Technical keport Documentation Page 

1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. 

DOT/FAA-AM-85-13 

4. Title and Subtitle 5. Report Date 

THE EFFECT OF VISUAL TASKLOAD ON CRITICAL FLICKER 

FREQUENCY (CFF) CBANGE DURING PERFOR~ANCE OF A 

CCMPLEX MONITORING TASK 

OCTOBER 1985 

6. Performing Organization Code 

t--::--.,.-.,.-;--------------------------l 8. Performing Orgcni zcrtion Report No. 

7. Author/ s) 

Richard I. Thackray and R. Mark Touchstone 

9. Performing Organization Name and Address 

FAA Civil Aeromedical Institute 

P. 0. Box 25082 

Oklahoma City, Oklahoma 73125 

12. Sponsoring Agency Name and Address 

Office of Aviation Medicine 

Federal Aviation Administration 

800 Independence Avenue, SW. 

Washington, DC 20591 

15. Supplementary Notes 

Work was performed under tasks 

16. Abstract 

10. Work Unit No. (TRAIS) 

11. Contract or Grant No. 

13. Type of Report and Period Cove<ed ---~ 

14. Sponsoring Agency Code 

AM-C-82/83/84/85-PSY---90 >~ 

/·z) 

The present study examined the effect of differing levels of visual taskload on 

critical flicker frequency (CFF) change during performance of a complex 

monitoring task. The task employed was designed to functionally su.ulate the 

general task characteristics of future, highly automated air traffic contl"'l 

systems in which passive monitoring is likely to be a principal job requirement. 

Forty subjects, divided into two equal-size groups, monitored displays 

containing either 8 or 16 alphanumeric targets. Nine critical events were 

randomly presented during each half-hour of the single 2-h session to whieb each 

subject was exposed. CFF thresholds were obtained prior to and following the 

sessions. Subjects monitored for the occurrence of two types of critical 

events. The first type consisted of a readily detectable change in an 

alphanumeric data block; the second kind of event was the occurrence of two 

aircraft (alphanumeric targets) at the same altitude on the same flight path. 

The results revealed that the more readily detectable critical events showed no 

evidence of performance decrement at either level of visual taskload. For the 

more difficult task of detecting critical altitude events, both CFF and 

performance showed evidences of fatigue that were confined entirely to the 

higher taskload condition. The findings are discussed with reference to fatigue 

and monitoring loads in highly automated air traffic control system concepts. 

17. Key Words 18. Distribution S'tatement 

Attention Automation Document is available t.o d1e public 

through the National Tedm.i.cal Information Service, Springfield, Vir~inia 

22161. 

Monitoring Performance 

Vigilance 

Air Traffic Control 

Critical Flicker Frequency 

19. Security Classif. (of this report) 

Unclassified 

20. Security Classif. (of this page) 

Unclassified 

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized 

21. No. of Pages 22. Price 

18 
ACKNOWLEDGMENT 

The authors extend their sincere appreciation to Ms. Anna Chomiak of Oklahoma 

State University for the many hours and specialized assistance she provided in 

developing the multidimensional fatigue scale used in this study. 
THE EFFECT OF VISUAL TASKLOAD ON CRITICAL FLICKER FREQUENCY 

(CFF) CHANGE DURING PERFORMANCE OF A COMPLEX MONITORING TASK 

INTRODUCTION 

With the development of increasingly automated air traffic control (ATC) 

systems, more and more of the functions currently performed by controllers will 

be assumed by the computer. As the controller's role gradually shifts from that 

of an active participant in control decisions to that of a monitor or overseer 

of a computerized operation, it seems likely that an increasing portion of the 

future controller's time will be spent in simply maintaining an awareness of 

actions being taken by the system and in verifying that those options presented 

by the computer are appropriate (Lipps et al. 1983; Swedish 1983). Current 

concepts of ATC automation, however, do-nor-relieve the controller of his/her 

responsibility to adequately back up the system in the event of malfunctions or 

deviations from normal system operation. Even under the highest levels of 

automation, such as the AERA (Automated En Route Air Traffic Control) 3 concept, 

in which the controller is essentially out of the control loop, he/she still has 

the responsibility to maintain active awareness of system operation in order to 

act as a backup, if necessary. This is stated rather emphatically in the 

following quote pertaining to a fully automated concept: "Since the controller 

no longer plays an active role in the implementation of the control plan but 

still is responsible for the actions taken, it is critical that the controller 

be al1le to follow the control activities performed by the automation system so 

that the controller can intervene if necessary and make informed control 

decisions" (Lipps et al. 1983). If we assume that intervention might be a 

relatively infrequentoccurrence in highly automated systems, ques.ti.ons relating 

to the maintainence of controller attentiveness, involvement, and readiness to 

react in emergencies while moni taring a largely computerized operat.ion will 

become increasingly important considerations in the systems being planned. 

In a previous study, we examined the effect that differing levels of visual 

taskload might have on the ability to sustain attention to a rather passive ATC 

monitoring task (Thackray et al. 1979). In this study, subjects were required 

to monitor either 4, 8, or--16~argets in order to detect occasional critical 

changes in the alphanumerics. While there was no evidence of performance 

decrement in the two lower taskload conditions, subjects assigned to the 

16-target condition showed a significant decline in attention as reflected in a 

progressive increase in detection times over the 2-hour session. In a somewhat 

similar study, Howell et al. (1966) likewise found a direct relationship 

between the magnitude of vigilance decrement and the number of targets that 

subjects were required to search. Detailed analyses of data in bo.th studies 

revealed that this increase in detection time under conditions of high targe~ 

density was the result of a progressive increase in the duration of long 

detection times; shortest times remained relatively constant over successive 

periods of the monitoring session. Since the appearance of long response times, 

"bl.ocks," or gaps during sustained performance of continuous or repetitive-type 

tasks i.s. generally considered to be one of the more sensitive and acceptable 

criteria of fatigue (Bertelson and Joffe 1963), it would seem. reasonable to 

hypothesize that a requirement to continuously monitor a large number of targets 

over a prolonged period of time demands considerable effort, and that the 

1 
increase in frequenpy of long response times found in our study was a 

manifestation of the fatigue resulting from this effort. A similar hypothesis 

was advanced by Howell et al. (1966) to account for the performance decrement 

found in their study. 

Even though a fatigue explanation would appear to be one of the more plausible 

ones to account for the performance decrement that occurred only under the 

highest taskload condition, Thackray et al. (1979) were generally unsuccessful 

in finding ancillary evidence to support~his. Except for an apparent increase 

in the frequency of brief eye closures that occurred primarily in the 16-target 

condition, most of the physiological and subjective measures of arousal or 

fatigue employed showed changes during task performance that were no greater in 

the 16- than in the 4- or 8-target conditions. Although it is believed that the 

obtained decrement in performance was indeed a manifestation of fatigue, it 

would clearly be desirable to obtain alternative indices, apart from 

performance, that could be used to detect its occurrence. Such "indirect" 

indicators of the presence of fatigue might then be used under operational 

conditions in which direct assessment of performance change could be difficult, 

if not impossible. 

Within recent years, there has been renewed interest in the use of critical 

flicker frequency (CFF) as a measure of fatigue, in particular the mental 

fatigue associated with performance of repetitive or vigilance-type tasks 

demanding sustained attention over prolonged periods of time (Davies et al. 

1983, Grandjean 1979). CFF, which may be defined as " ••• that rate of-successive 

light flashes from a stationary light source at which the sensation of flicker 

disappears and the light becomes 'steady'" (Simonson and Brozek 1952), is a 

measure that appears to reflect the number of impulses capable of being 

processed by the retinal-cortical system per unit time (Levander and Lagergren 

1973). Grandjean and his colleagues have done most of the recent work with this 

measure and were quite successful in using CFF as a measure of fatigue among air 

traffic controllers (Grandjean et al. 1971). In their study of Swiss 

controllers at the Zurich airport, CFF was found to decline gradually over the 

first 6 hours of a 10-hour work period and then to decline more abruptly during 

the final 4 hours. A parallel pattern of change was noted for subjective 

ratings of tiredness. 

Similar changes in CFF, although generally of lower magnitude, have also been 

reported in laboratory studies of mental fatigue. Thus, Baschera and Grandjean 

(1979) compared CFF change during the performance of three versions of a 

repetitive task; the versions all required the same motor responses but differed 

in cognitive/perceptual demand. CFF was found to decline significantly in both 

the least demanding (most monotonous) and the most demanding versions, but not 

in the moderately difficult one. This finding was in agreement with their 

hypothesis that both the "monotonie" of a repetitive, low difficulty task and 

the "fatigue" resulting from performance of a high difficulty, perceptually 

demanding task would produce common CFF central nervous system changes. 

Grandjean (1979), in fact, has stated that boredom and "mental fatigue" produce 

symptoms that are nearly the same and that it may be impossible to distinguish 

between the two. 

2 
In a subsequent study, Weber et al. (1980) examined the psychophysiological and 

subjective changes associated-with performance of four versions of a somewhat 

similar task, all versions of which required the same motor activity but 

differed in the level of perceptual discrimination needed. CFF was found to 

decline significantly over time in all versions of the task, but unlike the 

previous findings of Baschera and Grandjean (1979), only the most demanding task 

version showed a decline that was significantly greater than that shown by the 

other three. Subjective fatigue patterns differed among the versions, with 

drowsiness and boredom being greatest in the two versions requiring least 

perceptual discrimination, and tension characterizing the two most difficult 

ones. 

The above studies, and others reviewed by Davies et al. (1983), all suggest 

that continued performance of repetitive tasks demanding sustained attention is 

accompanied by a decline in CFF. However, laboratory findings differ with 

regard to the relationship of this decline to taskload. Thus, while Weber et 

al. (1980) found that only the heaviest taskload produced a CFF decline that 

was significantly greater than that of the other three taskload conditions, 

Baschera and Grandjean (1979) found that performance of a low difficulty task 

resulted in a CFF decline that was equivalent to that produced by a much more 

demanding task. It is evident that, if CFF is to be of any value as a measure 

of fatigue in ATC applications, a clearer understanding of its relationship to 

taskload is required. 

The primary purpose of the present study, then, was to examine the effect of two 

levels of visual taskload on CFF change during the performance of a simulated 

air traffic control monitoring task. In addition, the study also sought to 

determine whether a multidimensional scale of subjective fatigue, modeled after 

similar scales devised by Wolf (1967) and Kinsman et al. (1973), might yield 

information on specific patterns of fatigue, unique to the high and low taskload 

conditions and not apparent through the use of CFf ~lone. This latter 

possibility, that high and low taskload conditions may elicit qualitatively 

different patterns of subjective fatigue, has been suggested by Wolf and 

reflects a growing belief that multidimensional scales encompassing independent 

clusters of subjective symptoms may reveal unique patterns of fatigue associated 

with specific tasks and task conditions that cannot be revealed by simple 

unidimensional scales alone (Kinsman and Weiser 1976). 

The task employed represented an updated version of the radar monitoring task 

used in our laboratory over approximately the last 10 years. The previous 

version, which initially usea film strips and later a computer-generated 

display, was designed to functionally simulate the general task characteristics 

of future, highly automated ATC systems in which passive monitoring is expected 

to be a principal task requirement. While this earlier version proved to be 

useful in the investigation of a variety of variables affecting complex 

monitoring performance, it had certain limitations that restricted its use to 

particular kinds of research questions. For example, it, like virtually all 

other existing vigilance tasks, was developed primarily for the purpose of 

investigating factors affecting the detection of only one type or class of 

signal over time. As investigators are beginning to recognize, modern 

operational vigilance tasks, such as those involving the monitoring of automated 

processes, involve more than simply detecting and responding to infrequent 

3 
changes in unidimensional 3timuli. They frequently involve complex 

multidimensional discriminations (Mackie 1984) in which stimulus detection or 

identification may be followed by interpretation of significance, decisions as 

to appropriate action, implementation of actions, and evaluation of consequences 

(Craig 1984). Considerations such as these led us to the decision to develop a 

new version of our task that would allow us to investigate the effects of 

prolonged monitoring, not only on perceptual processes, but on a range of 

cognitive behaviors as well. In addition, it was felt that any revision of our 

radar monitoring task should provide for much greater flexibility of 

person-computer interaction in order to allow for studies dealing with optimal 

allocation of function in automated ATC systems. 

The task described in the present report represents the initial version of our 

updated radar monitoring task that, with subsequent modifications as needed, 

will evolve into a testbed for evaluating a variety of questions related to ATC 

automation. The ultimate goal is the development of a task that will allow us 

to examine separately most of the major behaviors that will probably continue to 

be required of controllers, although probably less often in the case of some of 

these behaviors, even under moderately high levels of automation. These 

behaviors include the detection of both simple and complex critical events 

(target changes), short-term memory, decision making, action selection, and 

action verification. Only data pertaining to the detection of critical events, 

however, are reported in the present study. The total task is still in the 

process of development, and data relevant to the other subtask elements are 

being analyzed in the context of this development process and will be reported 

on later in a separate study. For the purpose of providing the reader with 

details regarding the total task performed by the subjects, all aspects of the 

task are described in the procedure. 

METHOD 

Subjects. Thirty-two male and eight female paid university students volunteered 

to participate in the study. They were randomly assigned, in equal male-female 

proportions, to one of two target density (8- or 16-target) groups. Subjects 

ranged in age from 18 to 29 years, and none had prior experience with the task 

used or previous ATC training. All had 20/20 vision, corrected or uncorrected, 

and all had no reported hearing loss. 

Radar Simulation Task. The basic experimental equipment consisted of a Digital 

Equipment Corportion (DEC) VS11 19-in (49-cm) graphics display, keyboard, and 

joystick, all of which were interfaced with a VAX 11/730 computer (DEC). The 

computer was used both to generate input to the display and to process responses 

of the subjects. The VS11 was incorporated into a console designed to closely 

resemble an ATC radar unit. Two diagonal, nonintersecting flight paths were 

located on the display, along which aircraft targets could move in either 

direction. A given aircraft's location was displayed as a small "blip" on the 

flight path, and an adjacent alphanumeric data block identified the aircraft and 

gave its altitude and groundspeed. Aircraft were updated as to location and any 

change in alphanumerics in a continuous, clockwise manner, such that a complete 

update occurred every 6 s. The overall visual impression was that of a series 

of discrete jumps flowing in a circular pattern. This movement pattern 

approximates very closely the way in which aircraft targets are updated in 

4 
Figure 1. A typical target configuration as displayed to the subject. 

Figure 2. The simulated ATC work station. Only the console on the left was 

used in this study. 

5 
contemporary ATC radars with computer-generated alphanumeric displays. Figure 

shows a typical target pat~ern as displayed to the subject, with the total 

console-display configuration shown in Figure 2. 

The subject's task was to continually monitor the display for the occurrence of 

one of two types of designated changes, referred to as critical events, in the 

alphanumeric data blocks. Stimulus duration for these critical events was 

always 90 s; if a subject failed to detect a critical event within this 90-s 

period, the data block containing the change reverted to its previous state. 

The first type of critical event was a readily detectable one and consisted of 

the appearance of three X's in place of the three altitude numbers in a given 

data block. Subjects were told that this replacement of an altitude value by 

the three X's signified that some malfunction had occurred resulting in a loss 

of altitude information. Upon detection of such an event, subjects were told to 

press a button on the console labeled "XXX malfunction," move a 

joystick-controlled cursor over the data block containing the critical event, 

and press another button on the joystick control unit. This last response 

"corrected" the malfunction by replacing the three X's with the previous 

altitude value. The second type of critical event was the occurrence of two 

aircraft at the same altitude on the same flight path. As soon as such an event 

was noted, subjects pressed a second console button labeled "Altitude Check." It 

was next determined whether the two aircraft were moving towards each other, 

moving away fro~ each other, or traveling in the same direction. On the basis 

of this determination, subjects then pressed either a "Conflict" or a "No 

Conflict" button. (All aircraft in this simulation were assigned a speed of 450 

mph. Thus, aircraft could not overtake one another, and only targets moving 

towards each other would constitute a potential conflict situation.) Following a 

"conflict" decision, the cursor was positioned over one of the two conflicting 

aircraft and the joystick control button was pressed. This caused a new 

altitude value to appear in the lower left of the screen that, subjects were 

told, represented a value selected by the computer to resolve the conflict. 

Subjects then verified that the computer-assigned altitude did not result in a 

conflict with some other aircraft on the flight path. If no new conflict was 

created, a keyboard entry was made that assigned the new altitude value to one 

of the two previously conflicting aircraft. (Under the simulation used, a newly 

assigned altitude never conflicted with the altitude of any other aircraft.) 

Whenever a "no conflict" response was made, no further action ensued, since no 

change in altitude was required. Subjects were told that the altitude of one of 

the two nonconflicting aircraft would eventually change to some other value 

(this time was variable, but always less than the 90-s stimulus duration period) 

and that they had to remember that they had responded to this particular pair of 

aircraft. If they failed to remember and responded a second time, an error was 

recorded. 

For a given taskload condition (8 or 16 targets), the number of targets on each 

flight path was kept equal at all times; as one left the screen, another 

appeared. In order to prevent any occurreDce of data block overlap, two 

constraints were necessary: (a) speed was held constant at 450 miles per hour 

for all aircraft, and (b) all data blocks for targets moving from left to right 

were positioned above the flight path, while those moving right to left were 

6 
located below. Nine critical events occurred in each 30-min period, with no 

more than one event present at any given time. Of these nine events, three were 

XXX's, three were conflicting altitude changes, and three were nonconflicting 

changes. These events were arranged in a quasi-random order with the 

restriction that each of the three types of events had to occur at least once in 

both the first and second 15 min of each 30-min period. Subjects were given no 

information regarding the frequency of events or their order of occurrence. The 

times between events (interstimulus intervals) ranged from 126 to 302 s with a 

mean of 200 s. 

CFF Measurement. A Lafayette Instrument Company model 12025 Flicker Fusion 

Apparatus with binocular viewing chamber served as the basic equipment for CFF 

measurement. A circular target area 0.5 inches in diameter was viewed 

monocularly at a distance of 14.5 in, subtending a visual angle of 2 degrees, 10 

min. Two Sylvania R1166 glow modulator tubes were located in the viewing 

chamber behind milk glass diffusion filters; the left one served as the stimulus 

light source, while the right one drove a phototransistor that was connected 

directly to the digital inputs of the computer. A light/dark ratio of 1:1 was 

used for the stimulus light, and the intensity of the test patch was 5 mL. 

The CFF apparatus was modified so that thresholds were obtained directly by 

subjects themselves. The psychophysical method employed is referred to as the 

Bekesy tracking procedure and, although commonly used in audiometry, has not to 

our knowledge been used previously to measure CFF. (Recently, Ginsburg and 

Cannon (1983) and Kohfeld (1985) have reported using this technique to measure 

visual contrast sensitivity.) A stepping motor, mechanically attached to the 

frequency control of the CFF apparatus, allowed subjects to increase or decrease 

the frequency of the visual stimulus by means of a hand-held microswitch. With 

the stepping motor in operation, rate of change in the flickering light was 

approximately 0.43 Hz/s. Subjects were instructed to press the microswitch 

whenever the light appeared to be flickering and to continue to hold the switch 

down until fusion occurred, whereupon they were to release the switch until a 

flickering sensation was just noticed. They were told to repeat this sequence 

until the light in the viewing chamber disappeared, signaling a rest period. 

CFF thresholds were determined from two sessions; one occurred at the beginning 

of the experiment and the other at the end. The sessions consisted of five 40-s 

trials, with each trial followed by a 40-s rest period. A small red indicator 

light alerted subjects at the beginning of each trial. All sessions were begun 

with flicker rate initially set at 35 Hz. 

A computer program was developed that determined, within each 40-s trial period, 

the flicker frequency of the visual stimulus at the time each button press and 

release occurred. The values thus obtained gave the upper and lower transition 

frequencies for each ascending and descending series. CFF was defined as the 

average of the upper and lower values obtained within each 40-s trial period. 

The CFF apparatus and computer were located in an adjacent room from which the 

subject was monitored via closed-circuit TV. Indirect lighting was used in the 

subject's room, and the level of illumination at the display was 5.6 lux. 

Multidimensional Scale. The scale employed was derived from an earlier pilot 

study in which 35 fatigue-related adjectives were rated by 71 undergraduates 

7 
during the course of normal~ everyday activities. Adjectives used in developing 

the scale were those that appeared related to the fatigue factors (exhaustion, 

drowsiness, and tension/nervousness) isolated earlier by Wolf (1967), or that 

seemed related to a fatigue dimension that we labeled task aversion/boredom. 

This latter dimension was included because the items selected (e.g., bored, 

frustrated, apathetic) appeared to be associated with the feeling of conflict 

that Bartley and Chute (1947) regard as a necessary precursor to feelings of 

fatigue. A varimax rotation of a principal components analysis of the scores 

obtained in the pilot study yielded four interpretable factors. The items 

loading on each of these factors along with factor loadings are shown in Table 

1. The only factor that does not appear clearly distinct from the others is the 

one labeled general activation. This factor is similar to one of the factors in 

Thayer's (1978) Activation-Deactivation scale of arousal and seemingly 

represents the opposite pole of the sleepy/exhausted factor. Since the factors 

contained differing numbers of items, the factor scores used in the present 

study consisted of the means of the item scores rather than the sums. 

Table 1. Subjective fatigue factors and their item loadings. 

Sleepy/ 

Exhausted 

Nervous/ 

Tense 

Items Loadings Items Loadings 

Tired .70 Relaxed -.56 

Fatigued .80 Leisurely -.52 

Rested -.74 Anxious .70 

Lazy .42 Peaceful -.43 

Physically Irritable .56 

tired .80 Nervous .66 

Aching -53 Jumpy .62 

Drowsy .63 Calm -.67 

Exhausted .81 Tense • 61 

Mentally 

sluggish .50 

Weary .61 

Sleepy .62 

Worn out .75 

Task Aversion/ 

Boredom 

General 

Activation 

Items Loadings Items Loadings 

Bored -77 Vigorous .50 

Frustrated .35 Activated .75 

Empty .33 Peppy .74 

Negative .44 Energetic .73 

Annoyed .53 Lively .58 

Monotony .50 

Dull .67 

Uninterested .72 

Apathetic .72 

Unwilling .52 

-------------------------------------------------------------------------------

Procedure. On arrival, the subject was taken to the testing room, and an 

orientation tape was played. The orientation stated that this was one of a 

series of studies designed to investigate the role of the controller in 

increasingly automated ATC systems and that information their participation 

would provide might be used in planning the job/task design of future systems. 

Following this, subjects completed the multidimensional scale of subjective 

fatigue, rating items in accordance with how they felt at that time. 

8 
After completing the fatigue scale, subjects listened to the taped instructions 

for CFF measurement. The instructions indicated that any time the visual 

stimulus appeared to be flickering or fluttering to them, they were to press 

down on the response button until the light appeared to be steady; at this point 

the button was to be released until a flickering or fluttering sensation again 

occurred. This sequence of pressing and releasing the button was to be 

continued as long as the light in the viewing chamber remained on; when the 

light went off, it signaled the beginning of a rest period. It was emphasized 

that the button should be pressed down immediately at the first appearance of 

flicker and released just as soon as it appeared steady. They were also 

instructed to try to keep their eyes looking directly at the light at all times 

during a test trial. Five 40-s trials separated by 40-s rest periods were then 

administered. 

Immediately following CFF measurement, subjects were given task instructions and 

separate practice in responding to each of the three kinds of critical events. 

This was followed by a practice session in which the various kinds of critical 

events were presented in a random order. Twenty-one critical events (seven of 

each kind) occurred during the practice sessions, which lasted a total of 21 

min. On rare occasions, additional practice was given if the subject appeared 

to have difficulty with any of the procedures. 

The experimental session lasted 2 hours. In order to add a greater element of 

realism to the task, a tape recording of background noises recorded in actual 

air traffic control radar rooms was played continuously during the 2-hour task 

session. Sound level of this noise at the subject's head location was 62 dBA. 

It was not expected that this would have any effect on performance, since an 

earlier study, using the previous version of our monitoring task, failed to find 

any significant performance effects of this noise at a considerably higher (80 

dBA) level (Thackray 1982). 

At the completion of the 2-hour task period, five CFF trials were again 

administered along with the subjective rating scale. For half the subjects, CFF 

preceded the subjective scale, while this order was reversed for the remaining 

half. 

RESULTS 

Performance Data. As described earlier, two levels of stimulus difficulty were 

employed in this study. In the first level, subjects were required to simply 

scan the display for the occurrence of three X•s that replaced a three-digit 

altitude value in one of the targets on the screen. The second level, which was 

more difficult, required subjects to make continual comparisons of each target's 

altitude with the altitude values of all other targets on a given flight path in 

order to detect the occasional occurrence of two targets at the same altitude. 

These two levels of stimulus difficulty will henceforth be referred to as the 

low difficulty (LD) and high difficulty (HD) levels respectively. 

Figure 3 shows mean detection times across 30-min periods for both types of 

critical events under 8- and 16-target taskload conditions. Analyses of 

variance applied to the LD data revealed a significant main effect for target 

density (F(1/38)=17.71, p<.01) and a significant target density by periods 

9 
interaction (F(3/114)=3.15, p<.05). Tests of simple effects of the interaction 

revealed the two taskload ·conditions to differ significantly during the first 

(F(1/19):10.06, p<.01), second (F(1/19):18.24, p<.01), and third (F(1/19):6.95, 

p<.05) half-hour periods, but not during the fourth (F(1/19)<1.00). Additional 

tests of simple effects revealed the differences between periods to be 

significant for the 16-target condition (F(3/114):2.83, p<.05), but not for the 

the 8-target condition (F(3/114):1.97, p>.10). 

(/) 

0 

z 

0 

u 

UJ 

(/) 

8 

6 

---- ------- ----- ------- High Difficulty (HD) Events 

--16- Target Condition 

-- 8- Tof<J_et Condition 

~:;..---,__ ______ __ =-,._ ::;;;--'~ Low Difficulty (LD) Events -------

--16-Target Condition ---

8 Target Condition 

2 3 

30-MINUTE PERIODS 

4 

Figure 3. Mean detection times across 30-min periods for LD and HD events 

under the two taskload conditions. 

Unlike the data obtained for LD events, the more difficult task of detecting 

targets at the same altitude does not appear differentially influenced by 

taskload conditions. Except for some reversals, the general pattern shown in 

both task conditions is that of an increase in detection time from the beginning 

to the end of the session. Analyses of variance supported this impression by 

revealing significant main effects for both target density (F(1/38):89.24, 

p<.001) and periods (F(2/114)=3.14, p<.05), with no significant interaction. 

With regard to errors of omission, the more readily detectable LD events were 

seldom missed, and there was no indication that the frequency with which these 

events were missed differed as a function of target density. Thus, no events 

were missed under the lower taskload (8-target) condition, with only two 

subjects missing one event each under the 16-target condition. HD events, 

however, were missed more frequently, and these omissions were definitely 

influenced by taskload. Thus, while only 1 subject missed a single HD event 

under the lower taskload condition, 15 (or 75 percent) of the subjects missed at 

10 
least one event under the 16-target condition. In addition, failures to detect 

HD events increased in frequency over the task session. Out of the 12 HD events 

that occurred during the first hour of the session, subjects missed, on the 

average, less than 1 in 12 (Mn:0.6). During the second hour, however, the 

average almost tripled to a mean of 1.6 events missed. A Wilcoxon test revealed 

this difference between first and second hours to be significant (p<.05). 

CFF Data. CFF values for measurements obtained at the beginning and end of the 

experimental session for the 8- and 16-target conditions are shown in Figure 4. 

As is evident from the figure, while both groups appear to differ little at the 

N 

1-

0:: 

w 

I 

PRETEST 

----------------------

-- 8- Target Condition 

-- 16- Target Condition 

POST TEST 

Figure 4. Pretask and posttask CFF values for the two taskload conditions. 

beginning, there is marked divergence at the end of the session. As might be 

expected from the data shown in this figure, an analysis of variance revealed 

neither the main effect for groups, nor the main effect for measurement periods, 

to be significant (p>.05). There was, however, a significant interaction of 

groups by measurement periods (F(1/38):4.60, p<.05). Tests of simple effects of 

the interaction revealed the pretask to posttask decrease in CFF under the 

16-target condition to be significant (F(1/38):7.40, p<.05), while the apparent 

increase in CFF under the 8-target condition was not (F<1.00). 

Because of the significant decline in CFF found for the 16-target condition, 

further comparisons were made to determine whether magnitude of CFF change was 

related to performance change. Decrease in CFF from pretask to posttask 

measurement periods was correlated with increase, from the first to the second 

hour, in the number of HD events missed, and also with increase in mean 

detection time to HD events over these same two 1-hour periods. While the 

11 
correlation of CFF decrease~ith omission error increase failed to reach 

significance (r:-.30, p>.05), the relationship was in the expected direction. 

There was no evidence of any relationship between CFF change and the magnitude 

of increase in mean detection time to HD events (r:.03, p>.05). 

Subjective Fatigue Data. The subjective fatigue scale was administered prior to 

and following the 2-hour task session. Table 2 shows mean scores for each of 

Table 2. Mean pretask and posttask factor scores for the two taskload 

conditions. 

Taskload 

8 target 

16 tar;get 

Sleepy/ 

Exhausted 

Pre Post 

3.84 2.79 

4.15 2.96 

Nervous/ 

Tense 

Pre Post 

3-27 3.53 

3-57 

Task Aversion/ 

Boredom 

Pre Post 

4.45 3.48 

4.48 3.54 

General 

Activation 

Pre Post 

2.57 

2.63 3-59 

the four factors under the two taskload conditions. (The lower the score, the 

greater the feeling state represented by the factor.) Since scores could range 

from 1 (definite presence of the feeling state) to 5 (definite absence of the 

feeling state), it is evident that most of the factor scores shown in the table 

suggest moderate, rather than extreme, levels of feeling. Analyses of variance 

revealed significant main effects for pretask to posttask change for the 

sleepy/exhausted factor (F(1/38):80.08, p<.001), the task aversion/boredom 

factor (F(1/38):67.l8, p<.001), and the general activation factor 

(F(1/38)=37.70, p<.001). None of the other main effects or interactions of the 

analyses conducted on the above factors was significant, nor were any effects 

significant for the nervous/tense factor. Thus, while performance of the radar 

monitoring task significantly increased feelings associated with the 

sleepy/exhausted and task aversion/boredom factors and decreased feelings of 

general activation, there were no differences in the magnitude of these changes 

that could be .attr.ibuted to the two taskload conditions. Nor were any 

differences at a~ ~ssociated with the nervous/tense factor. 

Because the earlier lroale developed by Wolf had separate factors for exhaustion 

and drowsiness whil>e the present scale combined these two, the Wolf scale was 

reaonstructed from comparable items in order to determine whether, by 'separating 

the two factors, relationships with taskload might be found that would be more 

in accord with Wolf's predictions. Thus, tired, lazy, drowsy, mentally 

sluggish, and sleepy were items included in the present scale that were 

essentially the same as those loading on .w~lf'.·s dr-owsiness ~t:ac:tor, whil.: 

.physically tired, aching, etXhausted, and worn cout •were items trrat loaded on his ~haustion factor. Means of the item scor.es comprising each fa·ctor are shown in 

Table 3. Analyses of variance conducted on these data reveal!ed significant main 

12 
Table 3. Mean pretask and posttask scores for Wolf's drowsiness and exhaustion 

factors under the two taskload conditions. 

Taskload 

8 target 

16 target 

Pre 

3.97 

4.27 

Drowsiness Exhaustion 

Post Pre Post 

2.58 4.01 

2.71 4.17 3.51 

effects for factors (F(1/38):16.49, p<.001), for order of administration 

(F(1/38)=69.98, p<.001), and a significant order by factor interaction 

(F(1/38)=31.62, p<.001). No other effects were significant. Although no 

differences as a function of target density were found in this analysis, the 

significant order by factor interaction, coupled with an examination of Table 3, 

clearly reveals that it was an increase in feelings of drowsiness rather than 

exhaustion that was produced by the 2-hour monitoring session. 

DISCUSSION 

The results of the present study revealed a rather mixed pattern of performance 

change. Detection times for readily detectable stimuli (LD events) showed a 

slight, nonsignificant increase over the 2-hour session under the lower taskload 

condition and a pattern of increasing followed by decreasing detection times 

under the higher taskload condition. These events were virtually never missed 

under either target density condition. For the more difficult task of detecting 

two aircraft at the same altitude (HD events), detection times increased 

significantly during the session under the higher taskload condition, but also 

increased significantly, and in a parallel manner, under the lower condition. 

While none of the above data would support any suggestion of greater impairment 

under the 16-target condition, this was not the case with data regarding 

failures to detect HD events. It will be recalled that, when an altitude event 

occurred, resulting in two aircraft at the same altitude, this event remained on 

the screen for a period of go s. If the event was not responded to within this 

time period, it reverted back to its previous value, and the failure to respond 

was recorded as a missed stimulus. The number of times that these altitude 

events were completely missed increased significantly during the task session, 

but only when 16 targets were being monitored; no increase occurred when 

monitoring was confined to just eight targets. 

The data for missed events suggest a type of performance decrement in the higher 

taskload condition that was absent in the lower condition. However, it must be 

recognized that this apparent difference between conditions could simply be an 

artifact resulting from the need to place some limit on the length of time that 

a critical event remained on the screen. If it is assumed that each of the HD 

events missed under the 16-target condition would eventually have been detected 

13 
had the events not been "removed" after the 90-s stimulus duration period, one 

could then view these missed events simply as long detection times that 

overlapped the 90-s timeout period with increasing frequency as the session 

progressed. If this assumption is correct, then a comparable increase in long 

detection times may also have occurred under the 8-target condition but, because 

of the lower mean detection times associated with this condition, even extreme 

latencies would likely have had values that fell considerably below the 90-s 

stimulus duration period. In order to examine the comparability of the 

distributions of long detection times under the two taskload conditions, each 

subject's longest detection time for HD events in each of the half-hour periods 

of the session was obtained and means and standard deviations computed. These 

data are shown in Table 4. An analysis of variance revealed a significant 

Table 4. Means and standard deviations (in seconds) of maximum detection 

times over half-hour periods for the two taskload conditions. 

Taskload 

8 Target 

16 Target 

14.43 

(4.71) 

39.29 

(12.54) 

Periods 

2 

19.07 

(7.27) 

39.49 

(16.28) 

3 

18.62 

(8.45) 

46.26 

(12.33) 

4 

21.52 

(15.79) 

41.72 

(12.01) 

conditions effect (F{1/38):106.01, p<.001), but neither the periods effect nor 

the conditions by periods interaction was significant (p>.10). The lack of a 

significant periods effect might be expected if missed events under the 

16-target condition did indeed represent long d~tection times that were not 

included in the latency distributions; the lack of a significant interaction 

effect suggests that no real increase in long detection times occurred during 

the session under the 8-target condition. 

The increase in frequency of missed HD events under the 16-target condition did 

not appear to be dUe simply to a decline in scanning activity. This was 

determined from data obtained for the LD events. In the context of the present 

study, one of the reasons for including these events was to provide a measure of 

detection time to readily detectable stimulus changes, which in turn served as 

an index for assessing the frequency and adequacy of scanning behavior during 

the course of the monitoring session. Thus, ~f failures to scan the screen 

under the 16-target condition occurred~ore frequently during the second hour, 

one might reasonably expect to see an in ease in detection time to LD events 

and possibly even missed stimuli. How ver, detection times to these stimuli 

under the higher taskload condition were virtually the same at the beginning and 

end of the session, and therewas no evidence of any increase in the already 

extremely low frequency of'"missed LD events. (Only two were missed, and both of 

these occurred during the first hour.) 

14 
If we compare the findings of this study with those of our earlier one in which 

we compared monitoring performance to 4, 8, and 16 targets (Thackray et al. 

1979), a number of similarities become apparent. Both studies found evidence of 

performance decline occurring over a 2-hour session of continuous monitoring, 

but only under the highest taskload condition. In our previous study, this 

decrement was due primarily to an increase in the duration of long detection 

times, and this, in turn, was taken to be an indication of increasingly frequent 

lapses or fluctuations of attention. The task employed in this earlier study 

required only the detection of a fixed, three-digit altitude number; these 

events were almost never missed within the 60-s stimulus duration period. In 

the present study, it was an increase in the frequency of HD events missed, 

rather than an increase in time to detect such events, that appeared to 

characterize the 16-target condition. If, as indicated previously, one makes 

the reasonable assumption that each of these events would have been detected, 

albeit with extremely long detection times, had the events not been "removed" 

after the 90-s stimulus duration period, then the findings of the two studies 

become surprisingly similar. For reasons that are not entirely clear, both 

studies found evidence of apparent lapses in the reception or processing of 

sensory information that occurred when monitoring 16 targets, but not when 8 or 

fewer targets were monitored. In the earlier study, these "lapses" were 

manifested as long detection times, while, in the present one, they took the 

form of missed events. In neither study was there any indication that higher 

visual taskloads resulted in performance impairment simply because of a 

reduction in scanning activity. 

We initially hypothesized that apparent lapses in the reception or processing of 

sensory information under conditions of high monitoring load were likely to be 

manifestations of some fatigue process. This hypothesis was supported by the 

findings of the present study that CFF declined significantly (approximately 1 

Hz) under the 16-target condition but showed no change when only 8 targets were 

monitored. A decline of this magnitude would appear to be within the range of 

values reported in other studies of CFF change with fatigue (Grandjean et al. 

1977). These findings with respect to CFF, then, would suggest that this--

measure might be useful in operational situations to assess levels of fatigue. 

Clearly, Grandjean and his colleagues (Grandjean et al. 1971) found this to be 

the case in their study of fatigue among Swiss air traffic controllers. It 

should be noted, however, that that study also found that changes in subjective 

measures of "tiredness" paralleled the decline in CFF. In the present study, 

none of the subjective measures of fatigue that were employed showed any 

differences, either qualitative or quantitative, as a function of taskload. A 

similar lack of relationship of subjective fatigue to taskload was also found in 

our earlier study (Thackray et al. 1979). While one might speculate almost 

endlessly as to the reasons why-subjective fatigue showed no relationship to 

taskload in these two investigations, one reasonable possibility is suggested by 

the findings of the Grandjean et al. (1971) study of controller fatigue. In 

that study, most of the physiological and subjective indices of fatigue showed 

only a slight to moderate decrease (increase in fatigue) during the first 6 

hours of the 10-hour work period; the greatest decrease did not occur until the 

final 4 hours. On the basis of those findings, it is conceivable that the lack 

of relationship of subjective fatigue to taskload that was found in both the 

present study and in our earlier one (Thackray et al. 1979) as well, may have 

been due to the duration of the monitoring sessions-employed. Had sessions 

15 
lasting longer than 2 pours been used, significant relationships of subjective 

fatigue to taskload might have been obtained. 

CONCLUSIONS 

As noted earlier, the increasing automation of air traffic control will likely 

result in the controller becoming less of an active participant in control 

decisions and more of a passive monitor of a system largely run by computers. 

It is frequently assumed that this apparent reduction in workload will enable 

the controller to monitor a larger number of aircraft and hence increase 

productivity (Swedish 1983). For reasons that are not yet well understood, in 

both the present study and our earlier one, and using quite different display 

configurations and task designs, performance decrement, seemingly resulting from 

some fatigue process, was found only under the highest monitoring loads 

employed; there was little or no evidence of any decline in performance under 

the lower taskloads used in each study. What was particularly noteworthy was 

the finding in the present study of a significant increase under the higher 

taskload condition in the number of potential conflicts that were simply not 

"seen" during the 90-s period they were on the screen. While it must be 

recognized that these results were obtained under simulated ATC conditions, and 

that some degree of caution should be exercised in generalizing to operational 

tasks of the future, the findings at least suggest that the assumption of 

increasing productivity through an increase in the number of aircraft handled 

per controller may need to be considered rather carefully in highly automated 

ATC concepts where passive monitoring is a major task component. 

It is evident that the present research has raised certain questions requiring 

further study. These questions include, but are not limited to, the following: 

(1) Since the present study found evidence of performance decrement while 

monitoring 16 but not while monitoring 8 targets, at what level of visual 

taskload would evidence of a significant decline in performance begin to occur? 

(2) What variables, apart from target density, may have contributed to the 

decrement found under the 16-target condition? While considerable information 

exists with regard to variables influencing performance decrement in simple 

vigilance tasks, relatively little research has been conducted to determine 

whether these· same variables affect behavior in a similar manner in complex 

monitoring tasks requiring visual search. 

(3) Why did measures of subjective fatigue fail to show any differences as a 

function of taskloa~Z 

(4) How does the appar-ent fatigue that is associated with monitoring relatively 

large numbers of targets affect other relevant ATC behaviors (e.g., decision 

making, short-term memory, action selection) that were measured but not analyzed 

in the present study? 

Some or all of these questions will be addressed in a planne& study dealing with 

the differential effects of fatigue on the separate behaviors involved in ATC 

conflict detection and resolution. 

16 
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18