In highly automated driving, the driver is allowed to temporarily engage in non-driving related tasks (NDR-tasks). However, when reaching a system limit, the driver needs to take back vehicle control within a reasonable amount of time. Previous studies found impairments in take-over performance while engaged in NDR-tasks, but little is known about the impact of specific task characteristics. In the present driving simulator study 14 participants used a highly automated driving system on a motorway track and faced six critical take-over situations. Based on assumptions of Wickens’ multiple resource theory different variables were systematically manipulated: The demands of the NDR-task (modalities, cognitive workload) and the time budget of the take-over situation (6 vs. 8 s). Compared to an auditory task, take-over times tended to be longer for a visual-manual task, particularly when the task had a high cognitive load. Drivers did not brake faster, but stronger in the more time critical take-over situation. Further research is necessary to validate the results with a larger sample of participants and to extend the findings to other NDR-tasks and scenarios. Knowledge about the impact of different NDR-tasks provides possible approaches for adaptive HMI concepts or might help regulators making decisions on allowed NDR-tasks in automated driving.


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    Titel :

    Non-driving related tasks in highly automated driving – Effects of task modalities and cognitive workload on take-over performance


    Beteiligte:

    Kongress:

    AmE 2018 – Automotive meets Electronics - 9. GMM-Fachtagung ; 2018 ; Dortmund, Deutschland



    Erscheinungsdatum :

    01.01.2018


    Format / Umfang :

    6 pages



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch