Abstract Based on cognitive characteristics, this research aimed at quantifying a tractor driver’s cognitive load (CL) during field work. First of all, the operation tasks under different operating states were analyzed hierarchically utilizing multiple resources theory. Then the tasks were further classified into 4 processing resources, i.e. visual, auditory, cognition, and psychomotor. The cognitive load during the tasks was further quantified by time occupied (TO), action-set switching (ASS) and level of action load (LAL). Finally, this method was used for evaluating the driver’s cognitive load during pulping operation and seeding operation. The effectiveness of this method was validated in the driving simulation platform with a SMI eye tracker, while repeating the process during field work. The diameter of pupils and blink rate (BR) are used to characterize tractor driver’s cognitive load.


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    Titel :

    Cognitive Load Assessment of Tractor Driver Based on Cognitive Task Workload Model


    Beteiligte:
    Pei, Yeqing (Autor:in) / Jin, Xiaoping (Autor:in) / Song, Zhenghe (Autor:in) / Li, Haoyang (Autor:in) / Luo, Ling (Autor:in) / Zheng, Bowen (Autor:in)


    Erscheinungsdatum :

    24.06.2017


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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