Unpacking Situation Awareness: Improving Diagnosis and Assessment of Older Drivers’ Perception, Comprehension, and Projection Failures in a Specific Driving Scenario
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Description: | Models of situation awareness (SA) and
constructs originated in aviation domain, not originally intended for the
driving task. Situation awareness is defined as “the perception of elements in
the environment within a volume of time and space, the comprehension of their
meaning, and the projection of their status in the near future” (Endsley, 1995). Endsley described three levels of
SA: perceiving critical factors in the environment (level 1), determining
critical factors’ significance in relation to user’s goals (level 2), and
understanding how these critical factors will affect the user’s goals and
projecting this system’s behavior in the near future (level 3).
The boundaries
between these levels of SA in the driving task, where the environment is more
populated with potential hazards (e.g., other drivers, pedestrians, etc.), are
not as well-delineated as they are within the aviation realm. That is, the driving
task’s more dynamic demands lead to more potential overlap between the perception
and comprehension levels relative to aviation task, and most likely need to be
more quickly followed by evasive/corrective action (e.g., a car pulling out in
front of the driver unexpectedly vs. a pilot realizing a fuel leak by noting
the fuel gauge for one engine is depleting faster than the other engines). Identification
and correction of older drivers’ SA-related deficits stand to benefit from more
sensitive measures focused on the levels of SA specific to the driving task, as
opposed to the construct at large.
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Objective: | To explore and develop
possible convergent measures in a driving simulator equipped with eye-tracking
capability that reveal gaps in driving skill that can be related to perceptual
or comprehension processes. These measures may then be used to evaluate technological
systems or training regimens aimed at assisting older drivers in maintaining SA
in driving situations that are problematic to this age group.
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Benefits: | Developing measures that identify the specific
level of SA (e.g., perception, recognition, or projection) that is deficient within
the individual, specific failure points in a particular driving scenario, as
well as evaluate technology that can augment these SA components at these
failure points.
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Related Research: | Endsley,
M. R. (1995). Toward a Theory of Situation Awareness in Dynamic Systems. Human
Factors: The Journal of the Human Factors and Ergonomics Society.
doi:10.1518/001872095779049543
Stanton,
N. A., Salmon, P. M., & Walker, G. H. (2014). Let the Reader Decide: A
Paradigm Shift for Situation Awareness in Sociotechnical Systems. Journal of
Cognitive Engineering and Decision Making. doi:10.1177/1555343414552297
Endsley,
M. R. (2015). Final Reflections: Situation Awareness Models and Measures. Journal
of Cognitive Engineering and Decision Making, 9(1), 101–111.
doi:10.1177/1555343415573911
Liu,
Y.-C., & Cian, J.-Y. (2014). Effects of situation awareness under different
road environments on young and elder drivers. Journal of Industrial and
Production Engineering, 31(5), 253–260. doi:10.1080/21681015.2014.946103
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Tasks: | Review recent literature for methods of
differentiating and measuring the three levels of SA (perception,
comprehension, and projection).
Pilot left turn and/or merge tasks in a driving
simulator instrumented with eye-tracking capabilities to validate these
methods’ ability to differentiate between the levels of SA.
Obtain IRB approval, recruit young (18-30),
middle (40-60), and older participants (70+):
· Exclusion
criteria: medical condition with limiting severity, medications that affect
driving performance, failing Mini-Mental Status Examination score at
pre-screen.
· Inclusion
criteria: > 3 trips per week (defined as starting the car, driving to a
different location, and turning the car off), valid license
Recruit participants from the local area,
invite to the lab to participate in study, and obtain informed consent prior to
having them complete [specific driving task] and collect multiple types of data
(e.g., eye-tracking, objective driving measures, and concurrent verbal
protocols), analyze collected data, and write up results.
Establish useful next steps for using
these types of data to diagnose what level of SA needs intervention/
augmentation within a particular individual as well as evaluating the
assistance provided by in-vehicle technologies that might provide such help.
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Implementation: | Difficulty recruiting older adult samples
due to increased potential for simulator sickness. Proprietary nature of
manufacturers’ assessment methods of SA might be prohibitive to their
collection.
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Relevance: | We have no strong measures to evaluate the extent to which emergent ITS devices support specific levels of SA (particularly that of older adults) within the driving setting. This research informs the development of a metric to accurately measure SA at the perception, comprehension, and projection levels in the context of [whichever driving task we select] and the extent to which these burgeoning technologies support, rather than detract from, older adults’ SA while navigating [selected driving task].
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Sponsoring Committee: | ANB60, Safe Mobility of Older Persons |
Research Period: | 12 - 24 months |
Research Priority: | High |
RNS Developer: | Dustin Souders, Kathy Sifrit, Jack Joyce, & Jon Antin |
Source Info: | Review of SA, hazard perception, and distraction literatures using Google scholar, Web of Science, and Psycinfo databases. |
Date Posted: | 09/13/2015 |
Date Modified: | 11/13/2015 |
Index Terms: | Aged drivers, Alertness, Perception, Mobility, Pedestrian traffic, Driving, |
Cosponsoring Committees: | |
Subjects |
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Highways
Safety and Human Factors
Society
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