DAVID LARGE David.R.Large@nottingham.ac.uk
Senior Research Fellow
Predicting the visual demand of finger-touch pointing tasks in a driving context
Large, David R.; Crundall, Elizabeth; Burnett, Gary; Skrypchuk, Lee
Authors
Elizabeth Crundall
Gary Burnett
Lee Skrypchuk
Abstract
Finger-touch based interactions with capacitive touchscreen devices in cars are becoming increasingly common. As such, it is critical to understand the basic human factors of target acquisition (pointing/touching) in this context. We describe a simulator study that aims to build Fitts’ Law relationships for predicting the visual demands (mean glance duration and total glance time) associated with finger-touch pointing tasks as a function of target size, location and design. The observed data show strong linear relationships between all visual demand measures and Fitts’ index of difficulty, indicating that finger-touch pointing tasks conform well with the Fitts’ Law model under conditions of divided attention. The derived equations are discussed in the context of designing in-vehicle touchscreen interfaces for minimal visual demand.
Citation
Large, D. R., Crundall, E., Burnett, G., & Skrypchuk, L. (2015). Predicting the visual demand of finger-touch pointing tasks in a driving context. In AutomotiveUI '15: Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (221-224). https://doi.org/10.1145/2799250.2799256
Presentation Conference Type | Conference Paper (Published) |
---|---|
Conference Name | The 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications |
Start Date | Sep 1, 2015 |
End Date | Sep 3, 2015 |
Acceptance Date | Sep 1, 2015 |
Publication Date | 2015 |
Deposit Date | May 9, 2019 |
Pages | 221-224 |
Book Title | AutomotiveUI '15: Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications |
ISBN | 9781450337366 |
DOI | https://doi.org/10.1145/2799250.2799256 |
Public URL | https://nottingham-repository.worktribe.com/output/2035741 |
Publisher URL | https://dl.acm.org/citation.cfm?doid=2799250.2799256 |
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