12: Adjunct Proceedings - Automotive User Interfaces and ...

Tutorial: Driver Distraction
Bryan Reimer
MIT AgeLab & New England University Transportation Center
77 Massachusetts Avenue, E40-291
Cambridge, MA 02139
011 617 452-2177
reimer@mit.edu
ABSTRACT
This tutorial will briefly introduce: (1) the evolution of driver
distraction, (2) key definitions that have been proposed, (3)
research methods used in the assessment of distracted driving, (4)
the sensitivity of different techniques for measuring user interface
demand, e.g. eye tracking, physiological monitoring, task and
driving performance, (5) differences in the expression of visual,
manipulative and cognitive demands on driving behavior, and (6)
current governmental and industrial efforts to reduce distracted
driving.
Keywords
Eye-tracking, physiology, driver behavior, task performance,
safety
1. INTRODUCTION
The topic of distracted driving has been around since the early
days of the automobile. In 1930 Nicholas Trott wrote in the New
York Times, “A grave problem that developed in New
Hampshire… now has all the motor-vehicle commissioners of the
eastern states in a wax. It's whether radios should be allowed on
cars. Some states don't want to permit them at all—say they
distract the driver and disturb the peace…The [Massachusetts]
commissioner thinks the things should be shut off while you are
driving…The whole problem is getting very complex, but the
upshot is that you'll probably be allowed to take your radio
anywhere, with possibly some restriction on the times when you
can play it.” The technologies that can distract drivers have
arguably increased in complexity since Trott’s day, but the debate
on what interactions are appropriate to complete safely while
driving remains largely intact today. While thousands of articles
have been written on the topic, it is essential that researchers
consider numerous factors when interpreting the literature.
2. OVERVIEW OF THE TUTORIAL
Traditional, experimental research on distracted driving has
largely focuses on assessing behavior changes with a moderate to
high distraction task, e.g. drivers react more slowly when on a cell
phone [6]. In other lines of research effects of demands are
difficult to interpret, as attentive drivers may not fully engage in
the task at hand [2]. The optimization of interfaces to minimize
driver distraction requires a broader understudying of the
problem. The larger question is, at what level of demand does a
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AutomotiveUI'12, October 17-19, Portsmouth, NH, USA.
Copyright (c) 2012 ACM 978-1-4503-1751-1/12/10 ... $15.00
12
Adjunct Proceedings of the 4th International Conference on Automotive User Interfaces and
Interactive Vehicular Applications (AutomotiveUI '12), October 17–19, 2012, Portsmouth, NH, USA
driver’s behavior begin to be affected? Recent work [2, 4] shows
that driver behavior is impacted by the simple activity of repeating
a series of numbers (0-back).
The content of this tutorial will be geared towards providing
participants with an overview of important considerations in the
development of empirical research and the interpretation of
previous research on distracted driving. Emphasis will be placed
on understanding the appropriate use of techniques to provide
sensitive measures of driver behavior. Illustrations of previous
research will be presented where appropriate. Effort will be placed
on providing attendees with an understanding of the effective use
of different techniques for measuring demand and potential
pitfalls.
3. SUGGESTED READING
For a comprehensive discussion on factors involved with driver
distraction [3] is a good desk reference. Suggested reading in
preparation for this tutorial include the topic of task duration [1],
eye tracking and glance based analysis of visual demands [5], and
the impact of cognitive demands on physiology, visual attention
and driving performance [2, 4].
4. REFERENCES
[1] Burns, P., Harbluk, J., Foley, J., and Angell, L. (2012). The
importance of task duration and related measures in assessing
the distraction potential of in-vehicle tasks. Proc. Second
International Conference on Automotive User Interfaces and
Interactive Vehicular Applications (AutomotiveUI '10).
[2] Mehler, B., Reimer, B., and Coughlin, J.F. (2012).
Sensitivity of physiological measures for detecting
systematic variations in cognitive demand from a working
memory task: an on-road study across three age groups.
Human Factors, Vol. 54, 3, 396-412.
[3] Regan, M.A., Lee, J.D., and Young, K.L. 2009. Driver
distraction: theory, effects and mitigation. Boca Raton, FL,
CRC Press.
[4] Reimer, B., Mehler, B., Wang, Y., and Coughlin, J.F. (2012).
A field study on the impact of variations in short-term
memory demands on drivers' visual attention and driving
performance across three age groups. Human Factors, Vol.
54, 3, 454-468.
[5] Sodhi, M., Reimer, B., and Llamazares, I. (2002). Glance
analysis of driver eye movements to evaluate distraction.
Behavior Research Methods Instruments & Computers, Vol.
34, 4, 529-538.
[6] Strayer, D.L. and Drews, F.A. (2004). Profiles in driver
distraction: Effect of cell phone conversation on younger and
older drivers. Human Factors, Vol. 46, 4, 640-649.