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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

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


    Contributors:
    Pei, Yeqing (author) / Jin, Xiaoping (author) / Song, Zhenghe (author) / Li, Haoyang (author) / Luo, Ling (author) / Zheng, Bowen (author)


    Publication date :

    2017-06-24


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Driver cognitive workload estimation: a data-driven perspective

    Yilu Zhang, / Owechko, Y. / Jing Zhang, | IEEE | 2004



    Driver experience and cognitive workload in different traffic environments

    Patten, Christopher J.D. / Kircher, Albert / Östlund, Joakim et al. | Elsevier | 2006


    Measurement of Drivers Cognitive Workload Using Dual Task Methods

    Uchiyama, Y. / Wakita, T. / Kojima, S.-i. et al. | British Library Conference Proceedings | 2001


    TRIGGERING AUTONOMOUS CONTROL BASED ON DRIVER COGNITIVE LOAD

    ANDERSSON STEFAN / BRUNNEGARD OLIVER / LARSSON ANNIKA et al. | European Patent Office | 2020

    Free access