Reserve attention capacity of a pilot was calculated using a pilot model that allocates exclusive model attention according to the ranking of task urgency functions whose variables are tracking error and error rate. The modeled task consisted of tracking a maneuvering target aircraft both vertically and horizontally, and when possible, performing a diverting side task which was simulated by the precise positioning of an electrical stylus and modeled as a task of constant urgency in the attention allocation algorithm. The urgency of the single loop vertical task is simply the magnitude of the vertical tracking error, while the multiloop horizontal task requires a nonlinear urgency measure of error and error rate terms. Comparison of model results with flight simulation data verified the computed model statistics of tracking error of both axes, lateral and longitudinal stick amplitude and rate, and side task episodes. Full data for the simulation tracking statistics as well as the explicit equations and structure of the urgency function multiaxis pilot model are presented

Faulkner, W. H.

Onstott, E. D.

English

NASA Technical Reports Server

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https://ntrs.nasa.gov/search.jsp?R=19790009317 2020-03-20T18:06:50+00:00Z
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th
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is
e 
u
n
pl
ea
sa
nt
 t
ra
ns
ie
nt
 e
ff
ec
ts
. 
In
 &
Co
n 
to
 tb
e 
a
dv
an
- 
ta
ge
s o
f i
m
pr
ov
ed
 a
c
c
u
ra
c
y,
 t
im
e d
om
ai
n 
m
o
de
ls
 r
a
n
 in
co
rp
or
at
e 
In
fo
:-m
at
io
n 
th
at
 i
s 
fi
xe
d 
in
 ti
m
e.
 s
u
c
h 
a
s 
c
ri
te
ri
on
 g
w
er
ni
ng
 th
e 
ab
an
do
ni
ng
 o
f o
n
e
 ta
sk
 f
or
 an
o
th
er
. 
Th
is
 
ki
nd
 o
f p
llo
t b
eh
av
io
r 
is
 cr
u
c
ia
lly
 im
po
rt
an
t i
n 
m
u
lti
-t
as
k 
m
is
si
on
s 
an
d 
s
in
ce
 t
he
 d
ec
i-
 
si
on
 p
oi
nt
s 
a
re
 fu
nc
tio
ns
 o
f 
th
e 
sy
st
em
 s
ta
te
 v
a
ri
ab
le
s 
it 
r
m
t
 be
 m
d
1e
d
 by
 e
it
he
r 
fr
eq
ue
nc
y 
do
m
ai
n 
o
r
 s
ta
te
 s
pa
ce
 m
et
ho
ds
. 
T
he
re
 h
av
e 
be
en
 th
re
e 
m
a
in
 a
pp
ro
ac
he
s 
pr
ev
io
us
ly
 ta
ke
n 
in
 a
tt
em
pt
s t
o 
ex
te
nd
 
si
ng
le
 a
x
is
 m
o
de
l t
he
or
y 
to
 m
u
lti
-a
xi
s 
ta
sk
s.
 
AU
 o
f 
th
es
e 
re
c
o
gn
iz
e 
th
at
 th
e 
hu
m
an
 
m
u
st
 o
pe
ra
te
 a
s
 a
 t
im
e s
ha
re
d 
de
vi
ce
 w
he
n 
fa
ce
d 
6
 th
 d
iff
ic
ul
t c
o
n
ho
l t
as
ks
. 
T
hI
s 
in
te
rm
itt
an
t o
pe
la
tio
n 
de
gr
ad
es
 th
e 
pe
rf
or
m
an
ce
 of
 e
a
c
h 
ta
sk
 fr
om
 w
b
t t
he
 p
ilo
t 
w
o
u
ld
 a
c
hi
ev
e 
in
 c
o
n
tin
uo
us
 c
o
n
tr
ol
. 
A
s 
m
ig
ht
 b
e 
e
x
pe
ct
ed
, 
th
es
e 
th
re
e 
a
pp
ro
rh
es
 
a
re
 (
1)
 de
cr
ea
se
 th
e 
m
o
de
l g
ai
n 
fr
om
 th
e 
o
pt
im
um
 f
or
 co
n
tin
uo
us
 c
o
n
tr
ol
. 
(2
) i
nc
re
as
e 
th
e 
ti
m
e 
de
la
y 
to
 a
c
c
o
u
n
t f
or
 th
e 
pe
ri
od
s 
of
 i
na
tte
nt
io
n,
 a
n
d 
(3
) in
jec
t f
il
te
re
d 
n
o
is
e 
to
 
im
it
at
e 
th
e 
sp
ec
tr
al
 c
o
n
te
nt
 o
f t
he
 s
hi
ft
in
g 
pi
lo
t c
o
n
tr
ol
. 
Th
e 
pr
ob
le
m
 w
lth
 t
he
se
 th
re
e 
a
pp
ro
ac
he
t 
is
 th
ls
: 
T
he
 h
um
an
 p
ilo
t i
s 
qu
ite
 
di
sc
ri
m
in
at
in
g 
ab
ou
t 
w
he
n 
he
 w
lll
 a
ba
nd
on
 t
he
 c
o
n
tm
l o
f 
o
n
e
 t
as
k 
to
 t
ak
e 
w
e
r 
th
e 
c
o
n
tr
ol
 o
f 
a
n
o
th
er
. 
T
hi
s l
ea
ds
 to
 a
 s
a
m
pl
in
g 
c
ri
te
ri
on
 th
at
 i
s 
fu
nc
tio
na
lly
 d
ep
ad
en
t 
o
n
 t
he
 to
ta
l s
ys
te
m
 v
a
ri
ab
le
s.
 
In
 n
o
 w
ay
 c
an
 th
is
 b
e 
re
ga
rd
ed
 a
s 
a 
pu
re
ly
 r
h
m
.
 or
 
a 
re
gu
la
r 
sa
m
pl
in
g.
 
Th
us
 a
 m
u
lti
-a
xi
s 
pi
lo
t m
o
de
l 
m
u
st
 c
o
n
ta
in
 a
n
 a
lg
or
ith
m
 th
at
 
de
te
rm
in
es
 w
he
n 
c
o
n
tr
ol
 s
hi
ft
in
g 
ta
ke
s 
pl
ac
e,
 a
n
d 
th
e 
m
o
de
l m
u
st
 b
e 
c
o
m
pu
te
d 
In
 a
 
w
a
y 
th
at
 p
re
se
rv
es
 th
is
 in
fo
rm
at
io
n.
 
By
 u
si
ng
 th
e 
m
et
ho
d 
cf
 d
ig
ita
l s
im
ul
at
io
n,
 t
he
 e
x
a
c
t f
un
ct
io
na
l c
ri
te
ri
on
. 
by
 w
hl
cb
 
a
 p
ilo
t d
ec
id
es
 h
is
 c
o
n
tr
ol
. 
c
a
n
 b
e 
di
re
ct
ly
 co
m
pu
te
d 
w
ith
ou
t t
he
 g
m
ss
 d
is
to
rt
io
ns
 d
 
lin
ea
ri
za
tio
n.
 
Th
e 
de
ve
lo
pm
en
t o
f t
he
 fo
rm
 o
f t
he
se
 u
rg
en
cy
 c
ri
te
ri
a 
ha
s 
n
ow
 a
dv
an
ce
d 




It
 is
 u
se
fu
l 
to
 e
x
a
m
in
e 
a 
pl
ot
 o
f 
tr
ac
ki
ng
 e
r
m
r
 v
e
rs
u
s
 t
im
e 
as
 i
t w
o
u
ld
 b
e 
v
ie
w
ed
 
in
 t
he
 s
ig
ht
 b
) 
th
e 
pi
lo
t. 
Fi
gu
re
 9
 w
a
s
 o
bt
ai
ne
d 
fr
om
 th
e 
pi
lo
t 
m
o
dc
l. 
w
ith
 t
he
 p
ilo
t 
m
o
de
l c
o
n
tr
ol
 e
pi
so
de
s 
sh
ow
n 
bq
 
sy
m
bo
ls
 as
 
in
di
ca
te
d.
 
A
lth
ou
gh
 t
he
 d
at
a 
pr
es
en
te
d 
he
re
 h
as
 b
ee
n 
li
m
it
ed
 to
 c
a
s
e
s
 5
 a
rd
 6
 o
f 
R
ef
er
en
ce
 4
. 
th
e 
fo
llo
w
in
g 
fo
ur
 c
o
n
c
lu
si
on
s 
c
a
n
 b
e 
d
ra
m
 co
n
c
e
rn
in
g 
th
e 
a
bi
ii
ty
 of
 t
he
 u
r
ge
nc
y 
de
ci
si
on
 
pi
lo
t 
m
o
de
l t
o
 r
e
pr
es
en
t p
ilo
te
d 
ta
rg
et
 tr
ac
ki
ng
: 
1)
 
T
he
 m
o
de
l r
e
pr
od
uc
ed
 th
e 
v
e
rt
ic
al
 tr
ac
ki
ng
 e
r
r
o
r
s
 a
c
c
u
ra
te
ly
. 
2)
 
Ev
en
 th
ou
gh
 t
he
re
 w
a
s
 n
o
 h
or
iz
on
ta
l 
ta
rg
et
 m
o
tio
n,
 t
he
 a
tt
en
tio
n 
di
ve
rs
io
n 
In
 t
he
 p
llo
t a
n
d 
in
 th
e 
pi
lo
t 
m
o
de
l l
ed
 to
 s
im
il
ar
 h
or
iz
on
ta
l 
tr
ac
ki
ng
 e
r
n
r
s
. 
-
 VE
R
T!
CA
L 
CO
NT
RO
L 
.
-
.
.
 
H
O
RI
ZO
NT
AL
 C
O
NT
RO
L 
rx
x
x
 S
ID
E 
TA
SK
 
h 
10
m
 
3)
 
Tl
lB
 a
ss
u
m
pt
io
n 
th
at
 th
e 
e
le
ct
ro
de
 ta
pp
in
g 
s
id
e 
ta
sk
 u
s
e
d 
in
 th
e 
fl
ig
ht
 
si
m
ul
at
io
n 
c
o
u
ld
 b
e 
re
pr
es
en
te
d 
a
s
 a
 c
o
n
s
tv
lt
 u
rg
en
cy
 ta
sk
 w
a
s
 ju
sti
fie
d 
by
 a
) t
he
 v
e
rt
ic
al
 a
n
d 
ho
ri
zo
nt
al
 t
ra
ck
in
g 
e
rr
o
rs
. 
b)
 th
e 
o
c
c
u
ra
n
c
e
 o
f 
si
de
 
ta
sk
 e
pi
so
de
s 
o
n
ly
 f
or
 tr
ac
ki
ng
 e
r
r
o
r
s
 le
ss
 th
an
 4
 m
e
te
rs
. 
an
d 
c
) t
he
 
fr
eq
ue
nc
y 
o
f 
s
id
e 
ta
sk
 e
pi
so
de
s.
 
TO
TA
L 
TI
M
E 
=
 
60
 S
EC
O
ND
S 
i 
T
he
se
 r
e
s
u
lt
s 
jus
tif
y 
th
e 
la
st
 c
o
n
c
lu
si
on
: 
4
) 
T
he
 u
rg
en
cy
 d
ec
is
io
n 
pi
lo
t 
m
o
de
l 
c
a
n
 b
e 
u
se
d 
to
 p
re
di
ct
 tr
nc
ki
ng
 e
r
r
o
r
 
pe
rf
or
m
an
ce
 a
n
d 
pi
lo
t 
re
s
e
rv
e
 a
tt
en
tio
n 
c
a
pa
ci
ty
 f
or
 m
a
n
e
u
v
e
ri
ng
 b
rg
et
a 
by
 s
tr
ai
gh
rf
or
w
ar
d 
a
pp
lic
at
io
n 
of
 t
he
 It
xe
d 
fo
rm
 m
o
de
l a
dj
us
ted
 th
ro
ug
b 
o
pt
im
iz
at
io
n 
a
n
d 
si
de
 ta
sk
 u
rg
en
cy
 c
a
li
br
at
io
n 
in
vo
lv
in
g 
o
n
ly
 o
n
e
 d
at
a 
po
in
t. 
Fi
gu
re
 9
. 
T
im
e 
H
i-s
to
ry
 o
f 
Pi
lo
t 
R
lo
de
l C
on
tr
ol
 E
pi
so
de
s.
 
T
he
re
 a
re
 tw
o 
im
po
rt
an
t o
bs
er
va
ti
on
s 
th
at
 c
a
n
 b
e 
m
a
de
 c
o
n
c
e
r
~
in
g th
e 
s
id
e 
ta
sk
. 
By
 e
x
a
m
in
at
io
n 
o
f 
m
an
y 
ti
m
e 
hi
st
or
ie
s 
su
c
h 
a
s
 F
ig
ur
e 
9,
 i
t w
a
s 
c
le
ar
 h
i 
th
e 
s
id
e 
ta
sk
 
w
a
s
 p
er
fo
rm
ed
 b
y 
th
e 
m
o
de
l o
n
ly
 w
he
n 
th
e 
tr
ac
ki
ng
 e
r
r
o
r
 w
a
s 
le
ss
 th
an
 f
ou
r 
m
e
te
rs
. 
Si
nc
e 
th
e 
si
m
ul
at
io
n 
pi
lo
ts
 w
e
re
 r
e
po
rt
ed
 n
o
t t
o
 p
er
fo
rm
 s
id
e 
ta
sk
s 
u
n
le
ss
 th
e 
e
rr
o
r 
w
a
s
 
le
ss
 th
an
 o
n
e
 w
in
g 
sp
an
 o
f 
th
e 
ta
rg
e:
, 
th
is
 m
o
de
l 
s
~
d
e
 
ta
sk
 b
eh
av
io
r 
is
 c
o
n
si
st
en
t w
ith
 
th
e 
fl
ig
ht
 s
im
ul
at
io
n.
 
Th
e 
s
e
c
o
n
d 
po
in
t 
of
 c
o
m
pa
ri
so
n 
c
o
n
c
e
rn
s
 t
he
 fr
eq
ue
nc
y 
d
 s
id
e 
ta
sk
 e
pi
so
de
s.
 
St
ri
p 
c
ha
rt
 d
at
a 
fr
om
 th
e 
fl
ig
ht
 s
im
ul
at
io
n 
re
po
rt
ed
 i
n 
R
ef
er
en
ce
 4
 s
ho
w
 
th
at
 s
id
e 
ta
sk
 c
o
u
n
ts
 te
nd
 to
 o
c
c
u
r 
in
 y
ai
rs
. 
If 
th
e 
s
id
e 
ta
sk
 c
o
u
n
tin
g 
ra
te
 i
s 
ha
lv
ed
 o
n
 
th
e 
a
ss
u
m
pt
io
n 
th
at
 th
e 
pi
lo
t u
su
a
lly
 g
et
s 
th
e 
se
c
o
n
d 
c
w
n
t 
o
n
c
e
 h
e 
ha
s 
lo
ok
ed
 d
ow
n 
to
 
pe
rf
or
m
 th
e 
fi
rs
t. 
th
e 
c
o
u
n
tin
g 
ra
te
 i
s 
a
pp
ro
xi
m
at
el
y 
e
qu
al
 t
o
 t
he
 fr
eq
ue
nc
y 
o
f 
s
id
e 
ta
sk
 e
pi
so
de
s 
p
d
u
c
e
d
 by
 t
he
 u
rg
en
cy
 d
ec
is
io
n 
pi
lo
t m
o
de
l. 
It
 s
ho
ul
d 
be
 n
o
te
d 
th
at
 
th
e 
s
id
e 
ta
sk
 h
as
 s
ig
ni
fi
ca
nt
 in
fl
ue
nc
e 
o
n
 v
lr
ti
ca
l 
an
d 
ho
ri
zo
nt
al
 t
ra
ck
in
g 
e
r
r
o
r
s
; 
s
in
ce
 
th
es
e 
s
ta
ti
ts
ti
cs
 c
o
m
pa
re
d 
w
e
ll.
 t
he
 a
ss
u
m
pt
io
n 
o
f 
a 
c
o
n
st
an
t u
rg
en
cy
 m
o
de
l 
fo
r t
he
 
e
le
ct
ro
de
 ta
pp
in
g 
s
id
e 
ta
sk
 a
pp
ea
rs
 to
 b
e 
jus
tif
ied
. 
1.
 
Fa
ul
kn
er
, 
W.
 H
.. 
an
d 
O
na
to
tt,
 E
. 
D
.. 
=
r 
R
at
e 
In
fo
rm
at
io
n 
in
 A
tte
nt
io
n 
A
llo
ca
tio
n 
Pl
lo
t M
od
el
s,
 P
ro
ce
ed
in
gs
 o
f 
th
e 
T
hi
rt
ee
nt
h 
A
nn
ua
l 
C
on
fe
re
nc
e 
o
n
 M
an
ua
l 
C
on
tr
ol
. 
M
IT
. 
Ju
ne
 1
97
7.
 
2.
 
O
ns
to
tt
, 
E.
 D
. 
,
 T
as
k 
L
nt
er
fe
re
nc
e 
in
 M
ul
ti-
A
xi
s 
A
ir
cr
dt
 S
ta
bi
liz
at
io
n.
 
Pr
oc
ee
di
ng
s 
of
 t
he
 T
w
el
ft
h 
A
nn
ua
l 
C
on
fe
re
nc
e 
o
n
 M
an
ua
l 
C
on
tr
ol
. 
U
ni
ve
rs
ity
 
o
f 
Il
lin
oi
s,
 M
ay
 1
97
6.
 
3.
 
O
ns
to
tt,
 E
. 
D
., 
M
ul
ti-
A
xi
s 
W
ot
-V
eh
ic
le
 
D
yn
am
ic
s,
 P
ro
ce
ed
in
gs
 o
f 
th
e 
T
en
th
 
An
nu
al
 C
on
fe
re
nc
e 
o
n
 M
an
ua
l 
C
on
tr
ol
, 
A
lF
Tf
A
FF
D
L.
 
A
pr
il 
19
74
. 
4.
 
B
ue
ijo
. M
. 
J.
, 
a
n
d 
R
ile
y,
 D
. 
R.
. 
Fi
xe
d-
B
as
e 
Si
m
ul
at
or
 S
tu
dy
 o
f 
th
e 
E
ff
ec
t 
o
f 
T
im
e 
D
el
ay
s 
in
 V
is
ua
l 
C
ue
s 
o
n
 
Pi
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Prediction of pilot reserve attention capacity during air-to-air target tracking

Abstract

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