Mixed control by driver and automated system is going to be implemented for decades until fully automated driving is achieved. Thus, the driver has to re-control the vehicle accurately and in a timely manner when an automated system sends a take-over request (TOR) at its limitation. Workload is the actual capacity required for a person to complete a specified task. While in driving task, excessively low and high workloads result in an insufficient capacity of drivers. Hence, a driving simulator experiment was performed in three levels of automated driving conditions, with 31 participants involved. The results showed that compared to manual driving conditions, a driver’s subjective workload was significantly reduced in both partial and highly automated driving conditions. The results support the application of an automated driving system, as it reduces driving workload. The results also supported that participants reflected higher workload when encountering more critical situations, especially under higher levels of automation.


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    Titel :

    A Study of How Drivers’ Subjective Workload and Driving Performance Change under Varying Levels of Automation and Critical Situations


    Beteiligte:
    Zhai, Junda (Autor:in) / Lu, Guangquan (Autor:in)

    Kongress:

    19th COTA International Conference of Transportation Professionals ; 2019 ; Nanjing, China


    Erschienen in:

    CICTP 2019 ; 344-355


    Erscheinungsdatum :

    02.07.2019




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch