Investigating older adults’ preferences for functions within a human-machine interface designed for fully autonomous vehicles

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Abstract

Compared to traditional cars, where the driver has most of their attention allocated on the road and on driving tasks, in fully autonomous vehicles it is likely that the user would not need to intervene with driving related functions meaning that there will be little need for HMIs to have features and functionality relating to these factors. However, there will be an opportunity for a range of other interactions with the user. As such, designers and researchers need to have an understanding of what is actually needed or expected and how to balance the type of functionality they make available. Also, in HMI design, the design principles need to be considered in relation to a range of user characteristics, such as age, and sensory, cognitive and physical ability and other impairments. In this study, we proposed an HMI specially designed for connected autonomous vehicles with a focus on older adults. We examined older adults’ preferences of CAV HMI functions, and, the degree to which individual differences (e.g., personality, attitude towards computers, trust in technology, cognitive functioning) correlate with preferences for these functions. Thirty-one participants (M age = 67.52, SD = 7.29), took part in the study. They had to interact with the HMI and rate its functions based on the importance and likelihood of using them. Results suggest that participants prefer adaptive HMIs, with journey planner capabilities. As expected, as it is a CAV HMI, the Information and Entertainment functions are also preferred. Individual differences have limited relationship with HMI preferences.

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APA

Voinescu, A., Morgan, P. L., Alford, C., & Caleb-Solly, P. (2018). Investigating older adults’ preferences for functions within a human-machine interface designed for fully autonomous vehicles. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10927 LNCS, pp. 445–462). Springer Verlag. https://doi.org/10.1007/978-3-319-92037-5_32

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