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concluding remarks of Bray (ref. 27) state, “For large
aircraft, due to size and to the basic nature of their
maneuvering dynamics, the cockpit lateral translational
acceleration cues appear to be much more important than
the roll acceleration cues. There was the indication that
this observation might be extended to the generalization
that, in each plane of motion, the linear cues are much
more valuable than the rotational cues.”
Reasons for these differences of opinion at a high level are
unclear and point to the need for additional research. But
before the appropriate directions for the additional research
can be determined, a careful review of past work is
warranted. Those analytical and experimental efforts that
have addressed motion requirements are discussed below.
Analytical Motion Research. Many decisions are
made during both the design and development of a
particular simulation. All of the components shown in
figure 1 must be selected, and their characteristics must be
specified. If an analytical model was available that
accounted for the fidelity effects of these components, then
one could inexpensively make performance trade-offs to
optimize both the cost and utility of a simulator system.
So, a good analytical model would have great use.
Although the dynamics of the non-piloted components of
figure 1 are straightforward, the difficulty facing the
modeler is the pilot block. Pilots are often adaptive,
nonlinear, and inconsistent, and modeling their input/
output characteristics is a challenge. A possible breakdown
of the key processes carried out by a pilot is shown
in figure 2. These key processes are sensation, perception,
and compensation. The general characteristics of these
processes are discussed next, because knowledge of them
is relevant to the experimental designs presented in later
sections.
Task
demands
Simulator
stick
force
Simulator
visual, motion,
and stick cues
Remnant
Pilot
Compensation
Perception
Sensation
Figure 2. Top-level pilot model.
The sensation block in figure 2 is often used as the
starting point when motion requirements are hypothesized,
and a large database exists on human motion-sensing
characteristics (refs. 28–36). The details of the human
motion sensing systems are given in appendix A, but four
key points are made here. First, the bandwidth of the total
human motion sensory system encompasses the typical
pilot-vehicle range of frequencies (0.1–10 rad/sec). Second,
for the experiments that are subsequently described, the
thresholds of human motion sensors were exceeded;
however, the literature acknowledges that motion-sensing
thresholds differ among individuals and that they depend
on whether the subject is active or passive during the
7
motion stimulus (ref. 36). Third, previous incorporation
of the motion dynamics and thresholds into models of a
pilot-vehicle system has not resulted in an improved
ability to model pilot-vehicle behavior (ref. 35). Finally,
previous efforts to generate an integrated motion cueing
model have concluded that additional experiments need to
be conducted before that goal can be accomplished
(ref. 31).
Once the cues are sensed, the perception block of figure 2
comes next. At this point, an integrated perceptual process
likely occurs, but how it is accomplished is not known
exactly. One has to know how all of the external cues
(visual, kinesthetic, and tactile) are summed to develop the
pilot’s perception of motion. Unfortunately, little is
known about how these cues affect motion perception, and
further careful experiments are required to explore the
perceptual interactions that occur among these cues.
After the pilot has developed an estimate of the vehicle
state from the output of the perception block, compensation
is then applied to this state vector. Fundamentally, it
is known that the pilot applies compensation necessary to
have “integrator-like” or “K/s-like” characteristics in the
crossover region of the pilot-vehicle open-loop combination
(ref. 37). To do this, a pilot will typically provide up
to 1 sec of lead before his estimate of a task workload is
degraded.
Application of the above concepts is presented in
appendix B, which gives details of a structural pilot
model for the vertical axis experiment described in
section 4. It is shown that the model captures the general
closed-loop performance trends. However, it underpredicts
the magnitude of these trends to the point that it suggests
　
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