Driver Monitoring Systems in Automated Vehicles for the Older Population

Advances in vehicle technologies are changing the way we drive. Driver monitoring systems can detect driver states, such as drowsiness and inattention and, when linked with appropriate technological interventions, can provide support to drivers with the aim of making driving safer for all. This may be particularly beneficial to older drivers, who may have to adapt to changing cognitive and physical abilities. However, there are concerns around driver monitoring systems in terms of data collection, interpretation, and protection. This research puts forward a ‘behavioral’ approach to data management, which uses signs of behavior change, rather than symptoms of clinical conditions, to ‘understand’ driving behaviors and trigger interventions. In this way, we believe that driver monitoring, and related technologies, are ethically acceptable as a support to drivers, as opposed to a ‘diagnostic’ approach, which raises serious concerns. The research described here is at an early stage and we report on initial participatory-design work which has been conducted to inform learning. Future work is described, covering the inclusive design and evaluation of future driver monitoring and related technologies.

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Publication Details

Published
2024-09-15
DOI
https://doi.org/10.1109/aciiw63320.2024.00055
Citations
1
Primary Topic
Older Adults Driving Studies
Type
article
Field-Weighted Citation Impact
1.15
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article

Driver Monitoring Systems in Automated Vehicles for the Older Population

Iris Jestin, Catherine Harvey
1 citations
Older Adults Driving Studies
1.15
article

Driver Monitoring Systems in Automated Vehicles for the Older Population

Iris Jestin, Catherine Harvey
article en
1 citations

Abstract

Advances in vehicle technologies are changing the way we drive. Driver monitoring systems can detect driver states, such as drowsiness and inattention and, when linked with appropriate technological interventions, can provide support to drivers with the aim of making driving safer for all. This may be particularly beneficial to older drivers, who may have to adapt to changing cognitive and physical abilities. However, there are concerns around driver monitoring systems in terms of data collection, interpretation, and protection. This research puts forward a ‘behavioral’ approach to data management, which uses signs of behavior change, rather than symptoms of clinical conditions, to ‘understand’ driving behaviors and trigger interventions. In this way, we believe that driver monitoring, and related technologies, are ethically acceptable as a support to drivers, as opposed to a ‘diagnostic’ approach, which raises serious concerns. The research described here is at an early stage and we report on initial participatory-design work which has been conducted to inform learning. Future work is described, covering the inclusive design and evaluation of future driver monitoring and related technologies.

University of Nottingham (GB)
Openalex Percentile: Top 13%
Older Adults Driving Studies
1.15
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