine learning algorithm.

• Record URL:
  http://itswc.confex.com/itswc/WC2011/webprogram/Paper3065.html
• Availability:
  • Find a library where document is available. Order URL: http://itswc.confex.com/itswc/WC2011/webprogram/start.html
• Supplemental Notes:
  • Abstract reprinted with permission from Intelligent Transportation Society of America. Index title: Characteristics Extraction of Highly-Skilled Drivers’ Driving by Using an AdaBoost Classifier on Driver's Operations.
• Corporate Authors:

  ITS America

  1100 17th Street, NW, 12th Floor
  Washington, DC  United States  20036
• Authors:
  • Li, Shuguang
  • Yamaguchi, Daisuke
  • Sato, Yoichi
  • Suda, Yoshihiro
  • Hirasawa, Takayuki
• Conference:
  • 18th ITS World Congress
  • Location: Orlando Florida, United States
  • Date: 2011-10-16 to 2011-10-20
• Publication Date: 2011

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Photos; References;
• Pagination: 10p
• Monograph Title: 18th ITS World Congress, Orlando, 2011. Proceedings

Subject/Index Terms

• TRT Terms: Algorithms; Braking; Driver errors; Driver experience; Driver performance; Driving simulators; Measuring methods; Steering
• Subject Areas: Highways; Safety and Human Factors; I83: Accidents and the Human Factor;

Filing Info

• Accession Number: 01484823
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 23 2013 1:08PM