Driving skill analysis using machine learning: The full curve and curve segmented cases

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

研究成果: Conference contribution

12 被引用数 (Scopus)

抄録

Analysis of driving skill/driver state can be used in building driver support and infotainment systems that can be adapted to individual needs of a driver. In this paper we present a machine learning approach to analyzing driving maneuver skills of a driver that covers both longitudinal and lateral controls. The concept is to learn a driver model from sensor data that are related to driving environment, driving behavior and vehicle response. Once the model is built, driving skills of an unknown run can be classified automatically. In this paper, we demonstrate the feasibility of the proposed method for driving skill analysis based on a driving simulator experiment in a curve driving scene for both the full curve and curve segmented cases.

本文言語English
ホスト出版物のタイトル2012 12th International Conference on ITS Telecommunications, ITST 2012
ページ542-547
ページ数6
DOI
出版ステータスPublished - 2012 12月 1
外部発表はい
イベント2012 12th International Conference on ITS Telecommunications, ITST 2012 - Taipei, Taiwan, Province of China
継続期間: 2012 11月 52012 11月 8

出版物シリーズ

名前2012 12th International Conference on ITS Telecommunications, ITST 2012

Conference

Conference2012 12th International Conference on ITS Telecommunications, ITST 2012
国/地域Taiwan, Province of China
CityTaipei
Period12/11/512/11/8

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信

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