Abstract Our main objective was to develop a new driving assistance system that could help less experienced drivers improve their driving skills. We describe a statistical method we developed to extract distinctions between experienced and less experienced drivers. This paper makes three key contributions. The first involves a technology for feature extraction based on AdaBoost, which selects a small number of features critical for operation between experienced and less experienced drivers. The second involves a simple definition for experienced and less experienced drivers. The third involves the introduction of wavelet transforms that were used to analyze the frequency characteristics of driver operations. We performed a series of experiments using a driving simulator on a specially designed course that included several curves and then used the proposed method to extract features of driving operations that demonstrated the differences between the two groups.


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    Titel :

    Learning Characteristic Driving Operations in Curve Sections that Reflect Drivers’ Skill Levels


    Beteiligte:
    Li, Shuguang (Autor:in) / Yamabe, Shigeyuki (Autor:in) / Sato, Yoichi (Autor:in) / Suda, Yoshihiro (Autor:in) / Chandrasiri, Naiwala P. (Autor:in) / Nawa, Kazunari (Autor:in)


    Erscheinungsdatum :

    15.03.2014


    Format / Umfang :

    11 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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