Inc(OffSetArrayIdx) ; { Next!
Timingctr := 0; { Reset clock
StoreTestData; { Store data
ClearDevice; { Clear display
UNTIL SessionCtr = 0; 4 Last epoch?
ChoseFileF; { Close output file
CloseGraph; { Must do!
elrser;
writeln;
kO := (RespCtr * 100) DIV TargSymCtr; { Calculate S’s "score."
writeln;
writeln(’ SUBJECT’’S SCORE WAS ’,KO);
ariteln;
writeln(‘ SESSION COMPLETED’ );
write(’ * HIT X TO EXIT, ANYTHING ELSE TO REPEAT.’);

readln(ch0);
UNTIL (chO = ‘x’) OR (chO = ‘X‘);

END.

*U.S.GP0:1992-661-063/40044

A-8

te ee


{ = ;
PROCEDURE StoreConstantData;

BEGIN

{rece= ~ Constants for any one session. -------- }
writeln(F, ‘NAME: +, Sname);

writein(F, ‘AGE: +,8_Age);

writeln(F, ‘SUBJ. ID: *,S_ID);

writeln(E, ‘SEK: *,S_Sex}7

writeln(F, ‘OPTICS?: ', Glasses);

writeln(F, ‘VCS: 1 VCS);

writeln(F, ‘DOM. EYE: +, DominantEye) ;

writeln(F, ‘DATE: +, DZ(day),‘/‘,D2(wonth),°/’, year);
writeln(F, ‘START TIME: «,D2(hour), ‘:',D2(minute) )7
writeln(F, ‘SEGMENT TIME: “yk1)7

writeln(F, ‘NO. OF SEGMENTS: «, Sessionctr);

kO := Of fSetArrayIdx0;

writeln(F, ‘OFFSET SEQ.: «, OffSetArray[k0],‘ ‘,
offSetArray[(kOt+iJ,‘ ‘,
OffSetArray[{kO+2],‘ ‘,

Offsetarray[k0+3});
writeln(F, ‘TARGET: «, TazrgSym) 7
writeln(F, ‘TARGET SIZE: +, CharSize);
writeln(F, ‘SLOWDOWN UNITS: +, SlowDown) 7
writeln(F, ‘L. PIXEL DENSITY: ’, L£tDotProb);
writeln(F, ‘L. LOOP TIME: ' ,L£tLoops)7
writeln(F, ‘R. PIXEL DENSITY: ’ ,»RtDotProb) ;
writeln(F, ‘R. LOOP TIME: ’, RtLoops) 7
writeln; { Blank line for parsing }

END; { PROCEDURE StoreConstantData }

{
PROCEDURE SetUps;

—+--------~--- }

BEGIN
REPEAT
clrser;
writeln(’ <<< SET CAPS LOCK FOR ALL ENTRIES >> >')7
writeln;
writeln;
write(’S. NAME (25 max.): ‘)7
readin(Sname);
write(’AGE (18..40): ‘)7
readin(S_Age);
write(‘S. ID (4 max.): VF
readin(S_ID);
REPEAT
write(‘’SEX (M/F/X): ‘)?
readin(S_ Sex);
UNTIL (S_Sex IN [(‘m’,‘M’,‘£',°F', (x's 'X"))F
REPEAT
write(’OPTICS (N/G/C/X): ‘);
readln(Glasses) ;
UNTIL (Glasses IN (/n‘,‘N’,‘g’,'G', 6", °C", 'x','R'Y)3
write(‘VCS SCORE (5 digits): ‘)7
readin(VCS);

REPEAT
write(‘DOM. BYE (L/R/X): ‘)7
readin (Dominant£Eye);
UNTIL (DominantBye IN [‘r’,‘R',/1',°L','x",X"1)F

A2



increased; (d) the amount of visual noise, or
distraction, present increased. (Note: in much of
what follows we have grouped these factors
under the term "workload," for brevity.) These
hypotheses were based on the truism that any
scanning task requires transfers of visual atten-
tion among the targets and target areas moni-
tored. Each transfer takes time, up to 1 second,
depending on task structure (4, 5). As workload
increases, the percentage of the ATCS’s time
spent transferring attention among targets also
increases. Thus, relatively less time is availabie
for stimulus detection and recognition and errors
will tend to increase.

This paper describes the methods devel-
oped and reports initial results on the eftects of
WorkArea separation on scanning error. We
have also appended a full listing of the program
implementing our test structure because we feel
that this approach has many advantages in eval-
uating vision related perceptual problems in
aviation.

METHODS
General Approach

The purpose of scanning or monitoring
is usually the detection of and response to some
defined symbol, event or relationship, termed
here a "target." A WorkArea, as used here, is a
microcomputer-driven display sub-2.2a in which
some defined target or set of targets is embed-
ded. As in other long term (>60 minute) stud-
ies of scanning and monitoring (2), the variables
to be examined include the number of targets
per WorkArea, the number of WorkAreas to be
searched, the WorkArea size, the separation
between or among WorkAreas, the task com-
plexity within each WorkArea and the relative
task complexity between or among the WorkA-
reas.

Selection of the stimulus configuration
defining a workarea for studies of scanning was

difficult. For example, any study of the factors
affecting an ATCS’s ability to scan and monitor
must include some kind of character search
paradigm since ATCSs must de able to read
alphanumeric information displayed at many
locations on their sector suite or display. Char-
acter search activity can be modeled in several
ways. The simplest and most direct is to look
for one character (e.g., "A") in an array of
characters. The array is usually in a rectangular
format and looks something like this:

QORGXXTB
BROOCOOX
DFOOAOOK
QWOOOOOH
ZXBRPBBW

The "A" tends to pop out of the field as set up
here, but the ability to detect the "A," or any
other character, actually depends on the charac-
ter’s position in the array and on the shape of
the surrounding characters (6). However, the
target should be presented free from any consis-
tently located distracting shapes or patterns that
can affect its readability since such readability
changes could confound changes due to the
desired variables. It is also desirable to study
monitoring efficacy in the presence of visual
noise, since noise is always present on an ATCS
display. The challenge was to devise a character
identification task with noise and without the
kind of pattern interference problem mentioned
above.

The method developed uses two or more
constantly changing random dot WorkAreas into
which the characters are written; the random dot
display giving constantly changing background
noise without patterns to interfere with the
character identification. Producing rapidly chan-~
ging random dot patterns presents problems.
The investigators who first used the technique
employed special hardware built into a mini
computer (7). Others have used very fast mini-
computers or "workstations" with fast graphics
capabilities (B. Frost, York University, Canada,
personal communication). These are extremely



{ PRRRRORAARRAAAAT ARR E RARE TARAS RAARER AR RRRERERRERRERRERRERRERERRRERER EERE EER

{ cc----- NOW, BEGIN the MAIN program
BEGIN

REPEAT

SetUps;
SetGrafix;
Initialization;

- }

{ get & set program variabies
{ Initialize graphics
{ Initialise Variabies, etc.

- Start of main display loop, Exit on SessionCtr = 0 ------- }

Set up array position from OffSet -- }

offset := OffSetArray(OffSetArrayIdx];

LftX := ((GetMaxxX div 2) - 1C0) - (OffSet div 2);

{ array OffSet

RtX z= (GetMaxX div 2) + (OffSet div 2);

{ Write the TargSym cue every time. }

GrafixMsgs;

REPEAT
Left Array ------------------------- }

xO := random(100) + Lftx;

yO := random(100) + LftY;

IF random(LftDotProb) = 0 THEN
PutPixel(x0, yO, color)

ELSE

PutPixel(x0,y0, nocolor);
Inec(LftLoopctr) ;

IF (LftLoopCtr = LftLoops) THEN
BEGIN
Inc (L£tSymbelctr) ;
x1 := (random(80)+10) + LftX;
yl :* (random(80)+10) + LftY;
symO == symbol [{random(5)+1);
OutTextxY(x1, yl, sym0);
IF (symO = TargSym)
THEN
BEGIN
LftTargSymOn := True;
Inc(LftTargSymCtr) ;
Inc(TargSymctr)
END
ELSE
LftTargSymOn := False;

kO := (LftLoops div 2);
kl := random(k0) - (kO div 2);
LftLoopCtr := kl;

END; { IF LftLoopctr }

{ crecoo- End Left Array ------ }

t-

Right Array

xO := random(100) + RtX;

yO := random(100) + RtY;

IF random(RtDotProb) = 0 THEN
PutPixel(x0, yO, color)

ELSE

A6

{ Image at LftxX, Lfty

{ Position pixel

{ Omit pixel
{ Increment counter

{ Ck. ctrs. for symbol display
{ Aha! another symbol

{ Set Symrb5l location
{ dots and position

{ Introduce variability
{ OK
{ Reset @ LftLoops +- LftLoops/4

{ Image at RtxX, RtY

{ Put pixel

Se et ee

we ee

nd


TABLE II

STATISTICAL TEST RESULTS
WILCOXON MATCHED PAIRS TEST

PAIRED

SEPARATIONS~ p<

0.3 - 4.7 0.001**
0.3 - 9.3 0.00001**
0.3 - 14.0 0.00001**
4.7 - 9.3 0.2

4.7 - 14.0 0.02*
9.3 - 14.0 0.8

ke
*

wou

Table II shows analyses for paired seg-
ments and paired separations. In each instance,
the hypothesis tested was that the first element
of the pair was larger than the second. Table II
clearly shows that the differences in perform-
ance between 0.3 arc degrees and the other
separations were highly significant. The data
also indicates that performance does not change
much as separation increases beyond 4.7 arc
degrees. That is, our initial hypothesis was true:
performance does become worse as separation
increases from 0.3 to 4.7 arc degrees, though,
surprisingly, not much change is seen beyond
that. The small performance decrement seen at
the wider separation surprised us, and warrants
further study.

We evaluated possible practice effects
by comparing performance in the first segment
to that in succeeding segments. Table II shows,
as Table I suggests, that there were no signifi-
cant practice effects: that is, there are no signifi-
cant differences in performance among the
segments. The test was designed to be simple to
learn and to do, and this intent was realized.
The test was also designed to show some fourth
segment "fatigue" effects since preliminary test
runs, using CAMI personnel as Ss, suggested

PAIRED

SEGMENTS p<
ist - 2nd 0.3
1st - 3rd 0.8
ist - 4th 0.8
2nd - 3rd 0.8
2nd - 4th 0.9
3rda - 4th 0.9

separations in arc degrees.
Significant differences.
Differences probably significant.

that such effects might occur. However, no such
effects were seen. It may be significant that the
ages of the CAMI personnel tested were rather
greater than the ages of the Ss used in the study.
Such an age effect may be an important factor
in scanning and monitoring performance and,
again, warrants further study (9).

The raw data in Table I shows that
performance varied quite widely among the Ss.
Performance studies done without reinforcement
(i-e., without rewards for good performance or
punishment for bad) can be difficult to interpret,
since there is no way to control or evaluate a
subject’s motivation and/or effort during the
test. Like most experiments of this kind in the
literature, no reinforcements were used for this
study. Therefore, we instituted tests, now under-
way, using identical test procedures and param-
eters, but adding a simple positive reinforce-
ment: Ss are rewarded with extra money if their
performance exceeds the average levels reported
here, These experiments should indicate whether
reinforcement for good performance will be
desirable for future experiments and may indi-
cate whether, or to what extent, the present
results may be misleading.


Figure 1

movements were :ninimized by suitable location
of S’s seat, the keyboard, the display and a
mask surrounding the display. Direct observ-
ation of Ss indicate that this was fairly success-
ful, with actual eye to screen distances ranging
from 40 cm to 70 cm. The individual test ses-
sions were designed to run for 80 minutes with
an additional 10 minutes allotted for administra-
tive details.

The character set used was "23580."
These numerals were selected after preliminary
evaluation and extensive literature review (6).
The "5S" was selected as the target symbol to
simplify the program but only after preliminary
experiments indicated that, in this system, the
readability of all of these numbers was equal.
The target symbol was constantly displayed to
the Ss in a cue line (i.e., "The target symbol is
5.") at the top center of the display (not shown
in Figure 1), All symbols were presented at ran-
domly selected locations within the WorkArea
and at some average interval, randomly varied.
The probability of occurrence of the target
symbol was separately programmable. The
symbol presentation interval in each WorkArea
averaged 3 seconds with a programmed random
variation of plus or minus 0.75 seconds. This

interval and the pixel replacement rate combine
to give a moderate workload: the Ss could do
the test adequately, but constant attention was
tequired and it was not possible to work without
errors.

The task of the Ss was to monitor the
WorkAreas for the appearance of the target
numeral. If the target appeared in the lef: Work-
Area, S pressed the left arrow key on the key-
pad. If the target symbol appeared on the right,
S$ pressed the right arrow key. Thus S’s “per-
ception to response” coupling was simple, "right
side to right key" and “left side to left key."
The intent here was to make the system so
simple to learn that training time would be
negligible and little practice effect would be
seen within each test session. This intent was
realized as shown by the data cited below.

As implemented in the program, two
types of errors could be made by the Ss. An
error of commission, or of recognition, occur-
ted when § depressed a key when there was no
target symbol on the key side or if S responded
more than once to the same target presentation.
An error of omission, or detection, occurred if
an S did not press the proper key in the interval


effective approaches but beyond the resources
presently committed to this project. Therefore,
we developed a relatively simple software meth-
od of generating random dot <:rays using an "8
MHz" IBM PC-ATTM with an EGA adapter and
color display. A listing of the Borland Turbo
Pascal 5.5TM program used for these experiments.
is appended. The resulting software controlled
random doi display runs slowly, limited by the
compiler, processor and graphics board used.
The slow running speed, in turn, limited both
the WorkArea size and the number of Work-
Areas that could be used. However, this ap-
proach can give useful results, used within its
limits.

For the first studies, we used two Work-
Areas; rectangular screen areas filled with a
constantly changing random dot array. The
random dot writing process continually over-
wrote (i.e., erased) any characters displayed in
the WorkArea. Thus, a character’s legibility
was maximum when first displayed and deterio-
rated over time. This use of the random dot
writing process to slowly erase the displayed
symbol is unusual and, perhaps unique, as we
have not found similar approaches in the litera-
ture. When targets are presented in this way, the
subject (S} must respond relatively quickly to a
target presentation lest the symbol become illeg-
ible or changed enough to be confused with
other symbols (e.g., as written on the screen,
"8" and "3 can be confused after replacement of
one or two pixels}.

Workload can be easily varied by chan-
ging parameters such as the dot density within
the WorkArea, the rate of presentation of the
characters, the size of the set of displayed char-
acters and the probability of occurrence of the
defined “target character.”

Figure 1 is 2 reverse contrast full-scale
printout of two rectangular WorkAreas separ-
ated by 7 millimeters (mm). It illustrates the
main test display characteristics noted above.
However, contrast was reversed (black on white
rather than white on black) to improve print-out

legibility. Note the "3" near the center of the
left WorkArea. It was writtea 0.5 seconds be-
fore the frame was “frozen” for printout. It is
still clearly legible. The top center of the left
WorkArea has the remains of another “3,”
written 2.0 seconds before the first "3." The
remains of a "5," written at the same time, can
be seen in the bottom right corner of the right
WorkArea.

The pixel writing process replaces about
720 or 7% of the pixeis in each WorkArea each
second, limited mostly by the speed of the EGA
adapter. Our preliminary measurements suggest
that a symbol remains clearly recognizabie for
1.5 + 0.5 seconds, with some fragments visible
for 6 + 2 seconds. The times vary due to the
vagaries of the random number driven pixel
placement process. Thus, as shown in Figure 1,
the remains of one or moze symbols may be
present when a new one is displayed. Since the
minimum interval between character presen-
tations is 2.25 seconds, there is always a clear
difference between the newly displayed symbois
and the “older” ones. These old symbols do,
however, constitute another visual “noise” factor
on the display. Since these noise locations vary
randomly over time, no consistent pattern is
present and the readability problems mentioned
earlier do not seriously obtrude.

Implementation

Two WorkAreas are present. Each is a
100 by 100 pixel array, or 10,000 pixels per
WorkArea. The WorkArea’s on-screen size is
31 mm by 31 mm. At the normal viewing dis-
tance of approximately 60 centimeters (cm),
each WorkArea subtends 3.3 degrees of arc and

each pixel subtends 2 minutes of arc. In fact, °

the angular sizes are approximate because a
subject’s eye to screen working distance does

vary somewhat through any test session. Vari- _

ous systems to control head movement were
considered, and tested, but discarded as too
cumbersome or uncomfortable. Rather, head

‘Dist H

ey

re
a4
a]
o
Tae

f

aunility Cod
eit and/or
Special



PutPixel(x0,y0, nocolor);
Inc (RtLoopttr) ;
IF (RtLoopCtr = RtLoops) THEN
BEGIN
Inc(RtSymbolctr) ;
x1 s= (random(80)+10) + RtX;
yl := (random(80)+10) + RtY;
syml := symbol [random(5)+1);
OutTextxY¥(x1, yl, symi);
IF (syml = TargSym)
THEN
BEGIN
RtTargSymOn :* True;
Inc(RtTargSymetr);
Inc(TargSymctr)
SND

ELSE
RtTargSymOn := False;

kO := (RtLoops div 2);
kl := random(k0O) - (kG div 2};
RtLoopctr := ki;

END; { IF RtLoopCtr }
{ corece End Right Loop ------ }
FOR ctr0O := 1 TO SlowDown DO

FOR ctrl := 1 TO 30 DO;

Begin the keyboard monitor routine.

IF KeyPressed THEN
BEGIN
chO :* ReadKey;

?
All Keys other than ‘4’ and ‘6’ are ignored.

{ Or dont put it }
{ Begin Check Right Loop Ctr }
{ Yet another bloody symbcl. }

{ Adds variability }
{ OK }
{ Reset @ RtLoops +- RtLoops/4 }

{ SlowDown multiplier }
{ 100 microsec delay per unit. }

IP (chO = '4°) AND (LftTargSymOn = False) THEN

BEGIN
LftErrctr := LftErrctr + 1;
Beeper

END;

IF (chO = ‘4°) AND LftTargSymOn THEN

BEGIN
Inc(LftRespCtr) ;
Inc (RespCtr);
LftTargSymon := False
END; { IF }

IF (chO = ‘6*) AND (RtTargSymOn = False) THEN

BEGIN
RtErrCtr := RtErrCtr + 1;
Beeper

END.

3
IF (chO = ‘6’) AND RtTargSymon THEN

BEGIN
Inc(RtRespctr) ;
Tne(RespCtr) 7
RtTargSymOn := False
END; { IF }
END; { IF KeyPressed }
{ soose- OK, End KeyPad Check ------ }

Inec(TimingCtr) ;

UNTIL (TimingCtr = TimeRef);
Dec (Sessionctr);

A-7

{ Completed? }


SID*

All9
A115
All1l
Al31
A127
A123
A107
A103
A126
All4
A122
aAl18
A102
A130
A110
A106
A101
A129
A125
Ai21
A105
aAl13
A109
Al17
A120
A116
A132
A108
A104
A124
A112
A128

MEAN

STDEV

MAX
MIN

0.3

87.4
95.4
92.9
94.7
79.1
92.6
76.9
91.1
87.7
72.5
86.3
85.3
72.5
91.7
84.6
80.7
87.5
88.8
87.1
85.2
92.3
86.3
74.2
62.5
88.€
92.0
78.2
86.4
77.4
89.7
71.21
86.5

84.55

7.78
95.43
62.50

®

Percent Correct Responses for each Subject
By separation (degrees) and by segment.

SEPARATION
4.7 9.3
87.7 83.8
93.1 91.3
86.5 79.3
93.7 90.8
80.0 77.1
88.5 93.7
74.7 60.1
94.4 88.3
82.7 84.9
71.6 57.0
76.9 77.2
79.4 71.0
78.3 56.9
80.8 81.9
75.7 79.7
69.4 79.4
89.1 82.9
87.9 86.4
89.9 80.9
80.6 66.5
81.1 76.0
75.5 78.8
59.6 73.4
58.5 50.3
86.3 79.7
85.9 89.0
68.4 64.8
87.6 83.6
62.1 67.1
81.6 80.3
47.1 64.0
68.4 77.8
78.86 76.69
11.03 10.72
94.41 93.66
47.13 50.31

TABLE I

14.0

83.1
88.6
77.8
90.8
71.3
83.6
54.0
90.1
88.4
65.4
78.4
78.7
56.6
77.9
82.1
68.2
93.2
83.9
86.0
73.9
75.9
78.4
47.2
54.8
82.8
89.0
66.3
81.2
66.5
80.0
64.5
69.9

75.89
11.60
93.17
47.22

1

87.4
95.4
92.9
94.7
79.1
92.6
76.9
91.1
82.7
71.6
76.9
79.4
78.3
80.8
75.7
69.4
82.9
86.4
82.9
66.5
76.0
78.8
73.4
50.3
82.8
89.0
66.3
81.2
66.5
80.0
64.5
69.9

78.77

9.88
95.43
50.31

SEGMENT
2 3
87.7 83.8
93.1 91.3
86.5 79.3
93.7 90.8
80.0 77.1
88.5 93.7
74.7 60.1
94.4 88.3
88.4 87.7
65.4 72.5
78.4 86.3
78.7 85.3
56.6 72.5
77.9 91.7
82.1 84.6
68.2 80.7
87.9 93.2
88.8 83.9
87.1 86.0
85.2 73.9
92.3 75.9
86.3 78.4
74.2 47.2
62.5 54.8
73.7 86.3
89.0 85.9
64.8 68.4
83.6 87.6
67.1 62.1
80.3 81.6
64.0 47.1
77.8 68.4
80.15 78.33
10.08 12.53
94.41 93.66
$6.65 47.13

4

83.1
88.6
77.8
90.8
71.3
83.6
54.0
$o.1
84.9
57.0
77.2
71.0
56.9
81.9
79.7
79.4
89.1
87.9
89.9
60.6
81.1
75.5
59.6
58.5
88.6
92.0
78.3
86.4
77.4
89.7
71.1
86.5

78.74
10.94
92.00
$3.99

SID = Subject Identification Data Block Number.



DOT/FAA/AM-92/12

Office of Aviation Medicine
Washington, D.C. 20551

AD AZte . 123

to)

A New Test of Scanning
and Monitoring Ability:
Methods and Initial Results

A.M, Revzin
P.G. Rasmussen

Civil Aeromedical Institute
Federal Aviation Administration
Oklahoma City, Oklahoma 73125

March 1992
DTIq
ELECTS

Toterim Report APR2 2 1992

5B @:

This document is available to the public
through the National Technical Information
Service, Springfield, Virginia 22161.

U.S. Department
of Transportation

Federal Aviation
Administration

92-10089
ace


REFERENCES.

1. Hopkin VD. Air Traffic Control. In: Wiener
EL, Nagel DC. eds. Human factors in aviation.
San Diego: Academic Press; 1988:83-110.

2. Moray N, Rotenberg I. Fault management in
process control: eye movements and action.
Ergonomics 1989; 32:1319-42.

3. Moray N. Monitoring behavior and super-
visory control. In: Boff KR, Kaufman L,
Thomas JP, eds. Handbook of perception and
human performance. Vol II. New York: John
Wiley; 1986.

4. Flowers JH, Lohr DJ. How does familiarity
affect visual search for letter strings? Percep-
tion & Psychophysics 1985; 37:557-67.

5. Morris A, Temme LA. The time required
for U. S. Navy fighter pilots to shift gaze and
identify near and far targets. Aviat. Space En-
viron. Med. 1989; 60:1085-9.

6. Boles DB, Clifford sE. An upper- and
lowercase alphabetic similarity matrix, with
derived generation similarity values. Behav.
Research Meth. Instruments & Comput. 1989;
21:579-36.

7. Julesz B. Foundations of cyclopean percep-
tion. Chicago: University of Chicago
Press;i97i.

8. Bradley JV. D:.tribution-free statistical tests.
Englewood Cliff;. Prentice-Hall; 1968.

9%. Ball KK, Beard BL, Roenker DL, Miller
RL, Griggs DS. Age and visual search: expan-
ding the useful field of view. J. Opt. Soc. Am.
A. 1988; 5:2210-19.


The large variations among Ss are sig-
nificant in other ways. Limited test-retest data
suggests that a subject’s performance remains
stable over time. If so, it seems possible that a
Scanning test similar to this could be used in
screening ATC personnel for selection or reten-
tion. Also, some performance, scanning and
monitoring studies are done with small numbers
of Ss, frequently less than 10 (2). This raises
sampling error concerns. If 19 Ss who score
well happen to be selected the results will differ
somewhat from studies that happen to select Ss
with poor performance. Though 32 Ss is not a
large number, the very fact of the variability
indicates that the performance distribution in our
Ss may be typicai of the general population of
19 to 40 year olds.

Preliminary analyses, to be reported in
a subsequent publication, suggest that no “lock-
ing" occurs, even at the largest separations.
This is not surprising. Workloads were nothigh,
nor were error rates. Thus,some of the factors
which could induce selective attention (2) were
missing. Furtiermore, the workloads in the
WorkAreas were identical, as were the points
deducted for each error, so there was no reason
for any S to concentrate on one WorkArea
rather than the other. The effects of both fac-
tors, differential workloads and differential

reinforcement values, will be separately evaluat-
ed in the experiments to follow.

CONCLUSIONS.

The intent of the current paper is to
present a new test of scanning/monitoring per-
formance and to report some initial data show-
ing that application of the method produces
meaningful data.

Available resources permit testing of 3
or 4 Ss each day depending on task training and
practice requirements for special situations.
Thus, we can study large numbers of Ss more
quickly and efficiently then if we used more
traditional methods which require significant
training or practice times. In addition, paramet-
ric variations can be introduced readily, as req-
uired. Thus, to date, the test seems effective,
flexible, and powerful. Even these early results
clearly show that performance suffers as the
angle scanned increased from 0.3 to 4.7 degrees
of arc. This argues, not surprisingly, that
ATC’s sectors should be kept as compact as
possible to minimize scanning errors. Further-
more, there is no evidence of any selective
attention effects. Thus, separation, by itself,
probably does not induce the “locking” effect.


between the appearance of a target symbol and
the appearance of the next symbol in that area.
The preliminary analyses reported below, how-
ever, consider only the percentage of correct
tesponses made. A fuller analysis, considering
detection and recognition errors and any “lock-
ing" phenomena will be combined with later
data and prepared for publication in a subse-
quent report.

In these experiments a constant and
equal workload was used in each of the two
WorkAreas. The WorkAreas separations were 3
mm, 42 mm, 84 mm, and 126 mm (0.3, 4.7,
9.3 and 14 degrees of arc, respectively), inner
edge to inner edge.

Each subject was tested in one session
lasting for 80 minutes. Thirty two Ss were used,
19 to 40 years of age. The Ss were volunteers
recruited and paid by 2 local contractor. None
had prior ATC experience. We measured each
S’s vision using a VisTech TM visual contrast
sensitivity test system. Each $ was also tested
for “right eye” or "left eye” dominance so that
any positional effects due to eye dominance or
“handedness” could be measured. The age and
sex of each S$ were also noted. All this required
about 10 minutes. The S was then taken to the
testing setup and was given a brief but thorough
introduction to the test, during which we ex-
plained the purposes of the study and the struc-
ture of the task.

Each test session was divided into 4 seg-
ments of 20 minutes each. There was a 3 second
interval between segments and no “breaks” in
the session were permitted. The WorkArea
separation differed from segment to segment.
The order of presentation of the separations was
determined by a balanced latin square experi-
mental design. That is, each S$ worked at all 4
separations and all separations were present in
equal numbers. Thus each S’s performance
could be evaluated in terms of order of presen-
tation and/or WorkArea spacing, and perfor-
mance could also be evaluated for practice or
fatigue effects.

The software program created separate
individual data and performance disk files for
each S. For analysis, the text files were append-
ed to a database file and parsed to form maninu-
lable data structures which could then be passed
to a spreadsheet or a statistical program for
detailed analysis.

Data was analyzed using standard statis-
tical procedures provided in the "Number
Cruncher Statistical System TM" (NCSS) pro-
gram. Since the raw data distribution was
skewed, non-parametric analyses were normally
used, predominantly the Wilcoxon matched pairs
two-tail test. More conventional t-tests were also
used.

RESULTS and DISCUSSION.

Tnitial results from the 32 Ss are presen-
ted in Table I. The data are presented as the
percentage of correct responses for each § at
each each separation and within each segment,
together with the means, standard deviations,
maxima and minima for each category. Note
that the operation of the random number genera-
tor controlling symbol presentation is such that
ia any given segment, the number of neutral
symbols differs among the Ss. Therefore we
used percentages to ensure data comparability
among Ss.

In Table I the averages for percentages
correct responses at various separations (in the
line labeled MEN) suggest that the mean
percentage of correct responses decreased as a
function of WorkArea separation. These raw
numbers also suggest that, though the best
performance was at a separation of 0.3 arc
degrees, there was little difference in perfor-
mance at the larger separations. Further, the
mean percentage of correct responses did not
seem to differ significantly among the test seg-
ments. The data was evaluated for significance
using the non-parametric Wilcoxon Test (8) and
conventional t-tests. The results were identical.


ABSTRACT

Most tasks in the FAA’s Air Traffic
Control {ATC) system involve long duration
scanning and monitoring for continuously chan-
ging events occurring within a large visual
space. Errors occur, so it is important ta un-
derstand the causes cf such errors to minimize
or eliminate them by changing task design or
improving personnel selection. This study de-
scribes a new system for testing scanning and
monitoring abilities. The system, as currently
impiemented, is basically a character identifica-
tion task, The characters are presented at ran-
dom intervals and locations within two or more
"WorkAreas". The WorkAreas are defined as
rectangular areas on a microcomputer display
screen. They are filled with a constantly chang-
ing random dot pattern and may be located
anywhere on the screen.

The subject’s task is to press a designat-
ed key on the computer keypad when a specified
target character appears. Parametric manipula-
tions can evaluate the effects on performance of
many variables, including angular separation of
WorkAreas, differential workloads in the Work-
Areas, and effects of visual noise.

The results of the initial experiments are
presented. We found a highly significant perfor-
mance decrement as a function of increasing
angular separation of WorkAreas. This is con-
gruent with prior studies, which we interpret as
a validation of our test procedure. We did not
find practice effects, fatigue effects or selective
attention effects between WorkAreas. The sig-
nificance of these results is discussed.

INTRODUCTION

This research was undertaken to exam-
ine some factors that couid contribute to scan-
ning and/or monitoring errors in the ATC sys-
tem. Most tasks in the ATC system involve
scanning for and monitoring discrete events, or

targets, occurring over a wide visual angle.
Individual air traffic control specialists (ATCSs)
may sit in front of a visually complex sector
suite subtending an overall visual angle of 120
degrees or more, depending on the position of
the ATCS’s head relative to the screen. Scan-
ning and monitoring over so wide an area is
difficult, and errors do occur. However, though
scanning or monitoring problems were often
mentioned in conversations we have had with
ATCSs, such problems are seldom discussed in
standard aviation references (1), thougii they
have received considerabie attention in the
process control literature (2).

Personal observations and conversations
with instructors at the Federal Aviation Admin-
istration Academy suggest that both errors of
detection and errors of recognition occur. A
typical detection error occurs when an ATC
fixes attention on, or “locks" onto, one very
small display area and does not zespond to
anything else on the display. A recognition error
occurs when an ATCS does perceive a target,
but responds improperly. Such errors are usual-
ly caused by the complex behavioral factors
controlling attention and set (e.g., boredom,
fatigue, workshift changes, illness, drugs, medi-
cations, environmental toxicants) (3). However,
factors related to the spatio-temporal distribution
of information on the display may synergically
interact with these. For example, the probability
of a detection error may be influenced by the
number, spacing and relative velocities of tar-
gets or by the required number of operational
decisions per unit time.

Since scanning/monitoring errors are
perceived as a problem by ATCSs, we initiated
an investigation of the factors contributing to
such performance errors. The first group of
experiments examined the effects of varying the
spatio-temporal distribution of information on
the display. We began with the working hypoth-
eses that scanning oz monitoring errors would
increase as: (a) target separation increased; (b)
the number of targets or target areas increased;
(c) the rate of change of target area components


REPEAT
{ - Check to see if file already exists! - }
write(‘DIR. & FILENAME (20 max.): ‘)7
readin(OutFile);
Assign(F, OutFile);
{SI-}
Reset (F);
k2 := IORecult;
{$I+}
IF k2 = 0 THEN
BEGIN
Beeper;
writeln;
writeln( ‘<<< FILE ALREADY EXISTS >>> ‘);
writeln;
writeln(‘OVERWRITE EXISTING FILE? Y = YES, N FOR NEW FILE‘);
readin(ch0);
writeln;
BND; { IF }
UNTIL (k2 <> 0) OR (chO = ‘y’) OR (chO = ‘Y¥’);
Assign(F, OutFile); { OK. ReAssign File }
Rewrite(F); { & prepare for writing }
GetDate(year, month, day, dayOfWeek);
GetTime(hour, minute, second, se 100);

REPEAT

write(‘SEGMENT TIME (1..20 min.): ‘)7

readin(k1); { kl is a scrap integer location }
UNTIL (ki IN [1..20});

TimeRef := k1*(60000C00 DIV 574); { Sets Pixel loop TimeCtr reference }
REPEAT

write(‘OFFSET SEQ. {1..4): ‘)¢

readln(k0);

UNTIL kO IN [{1..4];

REPEAT

write(‘NO OF SEGMENTS (1..4): ’);
readla(SessionCtr);
UNTIL SessionCtr IN [1..4];
CASE kO OF
1: O£fSetArraylIdx
2 offSetArrayldax
3 offSetArrayIdx
4a offsetArrayldx
END; { CASE }
offSetArrayIdx0 := OffSetArrayidx; { set for data out }
REPEAT

write(’TARGET SYMBOL (8, G, 5, 3, or 2): ‘)?

readln(TargSym) ;
UNTIL (TargSym IN ['8°,'0','S','3',°2°})%
REPEAT

write(‘TGT. SIZE (4..6): ‘);

readin(CharSize);
UNTIL (CharSize IN [(4.-6]});

REPEAT
write(‘SLOW PIXEL CHANGE RATE? (¥/N): ');
readin(ch0);
UNTIL (chO IN {’n’,‘N’,’y’,‘¥'})5
IF (chO = ‘y’) OR (chO = ‘Y’) THEN
BEGIN
REPEAT
write(‘SLOWDOWN CONSTANT (1..10): ‘)7
readln(SlowDown)

A-3


LétErrctr z= 0;

writeln(F, ‘R. # SYMBOLS: + RtSymbolctr);

RtSymbolCtr := 0;

writeln(F, ‘R. TARGETS: *, RtTargSymCtr);

RtTargSymtr := 0;

writein(F, ‘R. CORRECT: «, RtRespctr);

RtRespctr := 0;

writeln(F, ‘R. ZRRORS: *, RtErrctr);

RtErrCtr := 0;

writeln; { Blank line to terminate file segment.

END; { PROCEDURE StoreTestData }

{ wes enone nanan na nn enc en enc nnnncencnnencons }

PROCEDURE ClosePileF;

BEGIN
Close(F);
END: { CloseFileF }

{
PROCEDURE SetGrafix;

BEGIN

GrDriver := Detect;

InitGraph(GrDriver, GrMode, ‘c:\tp\bgi’);

NOTE: for production, set InitGraph to get BGI stuff in default
directory, where I will put it.

-- 3
GrError :=* GraphResult; { GraphResult is in BGI
IF GrError <> GrOK { GrOK in BGI
THEN

writeln(’GRAPHICS ERROR: ‘, GraphErrorMsg(GrError));
END; { PROCEDURE SetGrafix }
t- - 3
PROCEDURE GrafixMsgs
BEGIN
SetTextStyle(SmallFont, HorizDir, CharSize);
color := 15; { white points
nocolor := 0; { black is the nocolor
SetTextJustify(CenterText, CenterText); { Messages to Screen
Out TextxXY((GetMaxX div 2), 15, ‘Target Symbol is ‘);
OutTextXY((GetMaxxX div 2)+(TextWidth(TargSym)*8), 15, TargSym);
SetTextJustify(LeftText, TopText);
END; { PROCEDURE GrafixMags }

{ -~ }

PROCEDURE Initialization;

BEGIN

chx <:* ‘a’; { Begin initialisation
TimingCtr := 0; { Start time @ 0!
L£&tY := (GetMaxY div 2) - 50; { both arrays on same horizontal
RtY := (GetMaxY div 2) - 50;

LftSymbolctr := 0; RtSymbolCtr := 0; { total # symbols
LftLoopCtr := 0; RtLoopCtr := 0; { Loops for symbol display
LftTargSymctr := 0; RtTargSymCtr := 0; TargSymCtr := 0;

LftRespCtr := 0; RtRespCtr := 0; RespCtr := 0; { Correct response ctrs.
LétErrctr := 0; RtErrCtr := 0; { Error ctre.
LftTargSymOn := False; RtTargSymOn := False; { TargSym on screen?
RandSeed := 314759; { Same random number sequence for everyone.

END; { PROCEDURE Initialisation }

AS

+

ere



Technical Report Documentation Page

. Report No, 2. Government Accesston Neo. 3. Recipient's Cotolog No. |

DOT/FAA/AM-92/12

4. Tithe and Subtitle 3S. Report Dote |
A New Test of Scanning and Monitoring Ability: Methods | March 1992
and Initial Results 6. Performing Orgenizanon Code

8. Performing Orgamzotion Repert No.

7. Authar’s)
A. M. Rewzin, Ph.D. and P.G. Rasmussen, M.B.A.

9. Performing Orgenizotion Nome and Address 10. Work Unit No. (TRAIS)
FAA Civil Aeromedical Institute

P.O. Box 25082 Tl. Contract cr Grant No.

Oklahoma City, OK 73125

13. Type of Report and Period Covered

12. Sponsoring Agency Name and Address
Office of Aviation Medicine

Federal Aviation Administration
800 Independence Avenue, S.W. 14. Spe 1soring Agency Code
Washington, D.C. 20591

15. Supplementary Notes

This work was performed under Task AM-A-91-PHY-146.

16. Abstreer

Most tasks in the FAA’s Air Traffic Controi (ATC) system involve
long duration scanning and monitoring for continuously changing events
occurring within a large visual space. Errors occur, so it is important
to understand the causes of such errors to minimize or eliminate them by
changing task design or improving personnel selection. This study
describes a new system for testing scanning and monitoring abilities.
The system, as currently implemented, is basically a character
identification task. The characters are presented at random intervals
and locations within two or more "WorkAreas." The WorkAreas are defined
as rectangular areas on a microcomputer display screen. They are filled
with a constantly changing random dot pattern and may be located
anywhere on the screen.

The subject’s task is to press a designated key on the computer
keypad when a specified target character appears. Parametric
manipulations can evaluate the effects on performance of many variables,
including angular separation of WorkAreas, differential workloads in the
WorkAreas, and effects of visual noise.

We found a highly significant performance decrement as a function
ef increasing angular separation of WorkAreas. This is congruent with
prior studies, which we interpret as a validation of our test procedure.
We did not find practice effects, fatigue effects, or selective
attention effects between WorkAreas.

17. Key Words 18. Distribution Stetement
Vision Requirements Document is available to the public
Scanning/Monitoring through the National Technical Information
Medical Certification Service, Springfield, VA 22161
Air Traffic Control
19. Security Classif, (of this report) 20. Security Clossif. (of this page) DNs. ef Pages ] 22. Price
i Daclassified Unclassified 20

Form DOT F 1700.7 1-72) Reproduction of completed poge authorized


NOTICE

This document is disseminated under the sponsorship of
the U.S. Department of Transportation in the interest of
information exchange. The United States Government
assumes no liability for the contents or use thereof.


PROGRAM SCANISA;

USES
dos, crt, graph ;
CONST
Symbol : string[5} = ~20532';

oOffSetArray : Array[1-.16} OF integer = (280,10,420,140,

140,420,10,280,
10,140,280,420,
420,280,140,10);
VAR
Sname : string{25]; { Name
S_Age : atring[{2}; { Age
S_ID : string{[5]: { S‘s ID

S_Sex, Glasses, DominantEye : char;

ves : string{5);

year, month, day, dayOfWee, : word;

hour, minute, second, secl00 : word;
TimeRef, TimingCtr : Longint;

SessionCtr : integer;

F : text;

OutPFile : string[20};

GrDriver, GrMode, GrError : integer;
TargSym : char;

x0, x1, yO, yl : word;

kO, kl, k2 : integer;

offSet =: integer;

offSetArrayldx, OffSetArrayIdx0 : integer;
LEtX, RtX, LEtY, RtY : integer;

etrO, ctrl, ctr2 : integer;

LftDotProb, RtDotProb : integer;
LfitRespCtr, RtRespCtr : integer;
LftErrctr, RtErrctr 3: integer;
LftSymbolCtr, RtSymbolCrr : integer;
LftTargSymCtr, RtTargSymCtr : integer;
RespCtr, TargSymCtr : Longint;
LftLoopCtr, RtLoopCtr : integer;
LftLeops, RtLoops : integer;
SlowDown : integer;

color, necolor : word;
CharSize : word;

symO, syml, sym2 : char;

ch0O, chi, ch2, ch3, chx : char;
LftTargSymOn, RtTargSymOn boolean;

> << = ?
PROCEDURE Beeper;
BEGIN

sound (1000);

Delay(75);

nosound;
END; { Beeper }

{ o— —- }
FUNCTION D2 (k2:word) : word;
BEGIN
IF k2 < 10 THEN write(‘'0’);
D2 := k2;
END; { FUNCTION D2 }

A-l

{ Pixel

{ Obvious
{ VCS score
{ Date info.
{ Session start time
{ PixelLoop Ctr for epoch time
{ # epochs
{ For output
{ Path & filename
{ graphics initialization
{ Target character
{ Array output locations
{ Misc. temp. variables
{ Display separation
{ OffSet seq.
{ Array Locations
{ Miec. counters
{ "On" pixel density
{ Correct response ctrs.
{ Error ctrs.
{ how many symbols?
{ TargSym cts.
{ Ctrs. for “scoring.*
loop ctrs.-loop freq. control.
{ Symbol display freq.
{ Pixel loop slowdown

{ Size of chars.

{ Keep track of symbols
{ Utility loc. for chars.

{ For time conversion }

Le et et Sat at ae a at a ae Sa Se Sa Se ae at a pt apd a a at a Sa a a Aa


UNTIL (SlowDown IN [1..10});
=ND
ELSE
SlowDown := 0;
write(‘ALL ENTRIES CORRECT?

readln(ch0);
UNTIL (chO = ’y’) OR (chO = ‘Y');
REPEAT

elrser;

writeln(’ENTER LEFT ARRAY VARIABLES -‘);

writeln;

REPEAT
write(’ L. PIXEL DENSITY (8..40) : 'y
readln(LftDotProb);

UNTIL (LftDotProb IN [8..40])s

REPEAT
write(’ LOOP COUNT (2,000..7,000) : ‘)
readln(LftLoops);

UNTIL (LftLoops > 1999) AND (LftLoops < 7001)

writeln;

writeln;

writeln(’ENTER RIGHT ARRAY VARIABLES -‘);

writeln;

REPEAT
write(’ R. PIXEL DENSITY (8..40) : ")

readln(RtDotProb) ;
UNTIL (RtDotProb IN [8..40]);
REPEAT
write(’ LOOP COUNT (2,000..7,000) : ‘)
readln(RtLoops) ;
UNTIL (RtLoops >1999) AND (RtLoops < 7001);
writeln;
Mem{ $0000: $0417)
writeln;
write(‘ALL ENTRIES CORRECT? Y = YES,
readin(ch0);
UNTIL (chO = "y’) OR (chO = ‘Y');
StoreConstantData;
clrscr;
writeln;
writeln;
writeln;
writeln;
writeln;
write(’
readin;
END; { PROCEDURE SetUps }

r= 32;

5 Siepehenetenntuteteteieiateinieieieieneneneenainial }
PROCEDURE StoreTestData;

BEGIN

writeln(F, ‘ARRAY OFFSET: ‘, OffSet);
writeln(F, ‘L. # SYMBOLS: ‘, L£tSymb> .Ctr);

LftSymbolctr := 0;

writeln(F, ‘L. TARGETS: ‘,L£tTargSymCtr) ;
LftTargSymCtr := 0;

writeln(F, ‘L. CORRECT: ’, LftRespctr);
LftRespCtr := 0;

writeln(F, ‘L. ERRORS: +, L&tErrCtr);

A4

Y = YES, N = REPEAT SCREEN:

a

{ Sets NumLock ON }

N = REPEAT SCREEN: ‘)7

{ Store screen entries }

Press RETURN to start.’);

{ Reset counters }