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...

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Bibliographic Details
Published in2024 12th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) pp. 274 - 280
Main Authors Jestin, Iris, Harvey, Catherine
Format Conference Proceeding
LanguageEnglish
Published IEEE 15.09.2024
Subjects
Automated Vehicles
Cognitive Decline
Conferences
Data collection
Driver behavior
Driver Monitoring Systems
Ethics
Human factors
Human Machine Interfaces
Human-machine systems
Industries
Monitoring
Older Drivers
Protection
Responsible Research
Vehicles
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Summary: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.
DOI:10.1109/ACIIW63320.2024.00055