Highlights Positive valence leads to better takeover quality. High arousal does not result in faster takeover time. We cannot simply apply the findings in manual driving to automated driving.

    Abstract In conditionally automated driving, drivers have difficulty in takeover transitions as they become increasingly decoupled from the operational level of driving. Factors influencing takeover performance, such as takeover lead time and the engagement of non-driving-related tasks, have been studied in the past. However, despite the important role emotions play in human-machine interaction and in manual driving, little is known about how emotions influence drivers’ takeover performance. This study, therefore, examined the effects of emotional valence and arousal on drivers’ takeover timeliness and quality in conditionally automated driving. We conducted a driving simulation experiment with 32 participants. Movie clips were played for emotion induction. Participants with different levels of emotional valence and arousal were required to take over control from automated driving, and their takeover time and quality were analyzed. Results indicate that positive valence led to better takeover quality in the form of a smaller maximum resulting acceleration and a smaller maximum resulting jerk. However, high arousal did not yield an advantage in takeover time. This study contributes to the literature by demonstrating how emotional valence and arousal affect takeover performance. The benefits of positive emotions carry over from manual driving to conditionally automated driving while the benefits of arousal do not.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Examining the effects of emotional valence and arousal on takeover performance in conditionally automated driving


    Contributors:


    Publication date :

    2020-01-08


    Size :

    10 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Predicting driver takeover performance in conditionally automated driving

    Du, Na / Zhou, Feng / Pulver, Elizabeth M. et al. | Elsevier | 2020



    Predicting Driver Takeover Time in Conditionally Automated Driving

    Ayoub, Jackie / Du, Na / Yang, X. Jessie et al. | IEEE | 2022



    Is driving experience all that matters? Drivers’ takeover performance in conditionally automated driving

    Zhang, Neng / Fard, Mohammad / Davy, John Laurence et al. | Elsevier | 2023

    Free access