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Workload Factors
A characteristic of most post-transition periods is a large number of
task demands often imposed with very severe time constraints. These tasks
are often characterized by the description of high workload. The term
workload has intuitive meaning for most people; everyone has experienced
periods of high or low workload in their daily life in response to different
situations. Psychologists have invoked the concept in theories of attention
and performance. Aircraft designers, manufacturers, operators, and regula-
tory agencies have identified operator workload as a critical factor in sys-
tem effectiveness. However, the word workload did not appear in many
dictionaries until the 1970s; and operational definitions proposed by psy-
chologists and engineers continue to disagree about its sourcets), mechanisms,
consequenceLs), and measurement. Furthermore, although workload and
performance are clearly related, it has proven to be a much more complex
relationship than originally thought.
WORKLOAD CHARACTERISTICS
Sources
Over the past 20 years, workload has been equated with: (1) imposed
task demands if the difficulty, number, rate, or complexity of the demands
imposed on an operator are increased, workload is assumed to increase; (2)
the level of performance an operator is able to achieve if errors increase
or control precision degrades, workload is assumed to increase; (3) the
54
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WORKLOAD FACTORS
55
mental and physical effort an operator exerts-workload reflects an operator's
response to a task, rather than task demands directly; and (4) an operator's
perceptions if an operator feels effortful and loaded, then workload has, in
fact, increased even though task demands or performance have not changed.
Most contemporary definitions assume that workload emerges from the in-
teraction between a specific operator and the assigned task (Gopher and
Donchin, 1986; Hart, 1986; Hart and Wickens, 19901.
Consequences
The consequences of optimal or suboptimal levels of workload depend
on the structure of a specific task, the environment in which it is performed,
and operator characteristics. As task difficulty increases, performance of-
ten, but not always, degrades; response times and errors increase for dis-
crete tasks, control variability and error increase for tracking tasks, and
fewer tasks are completed within an interval of time. The workload im-
posed by one task may interfere with the performance of other concurrent
activities. The subjective experience of excessively low or high workload
may prompt operators to adopt different task-performance strategies. Pro-
longed periods of high workload may result in operator fatigue. An in-
crease in psychological stress that often accompanies high workload may
result in elevated heart rate.
Measures
To some extent, these apparent complexities have been caused by (1)
the practice of using the same term (workload) to refer to the demands
imposed on an operator; the effort exerted to accomplish those demands;
and the physiological, subjective, or performance consequences of an operator's
actions and (2) the naive assumption that different measures of workload
index the same entity. In fact, different measures are sensitive to different
aspects of workload and are appropriate for answering different questions.
Thus, the results of most workload studies are interpreted far too broadly,
given the complexity of the phenomena and the limited range of factors to
which each type of measure is sensitive. The problem is compounded by
the absence of a generally accepted definition, standardized procedures and
units of measurement, or an absolute standard against which to compare a
particular task or candidate measure.
Relationship Between Workload and Performance
Designers, manufacturers, and operators of complex systems have been
more interested in the association between workload and performance than
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56
WORKLOAD TRANSITION
in theoretical issues. They assume that human performance is most reliable
under moderate workload that does not change suddenly or unpredictably
(Kantowitz and Casper, 19884. When workload is too high, errors arise from
an operator's inability to cope with critical task demands. When workload is
too low, errors may arise from loss of vigilance and boredom (see Chapter 6~.
However, the actual relationship between the effort an operator invests in a
task and the performance he or she is able to achieve is much more complex.
O'Donnell and Eggemeier (1986) suggested that the relationship be-
tween workload and performance changes as overall task difficulty is in-
creased. For relatively easy tasks, operators can maintain consistent perfor-
mance by exerting additional effort if task demands are increased. For
moderately difficult tasks, they cannot maintain consistent perfo~-~ance even
if they exert additional effort. For extremely difficult tasks, operators do
not have the capacity to exert additional effort in response to further in-
creases in task demands, so performance decrements no longer reflect a
change in workload.
Navon and Gopher (1979) suggested that this relationship depends on
the structure of the task, differentiating between situations in which addi-
tional resource investment would (resource-limited) or would not (data-
limited) result in improved performance. For data-limited tasks, additional
effort cannot improve performance. If sufficient information is available,
the task can be performed. If it is not, the task cannot be performed ad-
equately. For resource-limited tasks, however, additional effort can result
in improved performance.
Hart (1989) and Hart and Wickens (1990) discussed the importance of
operator strategies in determining the relationship between workload and
performance. People may not try to achieve perfect performance or accom-
plish tasks immediately. Rather, they manage their attention and effort,
rescheduling, deferring, or shedding less important tasks to achieve accept-
able performance and maintain a reasonable level of workload for the dura-
tion of the task (see Chapter 9 for some discussion of how effectively this
scheduling is accomplished). In a recent interview, Broadbent (1990:7'
stated that humans are "dynamic, self-regulating systems, with each func-
tion monitored and modified by others." Thus, to optimize their interaction
with a complex system, operator beliefs, values, and intentions must be
considered. Because it is clear that humans have interests beyond optimiz-
ing traditional indices of system performance (Rouse, 1979), simple linear
models cannot provide an accurate description of their behavior.
Despite the apparent confusion about what workload is (one might fairly
say that anything can cause workload) and what its effects might be, there
are some factors that stand out as being particularly salient. The duties
assigned to the crews of tanks, helicopters, jets, nuclear power plants, and
so on impose a set of requirements that vary in magnitude alla composition
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WORKLOAD FACTORS
57
from one moment to the next, from one type of activity or mission phase to
another, and from one crew position to another. The operational require-
ments of the tank crew are composed of a variety of behaviors that have
been studied in isolation (in laboratory research) or in different combina-
tions (in simulation and field studies) to determine the specific task-related,
equipment-related, environmental, and operator-related factors that influ-
ence workload and performance. From this research, general principles
may be drawn to estimate the effects of performing specific activities on the
operators of a particular system performing a mission. The following pages
contain a review of data regarding the primary factors that drive workload,
showing how these drivers are relevant to a variety of transition teams.
WORKLOAD DRIVERS: REVIEW OF RESEARCH
The intrinsic difficulty of the activities that an operator must perform
establishes the target or nominal level of workload. The difficulty of a
particular task may be influenced by any one or several of the following
factors: (1) the goals and performance criteria set for a particular task; (2)
the structure of the task; (3) the quality, format, and modality in which
information is presented; (4) the cognitive processing required; and (5) the
characteristics of the response devices. Although the fundamental source of
workload is literally the "work" that is "loaded" on an operator, the behav-
ior and workload experiences of a particular operator may be influenced by
other factors as well. For example, fatigue, stress, training, crew coordina-
tion, and environmental stressors (e.g., heat, cold, vibration, noise, and dan-
ger) may have a significant impact on operator workload. Although the
influence of these factors is obvious in operational situations, little research
has been performed to establish their relationship with operator workload,
and they are ignored in most workload theories. The relationship between
these factors and team performance are reviewed in other chapters.
Given the limitations of human memory, vision, physical strength, and
so forth, some tasks may stretch or even exceed an operator's capacities;
other tasks impose so few demands that they may be performed concur-
rently with other tasks. Thousands of experiments have been conducted in
which a variety of task-difficulty manipulations were imposed to examine
different aspects of the human information processing system and to define
and quantify the limits of human capabilities. The following section sum-
marizes the results of a representative sampling of this work.
Task Structure
The way in which a task or combination of tasks is organized, the rate
at which information is presented or error signals change, the length of time
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WORKLOAD TRANSITION
the task must be performed, and the levels of speed and accuracy that the
operator must try to achieve have a significant impact on the workload
imposed during its performance. A significant number of the experiments
conducted to analyze human operators' responses to different levels of workload
have included some variation in the rate of presentation for discrete tasks or
disturbance bandwidth for control tasks. Thus, a considerable amount is
known about these factors. Relatively less information is available about
the effects of speed-accuracy tradeoffs, task schedules, and task duration.
Performance Criteria and Strategies
The difficulty of almost any task can be altered by a requirement for
additional speed or accuracy. As criteria for acceptable performance be-
come more stringent, the workload associated with attaining adequate per-
formance increases (Yeh and Wickens, 1988~. People may adopt either
externally imposed performance criteria or personal criteria (which may or
may not be more stringent). Workload and performance are influenced by
the objective consequences of failing to meet task requirements as well.
People are more likely to try to meet performance standards if their job or
personal safety are on the line, than if the consequence of poor performance
is simply a "bad score." In addition, operators may act less conservatively,
take more risks, and try new techniques when there are no dire conse-
quences of failure.
In general, manual controllers of dynamic systems such as the tank
driver try to follow a particular course or path, while minimizing the effects
of external disturbances. Error will increase if control inputs are too little,
too late, or in the wrong direction. If operators overcontrol (i.e., make
control inputs that are faster or larger than necessary), they create additional
workload for themselves (i.e., they must compensate for the errors that they
generate) and run the risk of destabilizing the system. Thus, although mini-
mizing error is the goal of most control activities, smoothness and stability
may be equally important.
Similarly, in discrete control tasks like target acquisition, performance
strategies can be described by a tradeoff between the speed and accuracy of
the movements. Faster movements are made with less accuracy, and more
precise movements are made more slowly. This tradeoff is described by a
mathematical model known as Fitts's Law. This relationship has proven to
be extremely robust (Keele, 1986) for a wide range of target types, widths,
and distances, limbs (e.g., fingers, arms), system dynamics (e.g., displace-
ment of the joystick controls cursor position or velocity), control devices
(e.g., computer mouse, joystick, rotary knob), and displays (e.g., computer
screen, direct view of nearby or distant target). More recent research has
demonstrated that Fitts's Law also holds for targets that vary dynamically in
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WORKLOAD FACTORS
59
size (Johnson and Hart, 1987) or position (Jagacinski et al., 1980~. A
similar relationship has been found between the movement difficulty and
subjective workload (Hart et al., 1984b; Johnson and Hart, 1987; Mosier
and Hart, 1986~.
Instructions to maximize either speed or accuracy influence the workload
and performance associated with discrete responses, target acquisition, and
continuous control. If operators are instructed or choose to maximize preci-
sion, the cost may be an increase in time for task completion. Conversely,
if they maximize speed, then accuracy may be reduced. Depending on the
situation, either speed or accuracy may be more important. Thus, the over-
all quality of performance depends on the operators' correct assessment of
which factor is most critical. For example, correctly identifying a target (as
friend or foe) is more important than firing quickly (and running the risk of
hitting a friend), even though verifying the identity of a target may take
longer than making a snap judgment. If the position of a helicopter or tank
is not yet known to an enemy, making the first shot count (e.g., accuracy) is
extremely important, as firing a weapon will reveal its position. Alterna-
tively, if a tank is being fired on or the engine of a helicopter fails, a rapid
response is essential. Smooth control and on-time arrival may be more
important to an airline pilot than keeping the needles precisely centered on
the intended flight path, while extreme precision is required to accomplish
inflight refueling.
Different components of a complex task may have different functional
priority with respect to the overall goals of the task or temporal priority (if
they are not completed by a deadline, they can no longer be performed at
all). Operators may adopt different resource allocation and scheduling strategies
to satisfy external instructions or personal goals. Within limits, people are
able to maintain a particular level of performance on one task (at the ex-
pense of another) or to share attention equally or in graded amounts be-
tween two tasks (Gopher et al., 1982~. They may adopt a fixed policy for
resource allocation or dynamically modulate it in response to changes in
task demands or priority over time. People are better able to dynamically
allocate the same resource across tasks in response to priority instructions
(e.g., devote more processing resources to a tracking task than to a concur-
rent running memory task) than to dynamically allocate graded amounts of
different resources (e.g., devote more visual resources to one task than
auditory resources to another). Shifting task priorities and resource alloca-
tion policies in response to transient changes in task demands is particularly
difficult (Tsang and Wickens, 1988) and may inhibit an effective response
to workload transitions. In practice, humans tend to maintain a particular
strategy of resource allocation, even though the situation has changed.
To achieve required levels of performance on competing tasks, subjects
try to perform tasks simultaneously, or allow high-priority tasks to preempt
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WORKLOAD TRANSITION
their attention whenever their performance begins to degrade. In opera-
tional situations, task prioritization may be formalized, based on safety or
mission-related concerns. For example, all pilots are taught to aviate, navi-
gate, and communicate, in that order of importance. However, even low-
priority tasks can assume temporal priority (i.e., verbal communications do
not wait for an operator to get around to them) because they grab attention
(they are loud, bright, unexpected, etc.) or because they can be completed
quickly (thereby getting them out of the way).
An operator's ability to respond to changing priorities is influenced by
the total demands of concurrent tasks, their resource requirements, instruc-
tions, feedback, and training (Tsang and Wickens, 19881. Although little
research has been performed to relate priority manipulations and dynamic
resource allocation to workload, it is reasonable to assume that workload is
likely to increase when performance strategies must be changed in response
to a shift in task priority. Furthermore, if operators select an inappropriate
strategy (e.g., focusing more resources than required on one task and too
little on another), resources are wasted with a resulting cost in performance,
workload, or both.
It appears that people can learn more efficient methods of responding to
task-specific, priority manipulations through training (Gopher et al., 1989~.
Furthermore, more generic skills developed in one task (i.e., a video game)
can transfer to another (i.e., flight), thereby facilitating performance (Go-
pher et al., 19881.
Task Schedule
The way operators organize their time and resources to perform com-
plex tasks has a significant impact on the workload experienced and perfor-
mance achieved. To some extent, task scheduling depends on external fac-
tors (e.g., instructions, procedures, information availability, deadlines, the
length of time a task can be safely ignored, etc). In laboratory research,
tasks that are to be performed sequentially are generally presented sequen-
tially and those that are to be performed concurrently are presented concur-
rently, to elicit a particular response strategy. In realistically complex situ-
ations, however, operators may have greater flexibility in how they perform
multiple tasks. They may choose to perform different task combinations
either simultaneously, alternatively, or sequentially, with different workload
and performance costs.
Sequential performance may decrease workload and result in a better
quality of performance. However, this strategy may delay the completion
of some task components. Concurrent performance may increase workload
and result in a poorer quality of performance, although the time to complete
all of the tasks may be less. When tasks are performed simultaneously,
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WORKLOAD FACTORS
61
workload and performance depend on the cognitive and physical resources
required. If two tasks require the same resources, and if their demands
exceed available capacity, performance on one or both of them will suffer.
When operators alternate between several tasks (or perform them sequen-
tially), resource competition is no longer an issue, although switching atten-
tion may require additional time and effort (see Chapter 9~. In addition,
switching from one stimulus-response modality to another takes more time
and effort than switching between tasks that require the same stimulus-
response modalities. For example, visual-spatial target acquisitions take
longer and impose higher workload when the correct target is identified
auditorially, rather than visually, or represented verbally rather than spa-
tially (Hart et al., 1986~.
If operators are allowed some scheduling flexibility, they may adopt
different strategies depending on the characteristics of a particular task com-
bination. For example, King et al. (1989) found that subjects faced with
performing a three-axis tracking task while also completing a series of
discrete tasks adopted both time-sharing and switching strategies. Discrete
tasks that could be completed quickly preempted the tracking task. Sub-
jects were able to maintain single-task performance levels on the discrete
tasks without seriously disrupting control performance because they required
little time away from tracking. Subjects also alternated between the control
task and discrete tasks that took several seconds to complete. Response
times increased significantly over single-task levels, and subjective workload
was high, possibly reflecting the added cost of switching back and forth.
Moray and Liao (1988) found that when the presentation rate of four con-
current tasks was increased until there was insufficient time to service all of
the tasks, subjects simply stopped performing some of the tasks to protect
performance on the others.
When performing familiar tasks, in which variations in task demands
are relatively predictable, completing some tasks ahead of schedule and
developing contingency plans during periods of low workload can reduce
workload and improve performance during later periods of high workload.
For example, Pepitone et al. (1988) found that contingency planning signifi-
cantly improved the quality of later decisions made under time stress and
resulted in safer flights. Furthermore, if the time required to complete
specific tasks and the time remaining in which to complete them are known,
then operators can develop more efficient task-performance schedules.
When events unfold as planned and well-rehearsed sequences of actions
can be relied on, cognitive demands are lower, performance better, and
workload less than when unexpected events occur. Thus, developing a
range of contingency plans for potential events is a valuable workload man-
agement tool. Planning ahead requires time and effort, however. For ex-
ample, Vienneau and Gozzo (1987) found that helicopter pilot workload
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WORKLOAD TRANSITION
was higher during the planning stage immediately preceding the execution
of a maneuver than during the maneuver itself. Thus, predicted load levels
(based on physical activities) lagged the actual load levels by one event.
Hart and Hauser (1987) obtained similar results with fixed-wing pilots.
Premission workload levels were higher than those of all but the most de-
manding flight segments.
In laboratory research, random intertrial intervals and lack of preview
about upcoming events generally preclude anything but a reactive strategy.
However, the little research that has been performed on this topic suggests
that people are able to develop more efficient strategies if given the oppor-
tunity. For example, Tulga and Sheridan (1980) examined decision makers'
performance in a dynamic, multitask simulation. The number, durations,
deadlines, and payoff of tasks and intertask arrival times were manipulated.
With moderately complex schedules, operators adopted relatively optimal
scheduling strategies. However, they reverted to a reactive strategy when
the situation became too complex. Using a similar paradigm, Hart et al.
(1984a) found that proficient subjects adopted a time-sharing strategy, rather
than a sequential strategy, and actively controlled the flow of task elements
(e.g., requesting tasks ahead of schedule during periods of low workload,
deferring some tasks during periods of high workload, and shedding tasks
they could not complete), thus completing twice as many tasks in the same
interval of time as low-scoring subjects, who were more reactive and per-
formed task elements sequentially, even though there was sufficient time to
alternate between tasks.
In operational situations, team members may request assistance from
each other as a strategy for coping with excessive task demands. Although
the effects of team workload management strategies are not well known, it
seems reasonable to assume that the appropriate management of human and
system resources can result in adequate performance and acceptable workload,
even in the face of relatively high task demands. A team commander must
monitor the workload of team members and shift responsibilities to avoid
an uneven distribution of workload across people and time. However, when
a crew adopts a reactive strategy or is forced into one by externally paced
and unpredictable task demands, performance is more likely to suffer and
workload will be higher.
Rate of Presentation
Almost any task within an operator's capabilities can be performed
correctly and with acceptable workload if sufficient time is available. Con-
versely, if sufficient time is not provided to perform a single task, or if the
interval between task elements is reduced below some critical value, then
task completion is not possible, no matter how much effort is invested. In
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WORKLOAD FACTORS
63
between, where internal or external constraints impose some time pressure
but task performance is still feasible, the usual finding is that subjective
workload increases as time pressure increases. However, people may adopt
different coping strategies to deal with an increase in time pressure (e.g.,
trade accuracy for speed, shed or defer some tasks, reduce their perfor-
mance criteria), thereby reducing the effects of time pressure on their workload.
There are structural limitations in the speed with which humans can
perceive, process, and respond to successive inputs. For example, percep-
tual events that occur within roughly 100 milliseconds of each other are
combined into a single perceived event (Card et al., 1986~. If one stimulus
is presented before a previous one has been fully processed, responses to
the second will be delayed, presumably because the central processor can
operate on only one task at a time (Welford, 19671. Card et al. (1986)
estimated the duration of the entire perception-processing-action feedback
loop to take between 200 and 500 milliseconds. Thus, since the discrete
micromovements that combine to create continuous control activities re-
quire only about 70 milliseconds (Keele, 1986), a series of motor move-
ments can be executed open-loop between corrections guided by visual feedback.
For discrete responses, the lower limit of reaction time is in the range of 70-
100 milliseconds. However, the minimum time required to complete any
particular keystroke or button press is determined by the duration of the
perceptual and cognitive processes required to select the correct response.
For example, Card et al. (1986), in their summary of research, identified the
minimum processing times associated with: (1) number of potential re-
sponses (response times increase by 90-150 milliseconds for each additional
alternative), (2) comparisons with remembered items in short-term memory
(30-70 milliseconds for each additional item, depending on their complex-
ity), (3) meaningfulness (a range of 158 to 500 milliseconds per typing
keystroke for text, random words, and random letters, with text being the
fastest and random letters the slowest), (4) matching stimulus input to an
internal representation (310, 380, and 450 milliseconds, respectively, for
physical, name, and class matches), and so on.
Obviously, the minimum time required to perform the complex activi-
ties typical of the real world is longer and more difficult to predict. However,
the same principles hold. If operators are not allowed sufficient time to
encode and process information, select a response, and execute the response,
then performance quality will suffer and higher workload will be experienced.
In continuous control tasks, such as that performed by the tank driver,
the operator's goal is to minimize the time-averaged difference between a
target (e.g., a nominal flight path, a driving lane, a point or line on a screen)
and the output of a dynamic system. This goal is accomplished by manipu-
lating available control mechanisms (e.g., aircraft control inputs, steering
commands, or joystick inputs). The difficulty of this task is directly influ
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WORKLOAD TRANSITION
enced by the predictability, frequency, and amplitude of the disturbances
(e.g., winds) for which the operator is trying to compensate. People may be
able to compensate perfectly for highly predictable, low-frequency distur-
bances; error and workload generally increase at higher frequencies (see,
for example, Moray and Liao, 1988~. Random or quasi-random signals
composed of many frequencies are less predictable and therefore impose
even higher workload. As more frequencies are combined to create a com-
plex signal, it becomes more difficult for an operator to track. An increase
in bandwidth (the upper limit of the frequencies represented in a complex
signal), such as that caused by driving an unpredictable course at faster
speeds is usually associated with an increase in workload as well (see, for
example, Hauser et al., 1983; King et al., 1989~; operators must enter cor-
rections and monitor the visual display more often with high-bandwidth
disturbances. However, people may be less sensitive to the effects of band-
width on workload than they are to other manipulations of tracking task
difficulty (Vidulich and Wickens, 1984, 1986~. There is evidence from
scores of dual-task experiments that low-bandwidth tracking tasks (e.g., less
that 0.5 Liz) allow the operator sufficient time to simultaneously perform
many types of concurrent tasks. However, it is difficult for them to main-
tain the same level of performance on high-bandwidth tasks (e.g., greater
than 1.0 Hzj while also performing other activities. Maintaining acceptable
performance when a signal is very unpredictable simply demands too much
time and attention.
The relationship between rate of presentation (or response) and workload
or performance may be U-shaped. For extremely slow or infrequent tasks,
loss of vigilance has been associated with slower response time and higher
subjective workload; boredom is unpleasant for many people (Hancock and
Warm, 1989~. A moderate increase in presentation rate may increase arousal
and result in faster response times, but at the cost of an increase in workload
(see, for example, Moray and Liao, 19883. Beyond some point, further in-
creases in presentation rate generally result in an increase in subjective workload,
errors, or delayed responses as operators attempt to share their attention be-
tween temporally overlapping activities. For example, Pepitone et al. (1987)
found that pilot workload was significantly positively correlated with the rate
at which flight-related tasks were imposed while pilots flew a simulator. As
presentation rate was increased from once every 2.4 minutes to once every
0.8 minutes, subjective workload increased significantly.
For complex tasks, the pattern of performance decrements that occurs
when there is insufficient time to monitor, process, and respond to all task
components depends on the strategy an operator adopts. For example, Mo-
ray and Liao (1988) found that increased task frequency had different ef-
fects on the performance of each of four concurrent tasks. For choice
reaction time and arithmetic tasks, response time became faster but accu
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WORKLOAD FACTORS
83
craft, autopilots achieve and maintain the flight path based on information
entered by the pilot before takeoff or modified inflight by single, discrete
commands. In military jets, terrain following/terrain avoidance algorithms
process mission, terrain, and threat data to project and follow an optimal
flight path. In many environments, even system monitoring is accomplished
automatically, providing the operator with visual and/or auditory alarms
when a failure occurs. Expert systems are being developed for use in high-
performance aircraft that will infer the pilots' intentions and evaluate the
degree to which his commands support, or conflict with, his current goals
(Rouse et al., 1990~.
Given the increasing complexity of many advanced systems, operators
are no longer able to control the system without assistance. Thus, various
methods of alleviating their workload have been introduced. For example,
direct displays of system parameters (which may be noisy, high-order, and
unintegrated) might be replaced by displays that filter noisy inputs, appear
to be of a lower order, and integrate the outputs of related subsystems.
Predictor displays can depict estimates of the future state or position of the
system based on its current state and assumptions about the operator's fu-
ture control activity (Wickens, 1986) and present this information to the
operator in graphic form. Because predictor displays perform some integra-
tion and projection for operators, thus allowing them to be proactive rather
than reactive, they often improve the accuracy and smoothness of control
activities and reduce operator workload.
Stability augmentation systems reduce the frequency and order of con-
trol inputs required of an operator. For example, a number of the stability-
control augmentation systems evaluated in a simulated advanced Army heli-
copter significantly reduced pilot workload (Haworth et al., 1987), but the
benefits varied across mission segments. Fully automatic systems allow an
operator to enter a desired outcome directly (e.g., a new heading) while
underlying subsystems manipulate the control surfaces to achieve the de-
sired state. In fact, as the level of control augmentation increases beyond
some point, the role of the operator shifts from that of manual controller to
system monitor.
Vienneau and Gozzo (1987) evaluated the effects of automating eight
different subsystems in simulated military missions conducted in a single-
pilot advanced scout/attack helicopter. They found, as did Haworth et al.
(1987), that automation aided pilots in managing workload peaks and re-
duced overall workload. For example, computer-aided systems for commu-
nications (with voice-activated frequency selection) and navigation (with a
digital map display) reduced flight path deviations by an average of 67
percent and time en route by 70 percent. Again, differential benefits were
found across mission segments and greater improvements were found for
high-workload activities. Vienneau and Gozzo suggested that workload
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WORKLOAD TRANSITION
reductions might be achieved by either the addition of automated subsystems
or by increasing the efficiency of the human's interface with the system.
Automation does not always reduce operator workload. Often, it sim-
ply replaces one form of workload (the physical demands of manual con-
trol) with another (the perceptual-cognitive demands of monitoring the sys-
tem) (Hart and Sheridan, 1984~. Designers tend to automate tasks that are
easy to automate. As discussed earlier, these are usually the skill-based
tasks that are also easy for a human to perform. This often leaves the
operator with a collection of unrelated activities to perform that are too
ambiguous or unpredictable to automate and that impose equally high de-
mands on the operator. Finally, automation reduces an operator's direct
involvement with and knowledge of the system and may make it more
difficult to detect errors or assume control if the automated system fails.
For example, Wickens and Kessel (1979) found that people are better able
to detect a sudden change in system state when manually controlling a
system than when supervising the performance of an automated system.
Thus, opportunities for system error may, in fact, increase. Long delays
between an operator input and its ultimate effect decrease the probability of
detecting and rectifying a human error (Kantowitz and Casper, 1988) or a
system error. Although airline pilots have found automation to be useful,
they do not necessarily agree that it has reduced their overall workload
(Wiener, 1989; Wiener and Curry, 1980~.
In many cases, automation is introduced to allow a reduction in crew
size or an increase in mission capability. This creates the potential for
increasing the workload of remaining crew members if the level of automa-
tion is not sufficient. Even with a fully functioning system, it is difficult to
replace a human operator completely with an automatic system. For ex-
ample, Haworth et al. (1987) found it was impossible to achieve the same
level of workload typical of two-pilot crews for the single pilots of a highly
automated simulation of an advanced Army helicopter. In addition, workload
and performance predictions and system evaluations (on which crew complement
decisions are based) assume the appropriate use of available automation. If
the systems are too numerous or complex to be used effectively, or if they
fail, the burden of accomplishing the mission rests on the operators, who
may experience far higher workload than anticipated. Finally, the contro-
versy continues about how to allocate tasks between humans and machines
and whether the operator should retain control or allow an automated sys-
tem to override human decisions.
SUMMARY
In some cases, it is apparent that human limitations reflect the conse-
quences of poorly designed controls, displays, and automatic subsystems.
OCR for page 85
WORKLOAD FACTORS
85
In others, task demands simply exceed the operator's capabilities either
momentarily or for extended periods. Despite their limitations, humans are
remarkably flexible, adaptable, and capable. They can improvise, compen-
sate for inadequate information and system or human failures, adjust to
novel situations, exhibit graceful (rather than catastrophic) degradation, plan
ahead, predict the outcome of familiar and unfamiliar events, and learn
from experience. However, the consequences of extreme demands and re-
quirements to act creatively and adaptively impose significant workload on
the human operators of complex systems.
Regardless of the specific sourcegs) of workload at any point in time,
adequate training and preparation, adopting strategies and tactics most ap-
propriate for the situation, effective leadership, and smooth crew coordina-
tion can counteract some of the detrimental effects of imposed task de-
mands, transitioning from one mode of behavior to another, environmental
stressors, and fatigue. The more actions that have become automatic through
training and experience and the more predictable events seem through plan-
ning and rehearsal or availability of preview information, the more likely it
will be that crews will respond appropriately and sustain adequate perfor-
mance for as long as necessary.
There are several significant factors that characterize the transition from
low to high workload mission phases. One, of course, is the absolute level
of workload. There is no question that workload is higher during an en-
gagement than before. However, the fact that the sources of workload are
significantly different between the two phases may present a greater prob-
lem. The nature of the task demands shifts from preparation to action; from
static to dynamic; from long lead times to short; from passive monitoring
and maintenance to active information seeking, control, and operating; from
direct interaction to radio communications; from predictive to compensa-
tory behaviors; from planning to reaction; from organized procedures and
schedules to spontaneous actions.
Crews may adopt different strategies for coping with a sudden increase
in workload. They may choose to process fewer events (e.g., selectively
attend to fewer tasks, defer activities, monitor fewer channels, ignore infor-
mation about expected events, or consider fewer alternative hypotheses).
Alternatively, they may choose to process events less completely (e.g., sample
information sources less often, seek less corroborating evidence, be satis-
fied with partial feedback, narrow the field of attention, pursue fewer pos-
sible explanations, or limit their anticipation of what might happen next)
(Woods, 19891. Although either of these strategies might be effective in
reducing workload in the near term, they also might shift such workload to
a later time. Furthermore, incomplete attention to the current situation and
tasks is more likely to result in errors, which will impose additional workload
to rectify.
OCR for page 86
86
WORKLOAD TRANSITION
A shift in the nature of task demands, accompanied by an increase in
time pressure and uncertainty, requires a significant change in the team's
behaviors and strategies, which in itself imposes additional workload. In
addition, boredom, impatience, or apprehension (which may characterize
the premission phase) are replaced by stress and fear following a transition.
While the latter factors increase the level of arousal and focus the attention
of the crew (a potential benefit for performance) they may impair the crew's
ability to perform accurately and effectively, thereby increasing the effort it
must exert to maintain acceptable performance. These stress effects are
addressed in the next chapter.
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Representative terms from entire chapter:
workload factors
