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Development of Warning Methods for Planned and Unplanned Takeover Requests in a Simulated Automated Driving Vehicle

Published: 17 September 2022 Publication History

Abstract

In several circumstances, a level-three automated vehicle cannot continue driving in an automated driving mode and requests a human driver to take over. In this study, a series of experiments to examine how to provide a TOR was conducted. First, for forty-one persons, a HUD icon, earcon, seat vibration, and combinations were compared. The results indicated that the HUD icon-earcon and HUD icon-seat vibration were the most effective. Second, the combinations of A-pillar LED light and cluster icon (visual), earcon and speech message (auditory), and presence/absence of seat vibration (haptic) were compared. Thirty-six volunteers participated in the ADS failure and forty in the highway exit experiment. In the ADS failure, the combination of A-pillar LED light and seat vibration (AH) reduced the RT but can induce stress. In the highway exit, a speech message is recommended due to control stability, and the AH is not recommended due to longitudinal instability.

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    cover image ACM Conferences
    AutomotiveUI '22: Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
    September 2022
    371 pages
    ISBN:9781450394154
    DOI:10.1145/3543174
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    Published: 17 September 2022

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    Author Tags

    1. Automated vehicle
    2. Modality
    3. Takeover
    4. Takeover request

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    Funding Sources

    • BK21 Program, National Research Foundation of Korea (NRF) funded by the Ministry of Education
    • Transportation and Logistics R&D Program funded by the Ministry of Land, Infrastructure, and Transport of the Korean government
    • Middle-level Researcher Support Project, National Research Foundation of Korea (NRF) funded by the Ministry of Education
    • the Competency Development Program for Industry Specialists, Korean Ministry of Trade, Industry and Energy (MOTIE), operated by Korea Institute for Advancement of Technology (KIAT)

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    Overall Acceptance Rate 248 of 566 submissions, 44%

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    View all
    • (2024)Move, Connect, Interact: Introducing a Design Space for Cross-Traffic InteractionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785808:3(1-40)Online publication date: 9-Sep-2024
    • (2024)Honkable Gestalts: Why Autonomous Vehicles Get Honked AtProceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3640792.3675732(317-328)Online publication date: 22-Sep-2024
    • (2024)Interactive Output Modalities Design for Enhancement of User Trust Experience in Highly Autonomous DrivingInternational Journal of Human–Computer Interaction10.1080/10447318.2024.2375697(1-19)Online publication date: 10-Jul-2024
    • (2023)Investigating effects of multimodal explanations using multiple In-vehicle displays for takeover request in conditionally automated drivingTransportation Research Part F: Traffic Psychology and Behaviour10.1016/j.trf.2023.05.01496(1-22)Online publication date: Jul-2023
    • (2023)Exploring the Driver’s Mental Control Model: Concepts and InsightsHCI International 2023 – Late Breaking Posters10.1007/978-3-031-49215-0_51(431-437)Online publication date: 12-Dec-2023

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