McKerral, A., Mulhall, M.D., Gonçalves, R.C. et al. (5 more authors) (2025) HMI design in the context of DMS and automation: emerging themes from an expert workshop. Cognition, Technology & Work, 27 (1). pp. 181-192. ISSN: 1435-5558
Abstract
This paper consolidates insights from an expert workshop and presents overarching design concepts on how to effectively integrate driver monitoring systems (DMS) into vehicle interfaces. The safety potential of DMS hinges on effective integration with a vehicle’s human–machine interface (HMI), enabling a broader range of response options offered by increasing vehicle autonomy. Integration design significantly influences user experience, acceptance, and consequently, driver safety. Different driver impairment states may require different HMI approaches due to varying physical and behavioural features of driver states, requiring a HMI strategy that is more nuanced and customised than what is typically seen in automotive HMI. Workshop attendees at the 2023 Automotive-UI conference engaged in structured brainstorming, identifying ideal HMI system responses, implementation strategies, and associated risks for the detection of impaired drivers. Brainstorming occurred for two use cases (either distracted or drowsy); first in the context of manual driving, followed by highly automated driving (SAE L3+). Concepts included generic and state-specific responses, and level-of-automation-specific and -agnostic intervention strategies. Notably, DMS-HMI integration extended beyond simple alerts, with concepts addressing short-term risk-mitigation and long-term behaviour-change as intended outcomes. These principles represent contemporary thinking which must be tested and refined as the available technology develops, in turn enabling additional adverse driver states to be addressed. Design norms around DMS-HMI integration are yet to be established. DMS-HMI integration will be critical to the user acceptance and safety benefits of DMS, requiring a nuanced and considered approach.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s10111-025-00792-y. |
| Keywords: | Driver monitoring systems, Drowsiness, Distraction, Human–machine interface |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) |
| Funding Information: | Funder Grant number EU - European Union 101006664 |
| Depositing User: | Symplectic Publications |
| Date Deposited: | 25 Jul 2025 12:50 |
| Last Modified: | 25 Jul 2025 12:50 |
| Published Version: | https://link.springer.com/article/10.1007/s10111-0... |
| Status: | Published |
| Publisher: | Springer Nature |
| Identification Number: | 10.1007/s10111-025-00792-y |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:229381 |
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