Assistive Technology System for Highly Automated Vehicles to Support People with Mild Cognitive Impairment: A Human-Centered Design Approach
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Conference Proceedings
Authors: Alexandra Kondyli, Andrew Davidson, Chris Depcik, John Haug, Lyndsie Koon, Sanaz Motamedi, Mahtab Eskandar, Wayne Giang, Boyi Hu, Eakta Jain, Heng Yao, Xilei Zhao, Abiodun Akinwuntan, Shelley Bhattacharya, Hannes Devos
Abstract: Older adults with mild cognitive impairment (MCI) experience difficulties in memory, processing speed, attention, judgment, and visuospatial skills, which may impede the ability to perform various daily activities efficiently, including driving. The emergence of highly automated vehicles that do not require human intervention may offer significant benefits to individuals with MCI as these vehicles can increase mobility and independence. However, individuals with MCI may still be required to perform higher-level activities during a ride, which can be challenging for this user group. This research is focused on designing and prototyping a system that can help during trip planning and when interacting with an automated vehicle during normal and emergency operations. The proposed assistive technology system includes a secure mobile app, a real-time traveler monitoring system, an interactive in-vehicle agent for emergencies and safety functions, and a platform integrating all sub-systems with vehicle operations via a dashboard. The initial system requirements were identified through a series of interviews and focus groups with stakeholders, such as subject matter experts and older adults with and without MCI. Iterative participatory design sessions were further conducted to establish the information architecture and create visual and interactive designs. A final evaluation session with five individuals with MCI was conducted and showed favorable results in terms of system usability.
Keywords: Mild Cognitive Impairment, Automated Driving Systems, Human-Centered Design
DOI: 10.54941/ahfe1005787
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