Beyond the Dashboard: Investigating Distracted Driver Communication Preferences for ADAS
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866910499300442112 |
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| author | Hasan, Aamir McPherson, D. Livingston Miles, Melissa Driggs-Campbell, Katherine |
| author_facet | Hasan, Aamir McPherson, D. Livingston Miles, Melissa Driggs-Campbell, Katherine |
| contents | Distracted driving is a major cause of road fatalities. With improvements in driver (in)attention detection, these distracted situations can be caught early to alert drivers and improve road safety and comfort. However, drivers may have differing preferences for the modes of such communication based on the driving scenario and their current distraction state. To this end, we present an (N=147) where videos of simulated driving scenarios were utilized to learn drivers preferences for modes of communication and their evolution with the drivers changing attention. The survey queried participants preferred modes of communication for scenarios such as collisions or stagnation at a green light. that inform the future of communication between drivers and their vehicles. We showcase the different driver preferences based on the nature of the driving scenario and also show that they evolve as the drivers distraction state changes |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_03312 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Beyond the Dashboard: Investigating Distracted Driver Communication Preferences for ADAS Hasan, Aamir McPherson, D. Livingston Miles, Melissa Driggs-Campbell, Katherine Human-Computer Interaction Distracted driving is a major cause of road fatalities. With improvements in driver (in)attention detection, these distracted situations can be caught early to alert drivers and improve road safety and comfort. However, drivers may have differing preferences for the modes of such communication based on the driving scenario and their current distraction state. To this end, we present an (N=147) where videos of simulated driving scenarios were utilized to learn drivers preferences for modes of communication and their evolution with the drivers changing attention. The survey queried participants preferred modes of communication for scenarios such as collisions or stagnation at a green light. that inform the future of communication between drivers and their vehicles. We showcase the different driver preferences based on the nature of the driving scenario and also show that they evolve as the drivers distraction state changes |
| title | Beyond the Dashboard: Investigating Distracted Driver Communication Preferences for ADAS |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2403.03312 |