BibTex
@inproceedings{Gonz{\'a}lez:2007:10.1145/1268517.1268535,
author = {Gonz{\'a}lez, Iv{\'a}n and Wobbrock, Jacob and Chau, Duen and Faulring, Andrew and Myers, Brad},
title = {Eyes on the road, hands on the wheel: thumb-based interaction techniques for input on steering wheels},
booktitle = {Proceedings of Graphics Interface 2007},
series = {GI 2007},
year = {2007},
issn = {0713-5424},
isbn = {978-1-56881-337-0},
location = {Montr{\'e}al, Qu{\'e}bec, Canada},
pages = {95--102},
numpages = {8},
doi = {10.1145/1268517.1268535},
acmdoi = {10.1145/1268517.1268535},
publisher = {Canadian Human-Computer Communications Society},
address = {University of Waterloo, Waterloo, Ontario, Canada},
}
Abstract
The increasing quantity and complexity of in-vehicle systems creates a demand for user interfaces which are suited to driving. The steering wheel is a common location for the placement of buttons to control navigation, entertainment, and environmental systems, but what about a small touchpad? To investigate this question, we embedded a Synaptics StampPad in a computer game steering wheel and evaluated seven methods for selecting from a list of over 3000 street names. Selection speed was measured while stationary and while driving a simulator. Results show that the EdgeWrite gestural text entry method is about 20% to 50% faster than selection-based text entry or direct list-selection methods. They also show that methods with slower selection speeds generally resulted in faster driving speeds. However, with EdgeWrite, participants were able to maintain their speed and avoid incidents while selecting and driving at the same time. Although an obvious choice for constrained input, on-screen keyboards generally performed quite poorly.