Drivers’ emotion is one of the key factors affecting driving behavior, negative emotion would be harmful to safe driving. In conditional automated driving, drivers would devote the majority of the time to Non-Driving Related Tasks (NDRTs), and varying NDRTs may lead to variations in drivers’ emotions. In this study, a series of conditional automated driving simulation experiments considering four typical NDRTs was conducted, and the electroencephalogram (EEG) signals were detected to identify and characterize drivers’ emotions by the valence-arousal (V-A) model, where in valence ranges from displeasure to pleasure and arousal ranges from relaxation to excitement. The results show that 1) the drivers’ emotion, as measured by the valence and arousal, was significantly affected by the rest and reading tasks during conditional automated driving, but not influenced by the monitoring vehicle operation and watching video tasks; 2) the V-A model revealed that the drivers were prone to keep alert in automated driving while showing increased stress in the rest state. The findings of this study contribute to a better understanding of drivers’ emotions and NDRTs in conditional automated driving.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Understanding Drivers’ Emotion Variations During NDRTs in Conditional Automated Driving Using EEG Data


    Beteiligte:
    Guo, Wenhui (Autor:in) / Zhang, Hui (Autor:in) / Ding, Naikan (Autor:in) / Liu, Yongjie (Autor:in)


    Erscheinungsdatum :

    2023-08-04


    Format / Umfang :

    1020097 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Cockpit Concept for Conditional Automated Driving

    Dipl.-Ing. Reilhac, Patrice / Dipl.-Ing. Moizard, Julien / Dipl.-Ing. (Fh) Kaiser, Frank et al. | Springer Verlag | 2016


    How to Counteract Driver Fatigue during Conditional Automated Driving—A Systematic Review

    Alexandra Loew / Christina Kurpiers / Martin Götze et al. | DOAJ | 2024

    Freier Zugriff

    A Longitudinal Simulator Study to Explore Drivers’ Behaviour During Highly-Automated Driving

    Large, David R. / Burnett, Gary / Morris, Andrew et al. | Springer Verlag | 2017


    Task load of professional drivers during level 2 and 3 automated driving

    Bieg, Hans-Joachim / Daniilidou, Constantina / Michel, Britta et al. | TIBKAT | 2020