Presently, vehicles equipped with conditionally automated driving (SAE level 3) technology is gradually becoming part of people's lives, marking a considerable step towards fully automated driving. In conditionally automated driving, drivers can divert their attention from the road but must remain vigilant to receive vehicle status updates and be prepared to regain control at any moment. However, driver distraction during takeover can increase safety risks. Effectively providing takeover request prompts in such scenarios, allowing drivers to make high-quality takeover decisions, is a critical issue that conditional autonomous vehicles need to address. Hence, this study aims to explore how to effectively communicate different levels of Situational Awareness Transparency (SAT) information to drivers during conditional autonomous driving takeovers to ensure safe vehicle control handover. After collecting 243 survey responses to understand driver takeover scenarios, the study employed simulation experiments involving 21 participants aged 19 to 51 with varying driving experiences. The experiments tested the impact of auditory enhancements of different SAT levels on drivers’ takeover time, judgment quality, and perception in two scenarios with varying urgency. The findings suggest a method to improve takeover quality in the early stages of L3 autonomous vehicle development, enhancing drivers’ situational awareness.


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    Titel :

    Enhancing Driver Takeover Quality in Conditional Automated Driving Optimizing HMI Expression During Takeover Process


    Weitere Titelangaben:

    Communic.Comp.Inf.Science


    Beteiligte:
    Stephanidis, Constantine (Herausgeber:in) / Antona, Margherita (Herausgeber:in) / Ntoa, Stavroula (Herausgeber:in) / Salvendy, Gavriel (Herausgeber:in) / Liu, Yang (Autor:in)

    Kongress:

    International Conference on Human-Computer Interaction ; 2024 ; Washington DC, USA June 29, 2024 - July 04, 2024



    Erscheinungsdatum :

    30.12.2024


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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