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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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58 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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60 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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62 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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64 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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84 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.

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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.

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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. REFERENCES Acton, W.H., M.S. Crabtree, J.C. Simons, F.E. Gomer, and J.S. Eckel 1983 Quantification of crew workload imposed by communications-related tasks in commercial transport aircraft. Pp. 239-243 in Proceedings of the Human Factors Society 27th Annual Meeting. Santa Monica, California: Human Factors Society. Andre, A.D., and C.D. Wickens 1992 Compatibility and consistency in display-control systems. Human Factors 34(6). Andre, A.D., C.D. Wickens, L. Moorman, and M.M. Boeschelli 1991 Display formatting techniques for improving situation awareness in the aircraft cockpit. International Journal of Aviation Psychology 1(3):205-218. Aretz, A.J. 1990 Map display design. Pp. 89-93 in Proceedings of the Human Factors Society 34th Annual Meeting. Santa Monica, California: Human Factors Society. Baddeley, A.D. 1986 Working Memory. Oxford: Clarendon Press. Baddeley, A.D., and G.J. Hitch 1974 Working memory. In G.H. Bower, ea., The Psychology of Learning and Motiva- tion: Advances in Research and Theory, Volume 8. New York: Academic Press. Bamba, Z., D. Bushnell, S. Chen, A. Chiu, C. Nuekom, S. Nishimura, M. Prevost, R. Shankar, L. Staveland, and G. Smith 1991 Army-NASA Aircrew Aircraft Integration Program (A3I): Man-Machine Integra- tion, Design, and Analysis Systems (MIDAS). Report No. TN-91-8216-000. Palo Alto, California: Sterling Federal Systems, Inc. Bennett, C.T., M. Schwirzke, and J.S. Tittle 1990 Perceptual and Performance Consequences of Flight in Virtual Worlds. Poster presented at the Workshop on Human-Machine Interfaces for Teleoperators and Virtual Environments. Santa Barbara, California. Berg, S.L., and T.B. Sheridan 1984 Measuring workload differences between short-term memory and long-term memory scenarios in a simulation flight environment. Pp. 397-416 in Proceedings of the 20th Annual Conference on Manual Control. Report No. NASA CP-2341. Wash- ington, DC: National Aeronautics and Space Administration. Bittner, A., J.C. Byers, S.G. Hill, A.L. Zaklad, and R.E. Christ 1988 Generic Workload Ratings of a Mobile Air Defense System (LOS-F-H). Willow Grove, Pennsylvania: Analytics, Inc. Boles, D.B., and C.D. Wickens 1987 Display formatting in information integration and nonintegration tasks. Human Factors 29(4):395-406.

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