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Impact of In-Vehicle Touchscreen Size on Visual Demand and Usability
Technical Paper
2017-01-1984
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Given the wide adoption of touchscreens in vehicles, an interesting debate is taking place regarding the good screen size, length-width ratio and whether the usability of in-vehicle information system (IVIS) would be decreased by a larger screen, especially. Moreover, the lack of scientific evidence about the concrete impact of touch screen size on usability raises questions to practitioners. In this paper, we investigated the impact of in-vehicle touch screen size on users’ visual behavior and usability as measured using eye tracker and questionnaire. Two experiments were conducted on 30 participants. In the first experiment, participants were asked to seek same information on four different in-vehicle screens based on simulated driving environment, while eye movement was recorded for analyzing efficiency of visual behavior. In the second experiment, as secondary driving tasks tested in real driving environment, touch operations of same functions were implemented, including calling, playing music and adjusting air conditioner temperature. Touch areas of these tasks were similar in different vehicles to ensure the comparability. Furthermore, eye movements were recorded and system usability scales were completed for evaluating the usability of in-vehicle touch screen. As for analyzing, usability is evaluated by effectiveness, efficiency, perceived usability and driving compatibility. Four vehicles, namely Tesla model S, Volvo XC90, Cadillac CT6 and Mazda Alexa, were selected for these two experiment, considering that they had different size and length-width ratio screens. In consideration of visual demand and usability, it seems that large vertical touchscreens ≥inch, length-width ratio<1) are the best choice for IVIS.
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Citation
Ma, J., Li, J., Gong, Z., and Yu, J., "Impact of In-Vehicle Touchscreen Size on Visual Demand and Usability," SAE Technical Paper 2017-01-1984, 2017, https://doi.org/10.4271/2017-01-1984.Data Sets - Support Documents
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