A number of members of AgeLab and New England University Transportation Center staff travelled to Seattle in September to present newly published papers at the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (Automotive UI): a premier forum for research in the user interface field of vehicular applications. The conference was in part sponsored by the New England Center (Region 1) and Pacific NW Transportation Consortium (Region 10).
Bryan Reimer and Bruce Mehler started out by highlighting an exciting new app meant to make the AgeLab’s n-back task more widely accessible to researchers and practitioners. The n-back task is a working memory calibration task that the AgeLab developed for the purpose of inducing graded levels of cognitive load that can be used in driving studies. In this task participants are asked to hold single digit numbers in memory and to repeat them back verbally after being presented with anywhere from 0 to 2 additional numbers to recall in sequence. The n-back task has been developed into an Android application for both experimental and demonstration purposes. Bryan and Bruce discussed the ease of distribution and versatile applications of the n-back app in detail at 4th annual Cognitive Load Workshop held as part of Automotive UI (Reimer, Mehler, Arredondo, et al.).
Alea Mehler then went on to present the findings of a study (Lee et al.) that showed drivers’ self- reported health and perceived well-being were better predictors then other demographic characteristics on experience and perceptions around technology. Results revealed that respondents who felt better about their overall health or well-being were more trustful towards technology in general, and felt as though they were more capable of quickly adapting to new technology compared to people who reported feeling weaker mentally or physically.
With this in mind, the staff moved on to three more technologically based papers coming out of the AgeLab’s user interface and usability studies. These studies, while different in their individual goals, can work together to make interface usability in cars more practical, and safer. More easily perceived typefaces in vehicles could reduce the amount of time a driver keeps his or her eyes off the road, while voice navigation hopes to also decrease the amount of attention drivers need to allocate to interactions with vehicle systems.
First, Jon Dobres presented Dobres et al., a user interface study that studied the subtle yet important differences in on-screen typeface readability. Dobres’ paper examined simplified typefaces in Chinese as an example of his methodology that can be used to determine relative differences in legibility between typefaces and display conditions for text that is going to be read quickly on in-vehicle screens.
Next, Bruce Mehler presented Munger et al., which examined physiological arousal, detection response times, and driving performance metrics between manual and voice-activated GPS destination entry on a smartphone. The analysis found that while utilization of the voice interface options impaired a driver’s ability to respond to detection task as compared to just driving, the impairment was significantly less than was observed with manual input controls. However, destination entry regardless of the input method causes an increase in physiological arousal as compared to just driving.
Finally, Bryan Remier presented Remier et al., a paper focused on a more in-depth analysis of voice- control interfaces. In this specific study, Reimer compared the demands of two modes of a production level voice interface. In an “experienced” user mode, where the task interaction is streamlined, task completion times were reduced. However, the interaction did not reduce the amount visual engagement drivers had with the system over the default mode of operation. This research further illustrates the challenges involved in optimizing multi-modal interface demands across auditory-vocal- visual-manual and cognitive resources.
Dobres, J., Reimer, B., Mehler, B., Chahine, N., & Gould, D. (2014). A Pilot Study Measuring the Relative Legibility of Five Simplified Chinese Typefaces using Psychophysical Methods. Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicle Applications (AutoUI 2014), Seattle, WA.
Lee, C., Mehler, A., Reimer, B., Mehler, B. & Coughlin, J.F. (2014). Relationship between Drivers’ Self- Reported Health and Technology Perceptions Across the Lifespan. Adjunct Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicle Applications (AutoUI 2014), Seattle, WA.
Munger, D., Mehler, B., Reimer, B., Dobres, J., Pettinato, A., Pugh, B., & Coughlin, J.F. (2014). A Simulation Study Examining Smartphone Destination Entry while Driving. Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicle Applications (AutoUI 2014), Seattle, WA.
Reimer, B., Mehler, B., Dobres, J., McAnulty, H., Mehler, A., Munger, D., & Rumpold, A. (2014). Effects of an ‘Expert Mode’ Voice Command System on Task Performance, Glance Behavior & Driver Physiology. Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicle Applications (AutoUI 2014), Seattle, WA.
Reimer, B., Mehler, B., Arredondo, S., Gulash, C., Foley, J.P. & Waldmann, A. (2014). The MIT AgeLab n- back: a multi-modal android application implementation. Adjunct Proceedings of the the 6th International Conference on Automotive User Interfaces and Interactive Vehicle Applications (AutoUI 2014), Seattle, WA.