We investigate a possible method for detecting a driver's negative adaptation to an automated driving system by analyzing consistency of driver decision making and driver gaze behavior during automated driving. We focus on an automated driving system equivalent to Level 2 automation per the NHTSA's definition. At this level of automation, drivers must be ready to take control of the vehicle in critical situations by monitoring the driving environment and vehicle behavior. Since drivers are not required to operate the pedals or steering wheel during automated driving, a driver's negative adaptation to an automated system needs to be detected from behavior other than vehicle operation. In this study, we focus on driver gaze behavior. We conduct a simulator study to compare the gaze behavior of fifteen drivers during conventional and automated driving. We also analyze the consistency of driver decision making when changing lanes during conventional and automated driving. Experimental results show that drivers who pay less attention to the road ahead during automated driving tend to be less sensitive to risk factors in the surrounding environment and also tend to make inconsistent lane change decisions during automated driving.


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    Titel :

    Analyzing driver gaze behavior and consistency of decision making during automated driving


    Beteiligte:
    Miyajima, Chiyomi (Autor:in) / Yamazaki, Suguru (Autor:in) / Bando, Takashi (Autor:in) / Hitomi, Kentarou (Autor:in) / Terai, Hitoshi (Autor:in) / Okuda, Hiroyuki (Autor:in) / Hirayama, Takatsugu (Autor:in) / Egawa, Masumi (Autor:in) / Suzuki, Tatsuya (Autor:in) / Takeda, Kazuya (Autor:in)


    Erscheinungsdatum :

    01.06.2015


    Format / Umfang :

    905359 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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