Psychological and Physiological Stressors and Factors
Level 2/3 Plan (DRAFT 2)
Outline of Contents
0. Overall Program Description
0.1 Background
0.2 Objectives
0.3 Approach
Level 3 Program Lead -
Dr. Al Ahumada (ARC/AFH)
2. Task 2. Cognitive Models and Metrics (548-50-42-xx)
Level 3 Program Lead - Dr. Roger Remington (ARC/AFI)
2.2.1 Eye-Movement Metrics of Human Cognition
2.2.2 Models and Metrics of Human Executive Control
2.2.3 Models and Metrics of Human Spatial Attention and Memory
3. Task 3. Physiological Factors (548-50-22/32)
Level 3 Program Lead - Dr. Mark Rosekind (ARC/AFS)
3.2.1 Fatigue Countermeasures (POC: M. Rosekind, ARC)
3.2.2 Hazardous States of Awareness (POC: A. Pope, LaRC)
0. Overall Program Description
0.1 Background
The coming increase in air space utilization and the corresponding need to reduce the
incidence of human and system errors is expected to place increasing stress on the
human operators and decision makers who directly interact with the air
transportation system. It is expected that existing technologies and procedures will be
inadequate to alleviate this stress at minimum cost and to reduce the incidence of
human error and potentially catastrophic system failure. Consequently, research into
novel displays, controls, and procedures is required to explore innovative techniques
for safe and efficient management of the increasingly dense air traffic system. This
element is intended to spark this innovation. It is divided into three sub-elements:
human perception, cognitive models and metrics, and physiological research.
0.2 Objectives
The Psychological/ Physiological Stressors and Factors research project goal is to
develop new technologies and procedures to measure and reduce this increased stress
within the air traffic system. Techniques will be developed to quantify the specific
errors that the stress may cause. Knowledge will be developed that will enable
innovative technologies and procedures that may be integrated into the national air
transportation system to preserve its integrity. Stress is not simply considered to be
the psychological stress of operators who have to deal with increasingly frequent
takeoffs and landings, but it also includes the increasing visual clutter of the
electronic displays they use and the increasing aural clutter of the audio channels.
Research conducted on the enumerated elements below will 1) develop
computational tools that will better allow the aeronautical community to analyze the
perceptual fidelity of the human machine interfaces that they use, 2) assist analysis
of
perceptual problems with existing displays, and 3) explore the utility of revolutionary
new perceptual display technology that may be adopted by the aeronautical
community in the next century.
0.3 Approach
The Psychological/ Physiological Stressors and Factors research project uses
analytical,
experimental and actuarial methods to measure and predict human performance
within all sectors of the nation's air transportation system. The human perception
sub-element focuses on development of new methods, computational models, and
metrics that will enable optimization of operator sensory-motor interaction with the
displays and controls of the national air space system. The cognitive model sub-
element focuses on models of the human operator information processing during
interaction with the air transportation system with the goal of understanding how
operator attention may focused or misfocused by the system. The physiological sub-
element will consider the role of physiologically based variation in alertness and
develop novel work rules to manage disturbances in operators' circadian rhythms
while working within the air transportation system. This sub-element will also
assess the impact of these innovative work rules.
In addition to the usual publication of technical reports and scientific journal
articles,
the results of the research and development conducted under the Elements below
will be disseminated to the aeronautical community through workshops and site
visits organized and conducted by the principal investigators.
Level 3 Program Lead - Dr. Al Ahumada (ARC/AFH)
1.1 Overall Task Description
1.1.1 Background
The human perceptual system carries information from the operator's environment
to his cognitive and action systems. Although the perceptual system gives us the
illusion of being in direct contact with "the real world," it is a complex
system that
uses heuristics to construct a world representation from sensory data that can be
sparse and unreliable without any such notification to the user. Understanding the
perceptual system is necessary to predict the performance of a human operator and
improve display interfaces.
1.1.2 Objectives
The goal of this program is to provide the aviation community with research and
technology in perceptual systems that allows scientific assessment of perceptual
system capabilities and fosters improved aviation display technology.
1.1.3 Approach
1) Develop improved methods for measuring perceptual system performance. 2)
Collect experimental data on perceptual system performance. 3) Develop
computational models and metrics that predict perceptual system performance. 4)
Develop display technologies that exploit understanding of perceptual systems.
1.2 Sub-Tasks
1.2.1. Sub-Task 1-1: Visibility Models
(POCs - Drs A. Watson and A. Ahumada)
1.2.1.1 Background
A frequently asked perceptual question is how visible a target, a display element, or
an image compression artifact will be in certain conditions. Sometimes
psychophysical measurements could be taken to answer this question, but often a
computational model is what the designer or system engineer really needs, because
the target system is not yet realized or the situations are too numerous.
1.2.1.2 Objectives
The goal of this program is to develop computational models which take as input
computer images or video sequences of such images, and give as output the
probability that an observer can see the difference between a pair of such images or
sequences or the probability that specific targets are detectable in such images.
1.2.1.3 Approach
The basic approach to the discrimination problem is obtain additional basic
discrimination data and then develop and calibrate the models so they account for the
data. The model development is guided by biological vision science as well as
psychophysical measurements. While the discrimination models are intended to
reflect the limitations of sensory processing, target detection involves the selection
of
target features as a function of the image content. Techniques will be further
developed to examine the learning of target features, to identify observer target
templates, and to predict detection performance in noisy or cluttered images when
these processes become important.
1.2.1.4 Level 3 Milestones
FY98- Contrast-gain control visibility model
FY99-Time domain extension of the contrast-gain control visibility model
FY00-Color extension of the contrast-gain control visibility model
FY01-Template learning extension of the contrast-gain control visibility model
FY02-Public domain distribution of the contrast-gain control visibility model
FY03-Shape perception module
1.2.2 Sub-Task 1-2: Eye-Movement Metrics of Human Perception
(POCs: L. Stone, J. Mulligan, and B. Sweet)
1.2.2.1 Background
Although our visual space appears to be a wide-field detailed representation, it is ac-
quired by active motion of the eyes, whose total spatial resolution is comparable to
standard TV resolution. Research in relating the motion of the eyes to perception
and in smarter eye movement measuring devices allows both the possibility of veri-
fying display feature perception and the possibility of adjusting the information dis-
played as a function of involuntary and voluntary eye movements.
1.2.2.2 Objectives
Establish the relationships between eye movements, perception and construct predictive
models of the interaction of the eye movement control and displayed information.
1.2.2.3 Approach
Psychophysical experiments correlating eye movement measurements with observer
judgments and control responses will be used to develop and validate models. They
will be used to develop guidelines for eye movement controlled information display.
1.2.2.4 Level 3 Milestones
FY98-Quantitative validation of eye-movement metrics of motion perception
FY98-Quantitative validation of eye-movement metrics of spatial localization
FY99-Calibration algorithm for combined eye/head tracking
FY99-Model of display-induced errors in manual control
FY00-Measure display effects on temporal dynamics of eye movements
FY00-Model of human eye movements during search
FY01-Guidelines for using eye-movement metrics for display design
FY02-Guidelines for using eye-movement feedback during training
FY03-Guidelines for hands-free eye-movement interfaces
1.2.3 Sub-Task 1-3. Image Processing for Improved Displays
(POCs Drs. A. Watson, A. Ahumada, J. Mulligan)
1.2.3.1 Background
Models of the visual system can be used to improve image processing technologies.
Although this application can be done by the developers of such technologies, often
such application is greatly facilitated by simplifications of the models for the
specific
application and the simplification needs to be tested psychophysically in its
application.
1.2.3.2 Objectives
Use the vision models to develop image quality metrics for specific image processing
applications and then develop metric-based image processing technologies for
improved display interfaces.
1.2.3.3 Approach
To keep the models computationally manageable, simplified versions of the models
are developed for specific applications. Three kinds of simplification are being used:
- 1) Frequency transforms, such as the discrete cosine transform and the wavelet
transform, are used as approximations to the cortical representation.
- 2) Aggregation of error is simplified as either a maximum rule, for search
simplification, or squared error, which is little affected by the transform used.
- 3) Complexities of the visual system are ignored when they can be.
1.2.3.4 Level 3 Milestones
- FY98-Public domain JPEG optimization software
- FY99-Simplified image quality model for compression
- FY00-Video quality metric
- FY01-Perceptual optimization of MJPEG and MPEG video compression
- FY02-Refined temporal error diffusion algorithm
- FY03-Wavelet-based image/video quality metric
1.2.4 Sub-Program 4. Metrics and Models of Range and Closure Perception
(POCs M. Kaiser and B. Sweet)
1.2.4.1 Background
The ability of humans to reliably and accurately estimate target range and closure
rates is relied upon by many vehicular control tasks. In modern aircraft, pilotage is
often based on synthetic displays rather than contact displays; further, there is are
strong incentives to maintain airline operations even when visual conditions
become degraded. Thus, it is critical to understand how pilots extract range and
closure rate information from contact and perspective displays, and how these
processes are impacted when information sources are degraded, absent, or in conflict
with other visual cues.
1.2.4.2 Objectives
The program goal is to provide guidelines for perspective displays for vehicular
control, and evaluation tools to determine the likelihood of pilot
error/disorientation under various display and visibility conditions.
1.2.4.3 Approach
Develop models for human performance and evaluate their ability to predict human
performance (especially errors) in low, mid, and high-fidelity vehicle control
simulations.
1.2.4.4 Level 3 Milestones
- FY98-Preliminary human depth-Cue model
- FY98-Control/analysis software to examine depth-cue integration during active
control tasks
- FY99-Validation of depth-cue integration model
- FY99-Refined analysis tools for examining depth-cue integration
- FY00-Refined depth-cue integration model
- FY01-Extension of depth-cue model to cue conflict situations
- FY02-Assessment of depth-cue integration model robustness across individuals and
situations
- FY03-Guidelines and evaluation tools for 3-D displays to ensure accurate pilot depth
perception
1.2.5. Sub-Program 5. Metric and Models for the Perceptual Design of Virtual
Transparency
(POC S. Ellis and M. Kaiser)
1.2.5.1 Background
Commercial aviation operations are often constrained by poor visibility due to
weather conditions. Modern sensors, however, make it possible to accurately detect
the position and orientation of a sufficient number of relevant aircraft for ATC
system planners to contemplate new "electronic" flight rules. Under these
rules
flight operations could safely continue despite instrument meteorological conditions
that would otherwise shut down or restrict safe aircraft operation. These new
sensors, such as ground radar or infrared vision systems, provide spatial data that
must be processed by information systems to schedule and space individual aircraft.
But results of the scheduling and spacing algorithms need to be monitored by human
operators who ultimately have responsibility for safe operation of the air
transportation system. This need is particularly salient for air traffic control tower
operation which may become highly restricted during low visibility conditions, but
corresponding needs for cockpit operation in modern commercial aircraft with
restricted visibility also exist.
1.2.5.2 Objectives
The goal of this sub-element is to determine new psychophysical knowledge and
devise new wide field of regard (FOR), i.e. > 180 degrees, visual display technology
that will allow perceptually accurate, presentation of spatially conformal aircraft
position information so that VFR-like operations can be extended into low visibility
conditions and to condition in which line of sight contact with aircraft is blocked by
obstructions. This knowledge will enable the design of virtual objects displays that
will allow operators accurately to see aircraft through fog and physical obstructions.
Thus, the fog and obstructions will be made to appear transparent but the range and
direction of the aircraft of interest will be accurately displayed.
1.2.5.3 Approach
Initially, a functional testbed for presenting spatially conformal, virtual image
information in an unlimited field of regard will be constructed. It will be used for
psychophysical testing of the speed and accuracy with which direction and distance
information may be presented via virtual objects made to appear visible though fog
and physical obstruction. The psychophysical and oculomotor parameters of the
displayed virtual objects will be investigated to determine those settings that allow
most accurate spatial perception with acceptable visual fatigue.
1.2.5.4 Level 3 Milestones
- FY98-Testbed for wide field of regard (FOR) presentation of virtual objects
- FY98-Psychophysical optimization of view parameters for depth presentation w/ wide
FOR
- FY99-Empirical model for accurate depth-direction perception in conditions of
transparency
- FY99-Analysis of depth-cue integration under conditions of transparency
- FY00-Extension depth-cue integration model to nearby virtual objects
- FY01-Extension of depth-direction model to unlimited FOR situations
- FY02-Study of individual differences in depth-direction perception while using wide
- FOR virtual object displays.
- FY03-Guidelines and evaluation tools for wide FOR displays to ensure accurate depth
and direction perception during aircraft and tower operation
1.2.6. Sub-Program 6. Spatial Auditory Displays
(POC: E. Wenzel)
1.2.6.1 Background
The flight deck environment contains multiple channels of auditory and visual
information that must be accessed under high-stress, high-workload conditions. The
difficulty of segregating monaural audio channels in high level noise can necessitate
repeated commands, cause mistakes in communication, and thereby compromise
safety as well as audiological health. Visual head-down displays such as those for
TCAS may be improved by assigning or co-assigning some situational awareness and
alerting functions to a spatial auditory display that allows the pilot's eyes to be out
the
window during the information acquisition.
1.2.6.2 Objectives
Develop auditory displays that prioritize and spatially segregate auditory information
for improved intelligibility and for possible eyes-out-the-window advantages.
1.2.6.3 Approach
Combining 3-D audio technologies with active noise cancellation, the auditory
display system controllers can be improved by examining prototype systems in part-
task and model simulations. Separate channels of auditory information will be
placed at different virtual locations to provide situational awareness (e.g., airborne
or
ground traffic collision avoidance alerts; taxiway navigation aids and
announcements);increase intelligibility (through the use of binaural delivery
systems);and reduce auditory fatigue. The simulations studies will be supplemented
by basic research in human sound localization and acoustic modeling of the cockpit
environment.
1.2.6.4 Level 3 Milestones
- FY98-Complete 3D audio collision avoidance study
- FY99-Calibrated flightdeck acoustic model
- FY00-Design and evaluation of localized auditory alerts
- FY01-Complete measurement of intelligibility as a function of auditory display and
background noise conditions
- FY02-Guidelines for improving intelligibility with spatial auditory displays
- FY03-Design specifications for critical spatial auditory display system components
1.2.7 Easy Access to Human Factors Databases (POC: ????)
1.2.7.1 Background
Human Factors knowledge is often not incorporated into the design of systems with
which human operators closely interact at an early stage of the overall design process.
As a consequence, human machine interaction with these systems is often
suboptimal and sometimes intolerable. An example of a severe difficulty of this type
is found in the human factors problems encountered in the first attempt to duplicate
the function of the ATC controllers flight strips on a computer display. One reason
for the difficulty of incorporating up-to-date human factors knowledge has been its
relative inaccessibility and the fact that it is often expressed in terms that obscure
its
application to specific purposes.
1.2.7.2 Objectives
The objectives of this subelement is to improve ATC systems designers ease of access
to relevant, new human factors knowledge and expertise so that it may be efficiently
and effectively incorporated into the design of new ATC technology.
1.2.7.3 Approach
The improvement in access to human factors expertise and data will occur through
the development of WEB-based pages corresponding to all of the subelements in this
project and which will be maintained by each subelement's PI. These pages will
contain the essential reporting information required for the program and will
provide pointers to the technical details of the activities on the WEB and elsewhere.
1.2.7.4 Level 3 Milestones
- FY98-Complete installation of skeleton WEB sites for each subelement
- FY99-Analyze the ease/frequency of access to WEB information,/redesign
- FY00-Maintain WEB sites
- FY01-Maintain WEB sites
- FY02-Maintain WEB sites
- FY03-Maintain WEB sites and publish report on their communication effectiveness
2.Task 2. Cognitive Models and Metrics (548-50-42-xx)
Level 3 Program Lead - Dr. Roger Remington (ARC/AFI)
2.1 Overall Task Description
2.1.1 Background
Human error is the causal or contributing factor in the majority of aviation accidents.
It is now well understood that these errors are the product of both the propensity of
human to make errors and specific design features that may induce errors. Attempts
to reduce human error by improved design have met with only partial success. A
significant obstacle to error tolerant design is the complexity of human behavior
itself. Simple tests of system interfaces are insufficient to uncover the wide range of
errors human operators will make in using them. The nature of human error in
aircraft accidents is often puzzling since the crew typically will have performed the
same sequence of tasks many times. Thus the accident data shows a seemingly
capricious tendency for error, making the measurement of the benefit of new error
tolerant systems problematic. For the same reasons, simulations often fail to provide
adequate estimates of human error, yet simulations remain the most useful means of
examining human behavior in circumstances approximating operational condition.
Complexity affects simulations in an additional way: it is difficult to measure and
quantify important aspects of human behavior because of the variability inherent in
complex performance. Improved understanding of how errors are generated in
performing tasks would facilitate the design of error tolerant (or error resistant)
systems. Improvements in measuring complex performance will be necessary to
adequately test new designs.
2.1.2 Objectives
The proposed work seeks to
- 1) model the cognitive components of task execution,
- 2) use the model to explore sources of human error, and
- 3) explore new techniques for
measuring complex performance.
2.1.3 Approach
We approach the task of understanding human error by noting that many instances
of error reflect failures of executive control. In some cases this failure leads to
certain
classes of memory errors, such as a failure to remember intended actions (prospective
memory failures), as well as habit capture error. A review of ASRS incidents revealed
a significant number of such memory failures. In other cases, routine behavior is
carried out but without active executive control. This class is most clearly evidenced
by monitoring failures, where the observer may actually look at an information
source but not apply the executive control needed to process the information.
Examination of NTSB accident reports shows that in almost all cases failure to note
obvious discrepancies or the failure of the pilot not flying to perform cross-checks
are
cited as causal or contributing factors in the accident.
In current theories of human cognition, executive control is associated with limited-
capacity attention-demanding aspects of information processing and responding.
Some aspects of processing can proceed independent of executive control, but except
in very special cases cannot control behavior without the intervention of executive
control (attention). Common cognitive acts such as fetching items from memory,
reading text, solving problems, etc., all require some involvement of executive
control, while some early perceptual processes and low-level motor behaviors can
often proceed without executive control. The dissociation between executive control
and motor programs leads to particular kinds of error, such as the familiar situation
of going through the motions of reading a passage without comprehension. A better
understanding of the relationship between executive control and the more
autonomous information gathering and motor behaviors would lead to significant
advances in our understanding of human error. One pressing question is the
identification of specific task actions which require attention. The abstract stage
models developed through empirical experimentation can be elaborated through
imaging techniques that record brain activity directly.
Many important cognitive variables are not directly observable. This has impeded
progress in cognitive theory development. Recent advances in brain imaging
techniques promise new and largely unobtrusive techniques for identifying
underlying processing, even in complex tasks such as piloting. The feasibility of these
techniques should be examined. In order to examine the relationship between
executive control and information gathering it will be necessary to determine the
relationship between eye fixations and attention, since important questions involve
the nature of the information acquired outside of controlled processing. This will
require the application of eye movement recording. Finally, some of the variability in
complex behavior may be due to the lack of sequential constraints in the tasks
themselves. While it may seem that behavior is varying, experts may be uniform in
the sequencing and timing of specific actions. Indeed, the degree to which tasks
impose sequential restrictions may interact with memory or cognitive agenda
management to influence errors. It is important to develop measures that assess the
variability of human performance against the variability permitted by the task.
We propose to address the question of executive control and of measurement
through a research program that includes both empirical research and modeling.
Major areas of research are described below with their objectives, and resource
requirements.
2.2 Sub-Tasks
2.2.1 Sub-Task 2-1: Eye-Movement Metrics of Human Cognition
(POCs: R. Remington, J. Johston, L. Stone, J. Mulligan)
2.2.1.1 Background
Human error often arises from mistaken beliefs about the state of the world. These
beliefs, like other aspects of cognition, are not directly observable, posing a problem
for a cognitive analysis that could reveal the source of error. The pattern of
information acquisition from visual displays, as revealed by patterns of eye fixation,
promises to shed light on the cognitive processes that shape operator behavior, and
lead to the generation of human error.
2.2.1.2 Objectives
The goal of this element is to develop direct tests of the usefulness of eye movements
for inferring behaviors of interest. If successful, further efforts will be directed at
developing a system for using eye fixation patterns to infer cognitive state that can
be
applied to man-in-the-loop simulations. The ultimate goal is a validated technique
for finer analysis of operator information gathering strategies.
2.2.1.3 Approach
We first explore tasks for which the information requirements are well understood.
For example, by having controllers make judgments that entail the use of altitude
information we can test whether eye movements directly reflect information
gathering. Since altitude is available only in the data block, fixations necessary to
read
the information will be necessary. If successful in using eye fixations to infer
cognitive goals, we will use a similar paradigm to examine conditions under which
controllers actively seek information as opposed to retrieving information from
memory. Models of human behavior have difficulty in deciding when information
will be gathered anew or existing information retrieved from memory. By varying
the relative difficulties and length of time since a particular piece of information
was
used, it will be possible to better understand how mistaken impressions of aircraft
state can occur in the face of clearly disconfirmatory evidence.
2.1.3.4 Level 3 Milestones
- FY98 Set-up of Eye-Movement Laboratory
- FY98 Validation of Eye-Movement Metrics of Information Gathering in a Controlled
Task
- FY00 Computational Model Relating Eye-Movements to Cognitive Strategy,
Memory, amp; Errors
- FY01 Extend Eye-Movement Cognitive Metrics to Head-Free Eye-Tracking System
- FY02 Validation of Eye-Movement Cognitive Metrics to Complex Real-World
- FY03 Delivery of Hardware/Software Tools for Cognitive Workload Assessment
Based on Eye-Movement Metrics
2.2.2 Sub-Task 2-2: Models and Metrics of Human Executive Control
(POCs: R. Remington, J. Johston)
2.2.2.1 Background
The allocation of attention and executive control is at the center of our understanding
of how information is selected from the world. This in turn determines the
knowledge of the user with respect to the state of the world at any point in time. Here
we address the issue of how external stressors influence the allocation of executive
control. In particular we focus on the role of time pressure in determining how
operators sequence between tasks and information sources.
2.2.2.2 Objectives
Extend and validate the APEX model of executive control by specifying the role of
executive control in cognitive processing and how control failure leads to human
error in complex task environments.
2.2.2.3 Approach
Our hypothesis is that time pressure leads to a truncating of normal processing,
leading to a first-come-first-served task allocation strategy. We pursue this by both
empirical testing, by modeling, and by direct observation of brain activity. The
existing APEX model of executive control developed in the Cognition Laboratory at
NASA Ames will be refined and used as the basis of modeling.
2.2.2.4 Level 3 Milestones
- FY98 Analysis of Time-Pressure Effects on Human Errors in an ATC-like Task
- FY98 Complete Test of 3-stage Information Processing Models by Measuring Brain
Activity (FMRI)
- FY99 Analysis of time-pressure effects on monitoring task
- FY99 Identify multiple loci information bottlenecks by recording brain activity
- FY00 Examine Brain Activity Correlates of Time-Induced Omission Errors
- FY00 Analysis of Spatial Display Effects on Distribution and Allocation of Attention
- FY01 General Model of Executive Control
- FY02 Develop/Test Workload Metric Integrating Empirical Testing, Eye Movements,
and Brain Recording
- FY03 Validate Workload Metric in Full-Mission Simulation
2.2.3 Sub-Task 2-3: Models and Metrics of Human Spatial Attention and Memory
(POC: W. Johnson)
2.2.3.1 Background
Two and three dimensional spatial displays of traffic, weather, and terrain are
expected to become common on flight decks in the next 10 years. These displays are
also expected to provide information such as heading, altitude (for 2-D displays),
speed, expected flight path, threat/conflict level, etc., and ATC airspace
restrictions. A
significant requirement of such cockpit displays is that they provide the necessary
information and quot;situational awarenessquot; without forcing the pilots into a
quot;heads-
downquot; mode. That is, these displays must not require prolonged withdrawal of
attention from primary flight tasks. Optimal displays need to be designed such that
they enhance attention to critical elements, and thus allow greater efficiency during
periodic monitoring. Two of the primary determinants of attention on displays are
simple salience and display organization, or structure. Determining how these two
properties influence attention individually, and in combination, will aid in the
design of more optimal displays.
2.2.3.2 Objectives
The goal of this project is to measure attentional distribution over a spatial display
as
a function of salience (various forms of highlighting), and as a function of display
structure (frames of reference and grouping properties), and then to generate a
corresponding predictive model of attentional distribution.
2.2.3.3 Approach
Experiments will be run correlating highlighting characteristics (intensity, motion,
color) and display structure (grouping, absolute vs. relative reference frame) with
measurements of information detection accuracy /latency, information retention,
and also with eye-movements. This data will then be used to develop predictive
models of attentional allocation for display design.
2.2.3.4 Level 3 Milestones
- FY98: Develop metrics of salience-driven information acquisition and retention from
global display contents.
- FY99: Measure effects of display highlighting methods (motion, brightness, color) on
information acquisition and retention.
- FY00: Model human information acquisition and retention as a function of display
highlighting methods
- FY01: Extend metrics to include structurally-driven information acquisition and
retention from global display contents.
- FY02: Measure joint effects of display structure and highlighting on information
acquisition and retention
- FY03: Model joint effects of display structure and highlighting on information
acquisition and retention
3. Task 3. Physiological Factors (548-50-22/32)
Level 3 Program Lead - Dr. Mark Rosekind (ARC/AFO)
3.1. Overall Task Description
3.1.1 Background
Flight operations create fatigue, sleep loss, and circadian disruption leading to
significant decrements in alertness and performance. Furthermore, the performance
problems can occur before the degraded alertness is even detected and reversed. By
increasing the chances of an accident or incident, these alertness and performance
decrements reduce the margin of safety.
3.1.2 Objectives
The goal of this program is to understand the physiological underpinnings of fatigue,
circadian rhythm disruption, and faltering alertness, to determine their operational
effects, and to provide the aviation community with a range of products from
research findings to countermeasure strategies and policy input to minimize adverse
effects, maximize performance and alertness during operations, and maintain or
improve the safety margin.
3.1.3 Approach
- 1) Conduct an integrated program of laboratory, simulation, and field studies
- 2) Use physiological, performance, behavioral, self-report, and environmental measures to
assess levels of fatigue and circadian disruption.
- 3) Use these measures to evaluate the effectiveness of countermeasures, including new technologies. 4) Transfer
results to operational use through diverse mechanisms
3.2. Subtasks
3.2.1. Fatigue Countermeasures (POC: M. Rosekind)
3.2.1.1 Background
Flight operations create fatigue, sleep loss, and circadian disruption that lead to
reduced performance, alertness and safety. The Fatigue Countermeasures Program
directly supports safety goals through the development of fatigue countermeasures,
educational tools, incident/accident investigation methods, and providing technical
input to national policy considerations.
3.2.1.2 Objectives
The objective of the Fatigue Countermeasures Program is to minimize the adverse
effects of fatigue and maximize performance and alertness during flight operations,
thereby maintaining, and where possible, improving the safety margin. This
objective is accomplished through the following activities:
- 1) determining the operational effects of fatigue, sleep loss, and circadian disruption,
- 2) developing and evaluating fatigue countermeasures,
- 3) developing and transferring educational
tools to the operational communities,
- 4) conducting research to investigate the full range of fatigue issues in aviation environments,
- 5) providing technical input to
accident investigation methods and to national policy regarding crew flight/duty/rest
considerations.
3.2.1.3 Approach
The Fatigue Countermeasures Program conducts a complementary research approach
that capitalizes on laboratory-based experimental research, flight simulations, and
field research during regular operations. Ground-based, controlled laboratory
investigations allow safe examination of operational issues (e.g., total and cumulative
sleep loss) that could not be conducted in field studies. Operational/flight research
involves intensive investigation of fatigue factors during actual flight and field
operations. Flight simulations provide a setting for collecting operational flight
variables in study manipulations that would not be possible or safe during regular
operations. A variety of physiological, performance, behavioral, self-report,
environmental, and survey measures are used in all of these research approaches.
3.2.1.4 Level Milestones
- FY98 Techology Transfer via Industry Education and NTSB/Stanford/NASA
Workshop
- FY99 Complete Simulation Study of Active Alerting Strategy
- FY00 Complete Split Sleep Study
- FY01 Complete Study on Bunk vs Seat Sleep
- FY02 Complete Study on Effects of Short Callout on Pilot Performance
- FY03 Complete Field Study on Biomathematical Models of Sleep, Circadian Rythms,
and Performance
3.2.2. Hazardous States of Awareness (POC: A. Pope)
3.2.2.1 Background
The Hazardous States of Awareness subelement develops and validates human
response measurement technologies for assessing human attention and awareness
hazards. The effort develops methods for identifying task design factors associated
with task underload, and identifies and tests crew procedural and system design
factors which contribute to effective and hazardous states of awareness. These
activities are in support of the goal of the Critical Technologies Program of the NASA
Implementation Plan for the National Plan for Civil Aviation Human Factors (p. 34),
and Recommendations SA-8 and SA-9 of the FAA Human Factors Team Report on
The Interfaces between Flightcrews and Modern Flight Deck Systems.
3.2.2.2 Objectives
The objective of this subelement include 1) Development and validatation of
methods and techniques for identifying hazardous states of awareness, such as
complacency, boredom, and preoccupation, in automated-system design
and 2) the exploitation of opportunities to demonstrate dual-use applications of
methods, techniques and principles in fields within aeronautics as well as beyond,
such as process control and medicine
3.2.2.3 Approach
The approach taken includes establishing basic concepts and theories, developing and
validating new concepts in collaboration with universities, proving innovative
techniques through analysis, simulation, and laboratory testing, and, ultimately,
demonstration of the most promising concepts in operational environment tests.
Technology transfer mechanisms include demonstrations of methodological
innovations to industry and media at LaRC and at technology transfer expositions,
MOA as described below, and contributions to transfer publications and databases.
Metrics include number of requests from customers and partners in aerospace and
non-aerospace industries for our technology, and number of actual uses by
customers.
3.2.2.4 Level Milestones
- FY98 Demonstrate crew engagement assessment technology
- FY98 Complete identification and analysis of Mode Awareness issues
- FY99 Evaluate adaptive task allocation design options for reduced automation-
related complacency
- FY00 Complete review of psychophysiological approaches to adaptive interface
control
- FY01 Demonstrate adaptive task allocation design options that influence automated-
related complacency
- FY02 Validate mode confusion reduction with vertical profile display concept
- FY03 Demonstrate physiological forecast of performance decrement resulting from
workload transitions