Haptic Icons: A Hands-On Approach to Haptic HMI in Automated Vehicles
This paper examines the potential integration of haptic feedback on steering wheels for automated driving applications, with a particular focus on transitions between automated and manual modes, takeover requests, and warnings. An iterative, three-phase methodology was employed: (1) The initial set...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Open Journal of Intelligent Transportation Systems |
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| Online Access: | https://ieeexplore.ieee.org/document/10982355/ |
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| _version_ | 1850151333384945664 |
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| author | Joseba Sarabia Myriam Vaca Mauricio Marcano Sergio Diaz Joshue Perez Rastelli Asier Zubizarreta |
| author_facet | Joseba Sarabia Myriam Vaca Mauricio Marcano Sergio Diaz Joshue Perez Rastelli Asier Zubizarreta |
| author_sort | Joseba Sarabia |
| collection | DOAJ |
| description | This paper examines the potential integration of haptic feedback on steering wheels for automated driving applications, with a particular focus on transitions between automated and manual modes, takeover requests, and warnings. An iterative, three-phase methodology was employed: (1) The initial set of haptic notifications was designed based on input from the literature review, (2) These notifications were then tested in a driving simulator to identify the most effective options, and (3) The selected notifications were evaluated in a dynamic simulator under realistic conditions, including noise, vibration, and harshness (NVH). User studies were conducted at each phase to gather subjective metrics and validate the usability of the haptic feedback. The results demonstrate that specific haptic patterns enhance driver situational awareness and improve transitions between driving modes compared to conventional auditory signals, contributing to safer human-machine interaction in automated vehicles. |
| format | Article |
| id | doaj-art-9ddb4d58f9f54eb89b4fe989d98ec274 |
| institution | OA Journals |
| issn | 2687-7813 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Intelligent Transportation Systems |
| spelling | doaj-art-9ddb4d58f9f54eb89b4fe989d98ec2742025-08-20T02:26:19ZengIEEEIEEE Open Journal of Intelligent Transportation Systems2687-78132025-01-01667369110.1109/OJITS.2025.356658910982355Haptic Icons: A Hands-On Approach to Haptic HMI in Automated VehiclesJoseba Sarabia0https://orcid.org/0000-0002-1759-4365Myriam Vaca1https://orcid.org/0000-0002-7762-524XMauricio Marcano2https://orcid.org/0000-0001-7106-0922Sergio Diaz3https://orcid.org/0000-0002-2617-2121Joshue Perez Rastelli4https://orcid.org/0000-0002-0974-5303Asier Zubizarreta5https://orcid.org/0000-0001-6049-2308Bilbao School of Engineering, Automatic Control and System Engineering, University of the Basque Country, Bilbao, SpainBilbao School of Engineering, Automatic Control and System Engineering, University of the Basque Country, Bilbao, SpainBasque Research and Technology Alliance, Parque Científico y Tecnológico de Bizkaia, TECNALIA, Derio, SpainBasque Research and Technology Alliance, Parque Científico y Tecnológico de Bizkaia, TECNALIA, Derio, SpainBasque Research and Technology Alliance, CEIT, Donostia, SpainBilbao School of Engineering, Automatic Control and System Engineering, University of the Basque Country, Bilbao, SpainThis paper examines the potential integration of haptic feedback on steering wheels for automated driving applications, with a particular focus on transitions between automated and manual modes, takeover requests, and warnings. An iterative, three-phase methodology was employed: (1) The initial set of haptic notifications was designed based on input from the literature review, (2) These notifications were then tested in a driving simulator to identify the most effective options, and (3) The selected notifications were evaluated in a dynamic simulator under realistic conditions, including noise, vibration, and harshness (NVH). User studies were conducted at each phase to gather subjective metrics and validate the usability of the haptic feedback. The results demonstrate that specific haptic patterns enhance driver situational awareness and improve transitions between driving modes compared to conventional auditory signals, contributing to safer human-machine interaction in automated vehicles.https://ieeexplore.ieee.org/document/10982355/Haptic HMIautomated drivinguser studydriving simulator |
| spellingShingle | Joseba Sarabia Myriam Vaca Mauricio Marcano Sergio Diaz Joshue Perez Rastelli Asier Zubizarreta Haptic Icons: A Hands-On Approach to Haptic HMI in Automated Vehicles IEEE Open Journal of Intelligent Transportation Systems Haptic HMI automated driving user study driving simulator |
| title | Haptic Icons: A Hands-On Approach to Haptic HMI in Automated Vehicles |
| title_full | Haptic Icons: A Hands-On Approach to Haptic HMI in Automated Vehicles |
| title_fullStr | Haptic Icons: A Hands-On Approach to Haptic HMI in Automated Vehicles |
| title_full_unstemmed | Haptic Icons: A Hands-On Approach to Haptic HMI in Automated Vehicles |
| title_short | Haptic Icons: A Hands-On Approach to Haptic HMI in Automated Vehicles |
| title_sort | haptic icons a hands on approach to haptic hmi in automated vehicles |
| topic | Haptic HMI automated driving user study driving simulator |
| url | https://ieeexplore.ieee.org/document/10982355/ |
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