Technical Report 1176 

Do Army Helicopter Training Simulators Need 

Motion Bases? 

Michael E. McCauley 

Naval Postgraduate School 

February 2006 

 United States Army Research Institute 

for the Behavioral and Social Sciences 

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Do Army Helicopter Training Simulators Need Motion Bases? 5b. PROGRAM ELEMENT NUMBER 

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14. ABSTRACT (Maximum 200 words): 

This report reviews the arguments and the evidence regarding the need for simulator motion bases in training 

helicopter pilots. It discusses flight simulators, perceptual fidelity, history of motion bases, disturbance versus 

maneuver motion, human motion sensation, and reviews the empirical evidence for the training effectiveness of 

motion bases. The section on training effectiveness reviews research from relevant sources, including: Military 

helicopter, military transport, commercial airlines, general aviation, fighter, and attack aircraft. In addition the author 

describes a Perceptual Control Theory approach to determining the information requirements for simulator-based 

training. The author concludes that there is a substantial body of data to support the training effectiveness of flight 

simulation in general; that there is virtually no evidence to support the training effectiveness of motion platforms; that 

motion contributes to in-simulator performance, particularly for experienced pilots; that motion cues may be beneficial 

for flight training in unstable aircraft and in tasks involving disturbance cues, although the evidence is weak; and that 

motion, noise, and vibration contribute to the realism of the simulation and, therefore, strongly influence the 

acceptance of a simulator by the pilot community. There is no reliable evidence that a motion base prevents 

simulator sickness. Instructional design is more important than physical fidelity for training effectiveness. 

15. SUBJECT TERMS 

 Flight Simulation Flight Simulators Flight Training Helicopter Simulators Simulator Motion 

 Perceptual Control Theory Transfer of Training 

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iii 

Technical Report 1176 

Do Army Helicopter Training Simulators Need 

Motion Bases? 

Michael E. McCauley 

Naval Postgraduate School 

Rotary-Wing Aviation Research Unit 

William R. Howse, Chief 

U.S. Army Research Institute for the Behavioral and Social Sciences

2511 Jefferson Davis Highway, Arlington, Virginia 22202-3926 

February 2006 

 

Army Project Number Personnel Performance and 

622785A790 Training Technology 

Approved for public release; distribution is unlimited.
ACKNOWLEDGMENTS_______________________________________________

Thank you to Dennis C. Wightman, Ph.D. for initiating this project at USARIRWARU. Major Jason M. Jones, U.S. Army, a student at the Naval Postgraduate 

School, participated in the initial stages of the literature search. I appreciate the input 

from Dr. Richard S. Marken of Rand Corporation on Perceptual Control Theory. Thank 

you to William R. Howse, Ph.D. and John E. Stewart, Ph.D. for their valuable comments 

and suggestions on an earlier draft. I gratefully acknowledge the feedback, guidance, 

and detailed error-nulling provided by David M. Johnson, Ph.D. 

iv 
DO ARMY HELICOPTER TRAINING SIMULATORS NEED MOTION BASES?

EXECUTIVE SUMMARY________________________________________________

Research Requirement: 

The issue of whether or not simulators for flight training need motion bases is a 

perennial one. It has recently re-emerged for the Rotary-Wing Aviation Research Unit 

(RWARU) of the U.S. Army Research Institute for the Behavioral and Social Sciences 

(ARI) at Fort Rucker, AL. Fort Rucker is the home of the U.S. Army Aviation 

Warfighting Center (USAAWC). USAAWC has embarked on its Flight School XXI 

training program. Among other innovations, the Flight School XXI program will enhance 

basic and advanced aviator training with additional simulator-based flight instruction. 

Hence, inquiries concerning the need of motion for simulator-based helicopter flight 

training have found their way to RWARU. 

In addition, the issue of simulator motion has arrived anew with regard to the 

simulator-based training requirements for Future Combat Systems. Inquiries regarding 

this application also have found their way to RWARU. Thus, it was deemed appropriate 

by ARI to perform an up-to-date literature review on the subject. 

Procedure: 

An extensive literature review was commissioned by ARI. This review was to 

focus primarily on the specific need for motion in the simulator-based training of Army 

helicopter pilots. The central imperative, therefore, was to examine evidence from 

transfer of training experiments where motion was an independent variable. However, 

other related topics were reviewed as well, including: In-simulator learning; pilot 

preferences; force-cueing systems; simulator sickness; and Perceptual Control Theory. 

Findings: 

There is a substantial body of scientific data to support the training effectiveness 

of flight simulation. Flight simulators are unquestionably valuable for safely 

accomplishing training. However, there is virtually no scientific evidence to support the 

effectiveness of motion platforms for training. Motion does improve performance while 

in the simulator, particularly for experienced pilots. Motion cues may be beneficial 

under certain conditions, such as tasks involving disturbance motion, although the 

evidence for this is weak. Motion, noise, and vibration contribute to the realism, and 

therefore the pilot acceptance, of a simulator. Finally, there is no reliable evidence that 

a motion base prevents simulator sickness. 

v 
Utilization and Dissemination of Findings: 

ARI’s initial approach and early results were briefed to the Director, Directorate of 

Training Doctrine and Simulation, USAAWC, as well as to the Commander, Aviation 

Training Brigade, USAAWC. This final report represents RWARU’s current 

understanding of this complicated issue, and will be made widely available to the 

simulation and training community at USAAWC. 

vi 
DO ARMY HELICOPTER TRAINING SIMULATORS NEED MOTION BASES?

CONTENTS_________________________________________________________

 Page

vii 
DO ARMY HELICOPTER TRAINING SIMULATORS NEED MOTION BASES?

Introduction 

Overview 

The goal of this paper is to identify and summarize the arguments and 

evidence regarding the need for simulator motion bases in training U.S. Army 

helicopter pilots. For nearly 100 years, flight simulators have been used for pilot 

training. The motion base debate is nearly of equal length. 

A brief background and history of the use of simulator motion bases in aviation 

training will be provided. The empirical evidence for the training effectiveness of 

motion bases will be reviewed, and other motion cueing devices will be mentioned. 

Research issues will be identified regarding the use of motion in helicopter pilot 

training. A recommendation is made for a new perspective on this issue based on 

Perceptual Control Theory. 

Although Army helicopter training is the application of concern, evidence 

regarding motion cues will be reviewed more broadly, across fixed-wing as well as 

helicopter and in both commercial and military aviation. This approach is intended to 

provide a broad background and context for interpreting evidence about the need for 

motion bases in Army helicopter pilot training. 

Framework and Perspective 

The value of simulator features depends on one’s perspective and the purpose of 

the simulator. Schroeder (1999) defined flight simulators as an attempt to reproduce 

the pilot-vehicle behavior of actual flight on the ground reasonably and safely. 

Simulators are used for several purposes, the two major ones being training and 

research. “Do you need a motion base?” sounds like a yes or no question, but the 

issue is more complex. A better characterization of the question might be-- How do 

flight simulator motion requirements vary as a function of: 

• Simulator purpose 

• Aircraft type 

• Pilot experience level 

• Training objectives, maneuvers, and tasks 

• Criteria (training transfer, in-simulator performance, or pilot acceptance) 

• Budget for simulator acquisition and operations? 

Training is the product of training simulators. Hence, a training effectiveness 

perspective is the logical choice for evaluating the features of a training simulator. 

Simulator features that provide positive transfer of training (ToT) to the aircraft have 

value in terms of achieving training objectives (effectiveness) and reducing the 

1 
resources required to achieve criterion performance (efficiency). If the acquisition 

cost of these features is within reason (cost-benefit), then there is a strong case for 

including them in simulator training system acquisition. 

Reliable and valid data are the product of research and development (R&D) 

simulators. The perspective of handling qualities R&D is to achieve the most precise 

and accurate representation of pilot-vehicle behavior in the simulator. Experienced 

test pilots are the appropriate test subjects for simulator research on handling 

qualities. Simulator motion bases enable better in-simulator performance by 

experienced pilots. Thus, a clear case can be made for procuring motion bases for 

simulators that will be used to do handling qualities research. But the technology 

features that enable better performance in the simulator do not necessarily contribute 

to training effectiveness. There are other types of R&D that do not require precision 

in the simulator, such as research on cockpit instrument design layout, manning and 

automation, training research, and crew coordination (cockpit resource 

management). It is not clear that a motion base is necessary for these research 

simulators. 

User acceptance (pilot preference) is a third perspective on the value of simulator 

features. How much value should be placed on simulator features that are preferred 

by pilots but generate no measurable training effectiveness? This is a value 

judgment that is not amenable to empirical research but may be important to an 

acquisition program manager or a military commander responsible for training and 

readiness. If simulator operators/instructors and trainees are “the customers” of 

training simulators, shouldn’t some consideration be given to providing a product that 

has features desired and valued by the customer? 

The Federal Aviation Administration (FAA) has an alternative perspective on the 

criteria for choosing motion bases (Burki-Cohen, Soja, & Longridge, 1998). The FAA 

requires a 6 degree of freedom (DoF) motion platform for certification as a top-level 

(Level D) flight simulator. Without a motion platform, the FAA calls it a “training 

device” rather than a training simulator. The FAA takes the position that public safety 

requires nothing less than full physical fidelity: 

... the use of flight simulators in air-carrier training and checking 

activities goes beyond the standard transfer-of-training 

paradigm. When used as a substitute for the aircraft, the 

evaluation of pilot performance in the device constitutes a 

determination of the readiness of the pilot to perform immediately 

in line operations involving the flying public. That is, unlike many 

classical transfer-of-training situations, the simulator–trained aircarrier pilot is expected to perform within satisfactory standards 

of proficiency in the aircraft from day one. Consequently, the 

simulator must be capable of supporting 100 percent transfer of 

performance to the aircraft. Anything less would compromise 

safety. The existing standards for full flight simulator 

2 
qualification, all of which entail a requirement for platform-motion 

cueing, have a twenty year record of meeting the requisite 

criterion for transfer of performance. In the absence of 

compelling evidence to the contrary, it is therefore prudent to 

maintain these standards in the interest of public safety. 

Regulatory authorities will therefore continue to require platform 

motion...(Burki-Cohen, et al., 1998, p. 296). 

Rather than basing acquisition decisions on empirical data supporting positive 

transfer, the FAA assumes that a Level D motion platform is necessary until proven 

otherwise. This position is not amenable to empirical confirmation because it 

amounts to proving the null hypothesis. There are at least two possible downsides of 

the FAA position: (1) physical displacement limitations of motion systems mean that 

less than full fidelity will be provided for any unusual accelerations associated with 

equipment failures and emergency procedures, thus introducing the prospect of 

negative transfer of training to the aircraft; (2) the cost of Level D simulators is 

beyond the budget of small regional carriers, contributing to the difficult economic 

basis of the industry. 

Flight Simulators 

Purposes of Flight Simulation 

Flight simulators have been used for over half a century to provide trainees 

with some aspects of the flight experience to aid in the acquisition of flying skills 

without leaving the ground. Huff and Nagel (1975) claim that the simulation of piloted 

flight is almost as old as the history of flight itself. In addition to their use in training, 

flight simulators also have been used for research on topics such as pilot-vehicle 

interface design, subsystems design and development, and handling qualities

evaluation. A classic report by the National Academy of Sciences identified four 

fundamental purposes of simulation: (1) training; (2) systems and equipment design, 

development, test, and evaluation; (3) research on human performance; and (4) 

licensing and certification (Jones, Hennessy, & Deutsch, 1985). 

Flight simulators, with and without motion bases (also called “motion 

platforms”), have been used in a wide range of aircraft types and applications 

including military fixed-wing, military helicopter, general aviation, and commercial 

aviation (Jones, et al., 1985; Kaiser & Schroeder, 2003; Moroney & Moroney, 1999; 

Rolfe & Staples, 1986; Roscoe, 1980). 

Flight simulators create the illusion of flight by simulating equipment, tasks, 

and environments. Training simulators provide these capabilities for the purpose of 

accomplishing pilot or aircrew training without using the actual aircraft. The potential 

benefits of training simulators are cost savings, time savings, risk reduction, and 

efficiency (student throughput). 

3 
Often, operational and technical personnel express the opinion that realism is 

the most important characteristic of a simulator, but in many ways, it is departures 

from realism that make simulators worthwhile. Here are some unrealistic examples: 

We fly but don’t burn fuel; we crash but are uninjured and don’t bend metal; we can 

practice a flight segment or set of tasks repeatedly without flying into position; we can 

make it day or night, light or dark, good or poor visibility; we can replay an event to 

provide training feedback; we can pause in mid flight; we can invoke equipment 

failures or other emergency procedures without risk; we can fly in the desert, over 

water, over high mountains, in urban areas, and in geo-specific areas all on the same 

day; we can practice nearly 60 ship landings per hour. All of those valuable features 

and capabilities are departures from realism. 

The training value of a simulator is, in large part, derived from the instructional 

design and content rather than from the simulation hardware and software that 

emulate the functionality of the aircraft. As Caro (1973) pointed out over 30 years 

ago, the training value of a simulator depends more on a proper training program 

than on its realism. This is a lesson that is still being learned. 

In an analysis of simulation by the National Academy of Sciences, the number 

one conclusion was, “Physical correspondence of simulation is overemphasized for 

many purposes, especially training” (Jones, et al., 1985, p. 92). And further, “... the 

concern with fidelity should shift from what is technically feasible in a hardware sense 

toward achieving greater effectiveness and efficiency in terms of behavioral 

objectives.” 

Objective and Perceptual Fidelity

Objective fidelity in a simulator refers to the physical correspondence between 

the flight simulator and the aircraft. Presumably, engineering techniques can be 

applied to measure both the aircraft and the simulator, yielding an index of objective 

fidelity. 

Perceptual fidelity refers to the relationship between a pilot’s subjective 

perceptions of the simulator and the aircraft. It also refers to the comparative sets of 

pilot performance and control strategies in the simulator and the aircraft. The term 

“presence” from the realm of virtual environments (VE) is similar to the concept of 

perceptual fidelity in flight simulators. According to Sadowski and Stanney (2002), 

presence does not necessarily equate to better performance in the VE. Likewise, the 

relationship between perceptual fidelity and performance in the flight simulator has 

not been established. 

The “fidelity wars” have been ongoing in flight simulation for decades. 

However, there is little evidence to support the common belief that more fidelity 

equates to better training. A cogent summary on this issue was given 20 years ago 

in the National Academy of Sciences report on simulation: 

4 
The purpose of a simulator is to provide the conditions, 

characteristics, and events present in the operational situation 

necessary for the learning of skills that will be performed with 

actual equipment... Two related principles derive from this 

premise. First, the characteristics and methods of using 

simulators should be based on their behavioral objectives. 

Second, physical realism is not necessarily the only or optimal 

means for achieving the behavioral objectives of simulation. 

Because the history of simulator development is characterized 

by striving for improved realism through the advancement of 

technology, it is easy to forget that the learning or performance—

not physical duplication—is the primary goal. (Jones, et al., 

1985, p. 28) 

Brief History of Simulator Motion Platforms 

Motion systems in support of training have been used since 1918 to provide 

from one to six DoF using various drive mechanisms including pneumatic bellows, 

cables, cascaded gimbals, large amplitude beams, centrifuges, hydraulic pistons, and 

electrical motors (Puig, Harris, & Ricard, 1978). Edwin Link developed the Link

trainer during 1927 – 1929, adapting the pneumatic bellows concept from his father’s 

pipe organ factory to generate pitch, roll, and yaw movements of the crew station. In 

1934 the Army Air Corps began purchasing Link trainers (the “Blue Box”) and in 1937 

a Link trainer was delivered to American Airlines. During World War II, as many as 

10,000 Link trainers were in use (Moroney & Moroney, 1999). 

External scene visual display systems were based on model boards in the 

1950s and computer image generation (CIG) systems were developed in the 1960s. 

Since the 1970s, the rapid expansion of computational power has enabled enormous 

advances in image systems, complex aircraft models, and motion control systems. 

From approximately 1970 to 2000 the synergistic hexapod hydraulic system, 

based on the “Stewart” platform design, was the most common form of 6 DoF motion 

platform (three angular—pitch, roll, and yaw; three linear—longitudinal, lateral, and 

vertical or heave axis). AGARD (1979; 1980) recommended that the following five 

characteristics be used to describe the dynamic capabilities of simulator motion 

platforms: 

1. Excursion limits 

2. Describing function 

3. Linearity and acceleration noise 

4. Hysteresis 

5. Dynamic threshold 

5 
Figure 1. Examples of hexapod motion platforms (courtesy of Frasca International, 

Inc.). 

Despite the increases in computational capability, motion platforms are not 

capable of achieving the sustained accelerations found in flight. To constrain a flight 

simulator to a building, motion cues must be of limited duration and amplitude. Thus, 

motion cueing systems provide brief onset cues followed by washout. Even the 

relatively large motion platforms used in Level D commercial aviation simulators have 

a limited range of linear displacement, on the order of 1-2 meters. For all but the 

most gentle, subtle, and short-lived maneuvers in flight (such as normal operations in 

a large commercial airliner), these constrained motion cues presented in the 

simulator depart, sometimes substantially, from the actual motion of the aircraft. 

One new type of simulator, the centrifuge design, shown in Figure 2, can 

sustain a high level of acceleration. The primary axis can be varied according to the 

gimbal orientation. However, there is a possibility of negative transfer for scanning 

behavior with the centrifuge design because the trainee must maintain a fixed head 

position to avoid disorientation from vestibular Coriolis (Holly, 2004). It could be 

problematic for fighter pilots to learn to keep their head still. 

Figure 2. Wyle Dynamic Flight Simulator with dual gimbal gondola (courtesy of Wyle 

Laboratories, Inc.). 

Motion bases come closest to matching normal operations in large commercial 

airplanes. They are least capable of matching high-level, sustained accelerations 

that characterize fighter and attack aircraft. Helicopter operations fall somewhere 

6 
between those two extremes. Some individuals claim that motion cues are helpful for 

pilot training in unstable aircraft, such as helicopters (Kruk, 2004; Magee, 2004). 

This hypothesis has been confirmed for in-simulator performance, but has not been 

subjected to empirical test using the transfer of training paradigm. 

The temporal characteristics of motion bases are important. Transport delay 

and cue asynchrony have been major issues in flight simulator design (Puig, et al., 

1978). Due to the advances in computing power, those issues, while still important, 

have diminished. It is generally believed that transport delays and asynchronies 

must be limited to less than 150 or 200 ms. Due to computational power, current 

simulators are capable of less than 100 ms delay, which is thought to be below the 

threshold for the human user (Tsang & Vidulich, 2003). 

The current trend in simulator motion systems is away from hydraulic toward 

electro-mechanical actuation. The payload of electrical systems must reach 18,000 

kg to qualify for FAA Level D certification. However, some sources claim that electromechanical systems have challenges in the area of load capacity and velocity. At 

present, hydraulic systems appear to be the answer for those seeking payload of 

more than 18,000 kg or velocity greater than 1 m/s. 

Disturbance versus Maneuvering Motion Cues

Gundry (1976) appears to have been the first to make a distinction between 

maneuver motion and disturbance motion. Maneuver motion arises within the pilotvehicle control loop and results from pilot-initiated changes in the motion of the 

aircraft via the aircraft controls. Disturbance motion arises outside the control loop 

and results from turbulence, mechanical failure, or similar perturbations input to the 

aircraft that are unexpected by the pilot. 

Gundry (1977) believed that simulator motion bases enabled pilots to respond 

more quickly and accurately to disturbance motion, thus leading to better 

performance in the simulator. Maneuver motion, on the other hand, does not provide 

an alerting function because it is pilot-initiated. Therefore, it may not contribute to 

improved performance in the simulator. Gundry did suggest, however, that for 

unstable aircraft, maneuver motion might contribute to pilots’ flight control. 

According to Caro (1979) all prior investigations of the ToT of simulator motion 

were performed with maneuver motion, ignoring the potential training value of 

disturbance motion. He suggested that disturbance motions might play an important 

role in alerting a pilot to the onset of turbulence or the failure of an aircraft 

component. Caro further distinguished between correlated and uncorrelated 

disturbance motion. Correlated disturbance motion is a consequence of events that 

are of immediate interest to the pilot and require his or her prompt attention, such as 

an asymmetrical external stores jettison. Uncorrelated disturbance motion does not 

alert the pilot to a disturbing event, but may be either regular, such as engine 

vibration, or irregular, such as turbulence. Caro suggested that motion may not be 

7 
needed for stable aircraft or for maneuver motion, but that motion may contribute to 

training for unstable aircraft (or during unstable flight modes, such as approaching 

stall) or when disturbance motion cues are correlated with specific events related to 

training objectives. This suggestion implies that it is an instructional design decision, 

rather than an engineering decision, as to which specific disturbance cues should be 

included in the simulation. In short, Caro argued for a logical relationship between 

simulator motion and training requirements and, ultimately, for empirical test of the 

training effectiveness achieved by those logical analyses. 

Research by Hosman and van der Vaart (1981) investigated the effect of 

visual and motion information on pilot performance in two types of roll control, a 

disturbance task and a compensatory tracking task. Three qualified jet transport 

pilots were tested in a simulator with a 3 DoF motion system (pitch, roll, and heave) 

and a visual system with both a central and peripheral display. The central display 

simulated an artificial horizon and the peripheral display was a checkerboard pattern 

provided by monitors fixed to the side windows of the flight simulator cabin. A quasirandom signal was input to the roll attitude of the simulated aircraft. In the 

disturbance condition, the roll input signal affected all pilot inputs, the two display 

systems and the motion system. In the tracking task, the roll input signal affected 

only the central display, providing a roll angle error. Both the peripheral displays and 

motion improved pilot control performance in both types of tracking tasks. The 

combination of peripheral and motion cueing led to the best performance. These 

results support the conclusion that simulator motion contributes to improved pilot 

performance in the simulator. Motion helps pilots counteract disturbance maneuvers 

in terms of increasing pilot gain, whereas the benefit with respect to tracking 

maneuvers is an increase in stability (reduced phase lag). These results do not, 

however, provide evidence of training transfer from the simulator to the aircraft. 

How Do Humans Sense Motion?

Human orientation, head stabilization, postural control, and locomotion require 

information about the gravity vector plus body and head motion (Previc, 2004). 

Spatial orientation is a fundamental and primitive need for humans and we have 

evolved multiple, overlapping sensory mechanisms to accomplish the job, namely the 

visual, vestibular, and proprioceptive senses (Young, 2003). The ambient visual 

system, which is particularly strong in the peripheral retina, is the primary source of 

information for orientation and motion perception. Wide field of view visual systems 

that provide a coherent optical flow create a strong sense of “vection,” the illusion of 

self-motion. According to Previc, the three major perceptual influences of ambient 

vision are on our sense of self-motion (vection), our perceived self-position in Earthfixed space, and our perception of the slant and distance of the terrain around us. 

Visual information, unlike the vestibular system, does not habituate (decay over time) 

during constant-velocity motion. According to Previc, our perception of orientation 

and motion begins to break down without visual input. This is exemplified by circling 

behavior while walking blindfolded, velocity underestimations when pursuing a slowly 

moving target, and orientation misjudgments when we are tilted relative to gravity. 

8 
Simulator visual systems induce vection. In wide field of view visual systems, 

the illusion can be quite profound. Vection also is experienced in wide field of view 

entertainment media like an IMAX theatre or head-mounted VE display devices. 

When sitting in the IMAX theatre or in a fixed-base simulator, the input to the brain 

from the vestibular system is a loud and clear “static, no motion” signal. This creates 

a sensory conflict situation, i.e., the sensory input from the two information sources is 

no longer concordant and complementary. The solution, however, is not so simple 

as to provide motion cues via a motion base because motion bases are inherently 

limited in displacement and, in most flight maneuvers, are able to provide only onset 

cues, thus creating residual conflict with the visual input. 

The vestibular system is an important source of information about body 

orientation and movement in the normal, on-ground environment. The semicircular 

canals and the otoliths constantly provide information about an individual’s 

orientation relative to gravity and acceleration and velocity of the head in 6 DoF. The 

semicircular canals are quite sensitive, with a sensory threshold on the order of 0.1 

degree/sec2 (Young, 2003). Likewise, the otoliths can detect small changes in the 

gravity vector or sustained linear acceleration on the order of 5-10 cm/sec2

, or a head 

tilt of approximately 2 degrees. The vestibular system has been modeled thoroughly 

(Borah, Young, & Curry, 1979), although there are large individual differences and 

vestibular function is influenced by multisensory input, workload, attention, and other 

factors. According to Cheung (2004), within a frequency range of 0.1 to 5.0 Hz, 

which corresponds to natural movements such as walking, running, and jumping, the 

activity of the input signals from the semicircular canals approximates head velocity. 

The accuracy and reliability of the orientation sensory systems are significantly 

altered when exposed to unusual gravitointertial environments such as flight. 

Vestibular and proprioceptive information can no longer be relied upon. 

Consequently, all responsibility for acquiring reliable information depends on vision 

(Cheung, 2004). 

Vestibular Perception and Motion Bases 

Various researchers have sought to design simulator motion systems based 

on vestibular models (e.g., Bussolari, Young, & Lee, 1988). Engineering analyses 

have been ongoing for many years regarding human manual control and 

improvements to motion cueing algorithms, e.g., Baron (1988); Guo, Cardullo, 

Telban, Houch, and Kelly (2003); Hess (1990); Schroeder (1999). 

According to Rolfe and Staples (1986), the maneuver cues in commercial 

aircraft are of relatively low frequency and can be provided visually. However, in 

marginally stable aircraft, the pilot must pay prompt attention to motion cues and the 

lead provided by the motion platform contributes to the pilot’s ability to maintain 

control (Kaiser & Schroeder, 2003). 

9 
There is no question that the vestibular system is involved in sensing motion 

during flight. One important lesson that all aviators must learn, however, is to ignore 

or suppress vestibular sensory input and to “trust your instruments.” This invites the 

question—do we need to simulate motion to learn to ignore the motion? 

 

Motion platform washout algorithms attenuate the motion onset cues to keep 

the platform within displacement limits. In so doing, they generate accelerations 

opposite in sign to what would be occurring in a sustained maneuver in the aircraft. It 

is typically assumed that the washout motion is below the vestibular threshold of the 

pilot, but this assumption is not tested and is likely to be false for any vigorous 

maneuver. Although there have been several attempts to define flight simulator 

motion system design based on vestibular models, there is no clear path from 

vestibular stimulation to the training effectiveness of motion. 

It is no wonder that pilot trainees learning to fly on instruments are told by flight

instructors to “trust your instruments” (rather than your vestibular system). All military 

pilots have been exposed to unusual attitude training and exposure to information 

about disorientation and the “leans.” In flight, it is not possible for a pilot to use 

vestibular information to know accurately his/her attitude or dynamic state. 

Ecological Approach 

Brown, Cardullo, McMillan, Riccio, and Sinacori (1991) collaborated in an 

attempt to define a new approach to motion cueing in flight simulation. This work 

resulted in a new framework for analyzing and characterizing motion information in 

flight and a “need-based” analysis of cues available to the pilot for aircraft control. 

Control systems theory was a foundation for their approach, combined with analysis 

of human perception of motion via various sensory systems, plus a determination of 

what motion cues are necessary for specific flight maneuvers. This work was a 

major contribution and an advancement of the distinction between maneuver cues 

and disturbance cues made earlier by Gundry (1976). 

Empirical Evidence for the Training Effectiveness of Motion Bases

In this section, empirical evidence for training transfer will be reviewed by 

aircraft type. First, an introduction to the transfer paradigm is provided. 

Transfer of Training Research is Difficult, Expensive, Dangerous, and Rare 

ToT experiments in aviation are difficult, expensive, and sometimes 

dangerous. It is not surprising that they are rare. The typical procedure in a ToT 

analysis is to expose one or more groups to training in a simulator and subsequently 

measure performance in the aircraft. There are many variations on this theme, but 

the main one is to establish a basis for comparison by including a control group that 

does not receive simulator training at all. In an investigation of the effect of motion, 

experimental subjects (pilots or pilot trainees) are randomly assigned to one of two 

10 
(or more) groups—one group gets motion and the other does not (fixed-base

condition). If, for example, after training in the assigned simulator condition, the 

motion group performs significantly better in the aircraft than the no-motion group, 

then the results support the claim of positive transfer of training of simulator motion. 

Roscoe (1980) described the basic principles of measuring training transfer and 

calculation of the Incremental Training Effectiveness Function (ITEF). 

One difficulty commonly faced by the ToT researcher in military aviation is that 

a training transfer analysis will disturb the flow of students through the training 

pipeline. Obtaining approval from the training commander can be difficult when some 

trainees will be assigned to a control group that gets no training. 

Measuring trainee performance typically is easier in the simulator than in the 

aircraft. The more expensive and complex the aircraft, the less likely that approval 

will be obtained to do transfer tests in the aircraft, particularly if they involve 

dangerous tasks such as recovery from unusual attitudes or nap of the earth (NOE) 

flight. There is an increased risk of losing the aircraft, the trainee, and the instructor 

in these circumstances. Finally, ToT studies can be costly if a large sample of 

trainees must be tested in the aircraft. This is particularly true for expensive, complex 

aircraft with high operational costs. Preliminary analysis of statistical power is 

important for ToT research so that an appropriate sample size can be determined 

(e.g., Boldovici, 1992) 

For these reasons, ToT experiments are very rare and “pseudo-transfer” 

(sometimes called “quasi-transfer”) studies are more common. Pseudo-transfer 

means that students are trained in the simulator under various conditions, such as 

with and without motion, and then tested in the simulator with motion. This technique 

avoids the cost and the danger associated with testing in the aircraft. For example, 

the operational cost of flying a 747-400 in a transfer experiment would be prohibitive. 

Analysis of the transfer of emergency procedures in the 747-400 could be 

dangerous. Most ToT studies have been done in general aviation aircraft or military 

training aircraft. 

General principles are difficult to derive from transfer studies because they 

must choose specific values of variables such as instructional technique, trainee 

experience (e.g., initial, transition, or refresher training), aircraft type, aircraft mission, 

maneuvers, tasks, simulator features, simulator calibration, instructors, and the 

reliability and validity of the performance measures. 

Semple et al. (1980) reviewed transfer studies that used subjective (instructor 

ratings) and objective (e.g., bombing accuracy) performance measures and found 

that the subjective measures failed to detect training transfer whereas the objective 

measures of performance on the same tasks demonstrated positive transfer. 

Bricston and Burger (1976) used both objective and subjective measures and found 

positive transfer for both types of measures, but the objective measures resulted in 

substantially higher positive transfer. 

11 
Reliability of the performance measures, whether objective or subjective, is 

essential (Bittner, Carter, Kennedy, Harbeson, & Krause, 1986). Similarly, analysis 

of statistical power is strongly recommended, but often overlooked, before 

undertaking studies of ToT. Adopting unreliable performance measures in a ToT 

analysis (thereby reducing the power of the statistical tests) is likely to waste 

resources and provide little hope of detecting positive transfer, even when it exists. 

ToT studies have an often-overlooked temporal aspect related to learning 

curves and retention. A positive transfer effect can be transitory. It depends, in part, 

on the time and intervening experience between the training and the measurement of 

transfer performance. Consider, for example, a paradigm where we might test for the 

persistence of a transfer effect, by administering a daily test battery in the aircraft. It 

would be possible to detect a small, but statistically significant, transfer effect by 

using highly reliable performance measures, but the transfer effect could be washed 

out by the second day. Ultimately, decisions about simulator features and their value 

for training effectiveness must be considered in the context of cost-benefit as well as 

training transfer. Cost-benefit issues will not, however, be addressed in this paper. 

Military Helicopter 

Bray (1994), an expert in motion system engineering, suggested that simulator 

motion may be more beneficial in helicopter simulation than in transport aircraft 

simulation because control sensitivities are higher and stability is lower. However, 

studies of ToT in helicopters are extraordinarily rare. 

McDaniel, Scott, and Browning (1983) evaluated the contribution of platform 

motion to training effectiveness in a Navy SH-3 helicopter simulator (Device 2F64C). 

Because previous ToT research studies had sometimes been criticized for using 

simulator motion platforms with excessive lags and less than design accelerations, 

McDaniel et al. instrumented the motion system platform and subjected it to regular 

testing by simulation system engineers during the ToT experiment. 

Two primary measures were used as criteria for transfer: (1) the number of 

flight hours in the SH-3 Sea King aircraft required by each student to pass 

designated flight checks; (2) the number of training trials required to demonstrate 

proficiency for specific flight tasks. The 26 student pilots who served as subjects 

were recent graduates of undergraduate pilot training (UPT) and were designated 

Naval Aviators with instrument certification. The simulator did not have a visual 

system installed during this research. The motion platform was a 6 DoF synergistic 

hexapod. The training program had two stages. The A stage was primarily focused 

on transition training, aircraft operation, and emergency procedures while flying 

Visual Flight Rules. The B stage, done mostly under Instrument Flight Rules, 

focused on mission-oriented training in antisubmarine warfare and search and 

rescue. Both training stages involved time in the flight simulator and time in the 

aircraft. For the two stages combined, the pilot trainees received 24.0 hours in the 

12 
flight simulator (twelve 30-min sessions) and ten flights in the SH-3 aircraft for a total 

of 25 flight hours. 

McDaniel et al., (1983) found no significant differences in pilot performance 

between the group trained with motion and the group trained without motion. Further 

analysis revealed that the motion condition variable contributed only 4% of the total 

variance in flight hours in the A stage and 7% in the B stage. Variables that were 

predictive of success in the aircraft were: (1) The number of training trials required to 

achieve proficiency in the simulator was positively correlated with the number of 

training trials required to attain proficiency in the aircraft (e.g., the students who were 

slow to learn in the simulator were slow to learn in the aircraft); (2) Instructor 

variability (grading leniency) was correlated with flight hours and the number of task 

trials required for the student; (3) Variability in flight scheduling was correlated with 

student success (i.e., students not receiving regularly scheduled training tended to 

progress more slowly); and (4) Pilot training grades were correlated with later 

success in the operational assignment (fleet readiness squadron). 

Among the conclusions of McDaniel et al. (1983) were the following: 

• Platform motion training in the simulator did not transfer to the aircraft 

• An engineering assessment demonstrated that the motion platform was within 

design specifications.

Horey (1992) evaluated the contribution of motion cueing conditions to 

helicopter pilot performance in a CH-53E Super Stallion simulator (device 2F120). A 

new visual system, presumably of greater weight, was to be installed in a simulator 

upgrade program and the motion cueing capability was to be reduced by restricting 

the displacement of each of the hexapod legs by 50%. The question was whether 

this restricted motion cueing capability would have a negative influence on training or 

on simulator sickness. Flight instructors nominated four maneuvers most likely to 

benefit from motion cueing: 

1. Automatic Flight Control System/Servos Off Flight 

2. Tail Rotor Failure/Separation 

3. Shipboard Landings 

4. External Loads 

A preliminary analysis of simulator motion system response in these four tasks 

determined that only the Tail Rotor Failure maneuver resulted in motion platform leg 

excursions beyond 50 percent of full range. Nevertheless all four maneuvers were 

used in the experiment. A pseudo-transfer design was used to determine the effect 

of motion fidelity on training effectiveness in the simulator. Twenty-four fleet (fully 

trained and qualified) pilots were assigned randomly to three motion groups: no 

motion, restricted motion, and full motion. The restricted motion condition was 

characterized by simulating the 50% reduction in hexapod leg displacement. The 

13 
pilot participants were not informed of the motion condition manipulation. They flew 

each maneuver three consecutive times. The maneuver sequence was 

counterbalanced within each motion condition. Several performance measures were 

defined for each of the four maneuvers. For example, the Tail Rotor Failure 

maneuver was assessed by the following three performance measures: vertical 

speed, pitch, and roll at impact. 

Results from the Horey (1992) experiment showed that only 1 of the 11 

performance measures was significantly (p < .03) affected by motion condition—roll 

at impact in the Tail Rotor Failure maneuver. The results showed greater roll error at 

impact for the motion condition compared to the no motion or restricted motion 

conditions. Performance was significantly worse in the full motion condition. 

The only other statistically significant effect (p < .001) was an interaction 

between trials and motion condition for the “time to landing” performance measure in 

the Shipboard Landing maneuver. The data indicated that performance improved 

over the three trials for both the restricted and no motion groups, but there was no 

performance improvement in the full motion group. 

There are two contrasting interpretations of this finding: (1) the full motion 

condition failed to contribute to performance improvement on this task and 

performance measure; or (2) the full motion condition enabled superior performance 

on this task from the beginning, so no further improvements were likely. 

Horey (1992) generated composite scores for each maneuver using standard 

score transformations but found no significant main effects or interactions for trials or 

motion conditions. This supports the finding that there were no reliable performance 

differences among the motion conditions. Horey concluded that neither restricted 

motion nor full motion cueing led to better performance in the simulator than no 

motion. He suggested that, if the motion manipulation failed to show differences in 

the simulator, it would be very unlikely to produce reliable performance differences in 

transfer to the aircraft. 

Horey (1992) also measured simulator sickness using the traditional symptom 

checklist to determine whether the full motion condition might result in less sickness 

relative to the restricted- or no-motion groups. Motion condition had no significant 

effect on simulator sickness total scores or subscale scores. 

The U.S. Army Research Institute, Rotary Wing Aviation Research Unit, has 

performed ToT analyses in Army helicopter simulators, e.g., Stewart, Dohme, and 

Nullmeyer (2002). This series of experiments showed quantitative evidence of 

positive transfer on all maneuvers (takeoff to hover, hover taxi, hovering turns, 

hovering autorotation, normal takeoff, traffic pattern, normal approach, and landing 

from a hover). A seat-shaker and a 5 DoF motion base were included in the 

simulator, but these studies focused on overall transfer, not on the contribution of 

simulator motion to the training. 

14 
Other discussions about the use of motion for helicopter simulation are 

available in Boldovici (1992), but they are based on opinion and conjecture rather 

than empirical data. The expert opinions collected in this report confirmed the lack of 

empirical evidence to support the training value of motion bases. The pitfalls of 

accomplishing good TOT research were identified, including limited statistical power 

and safety concerns for testing in the aircraft. Boldovici boldly proclaimed that user 

acceptance of the simulator is not a legitimate concern for motion base procurement 

in military simulators. This is a debatable position. 

Military Transport or Other 

Ryan, Scott, and Browning (1978, in Burki-Cohen, et al., 1998) analyzed 

transition training in a P-3 Orion simulator to the S-2 Tracker aircraft. It is unclear 

from the cited source why the authors chose to train in a P-3 simulator, which is a 4-

engine turboprop aircraft, and test transfer to the S-2, a smaller 2-engine aircraft. 

Ryan et al. (1978) chose tasks that featured disturbance motion, such as asymmetric 

engine failure. The results of the transfer experiment indicated that the approach and 

landing performance in the aircraft was not significantly different for the groups 

trained in the simulator with and without motion. One specific task, engine abort on 

takeoff, seemed to benefit from motion in the simulator, but this advantage did not 

transfer to the aircraft. Although there was no evidence of a beneficial effect of 

motion from the TOT results, the pilots indicated by questionnaire that they strongly 

favored having the motion cues available. 

Parris and Cook (1978) performed a quasi-transfer analysis of motion using 

the NASA Ames Flight Simulator for Advanced Aircraft (FSAA) configured to simulate 

a U.S. Air Force KC-135 aircraft. The FSAA was a large 6 DoF motion system (+/- 

10 m longitudinal displacement) with a visual scene and audio cueing. The visual 

system was a model board with a color television camera mounted on a gantry that 

provided a collimated color image to the pilot and co-pilot stations in the FSAA cab. 

In this analysis, the motion system was operated in two configurations-- a full motion 

condition and a restrained motion condition, which was intended to represent the 

motion capability of a typical synergistic hexapod system. Thirty-six qualified KC-135 

aircraft commanders with an average of 1500 hr flight time served as test subjects. 

The subjects were randomly assigned to one of four groups for orientation and 

training: CSI (no visual, no motion); CSV (visual system, no motion), CSM (limited 

motion system, no visual); and CSMV (limited motion and visual system). The

transfer testing was done in the full motion plus visual system. The flight maneuvers 

were based on the perceived problem that shutting down an engine in the KC-135 is 

not allowed by the USAF, thereby limiting training opportunities in the aircraft. Four 

types of engine failures were simulated: 

• Outboard engine prior to lift-off 

• Outboard engine after lift-off 

• Inboard engine prior to lift-off 

15 
• Inboard engine after lift-off 

Preliminary data analysis led to the selection of five criterion measures: Initial 

reaction time, sum of control reversals, lift-off point, total integrated roll and yaw, and 

maximum yaw angle. The subjects performed 26 trials in the four training conditions 

and subsequently performed 10 trials in the full FSAA system capability (CSF) 

condition as a quasi-transfer test. Following each phase of the investigation, the 

subjects completed questionnaires concerning the quality of the simulation. 

Results of the Parris and Cook (1978) experiment showed that the pilots rated 

the combination of visual system and full motion system highly. During the training 

trials, the pilots rated the visual plus motion condition highly “as a training device for 

outboard engine failures,” but the motion system (without visual) received much lower 

ratings. It should be noted that the visual system used in this experiment was 

primitive in comparison to the high resolution CIG systems in today’s simulators. 

The performance parameters showed mixed results with the various simulator 

conditions. The authors showed performance curves, but did no statistical analyses. 

The only apparent outcome was that a visual system is necessary to keep the aircraft 

on the runway during takeoff, regardless of engine failures or whether or not there is 

a motion platform. 

Civilian: Commercial Airlines 

A series of studies was sponsored by the FAA from approximately 1997 – 

2003 to provide an empirical basis for decisions about whether training simulators for 

regional airlines should be required to have the same Level D large, expensive 

motion base as the major carriers. There are cost implications for smaller, regional 

airlines to procure Level D flight simulators or to rent time from major airlines on 

these simulators. The combined issues of training effectiveness and affordability 

prompted this series of studies. 

The first experiment in this series (Go, Burki-Cohen, & Soja, 2000; Longridge, 

Burki-Cohen, Go, & Kendra, 2001) addressed these issues: Are there any flight tasks 

for which a measurable difference in simulator training effectiveness can be found 

with and without platform motion? Does a wide field of view (FOV) visual display 

provide more effective motion cueing than platform motion? Are existing (FAA) 

platform motion qualification criteria optimal? Is there a relationship between pilot 

experience level and the effectiveness of platform motion for training? 

This experiment used a FAA-qualified Level C simulator (a lower rating than 

Level D) of a 30-passenger, twin-turboprop aircraft. The simulator had a wide FOV, 

high-quality visual system, and a 6 DoF motion system. The motion platform 

featured a hydraulic, synergistic hexapod with legs capable of a 60 inch stroke. The 

experimental approach attempted to avoid criticisms of previous ToT studies by 

measuring both pilot input and response, testing maneuvers and pilots likely to 

16 
benefit from motion, preventing pilot and instructor bias, and ensuring sufficient 

statistical power (Go et al., 2000; 2003). Subjects were 42 crews of experienced 

airline pilots, half of whom were assigned randomly to a Motion group and half to a 

No-Motion group. In accordance with the pseudo-transfer design, final testing was 

done in the simulator with the motion on. The test maneuvers were variations of 

engine failure on take-off, satisfying objectives of tasks that are high gain, high 

workload, short duration, and include both maneuver and disturbance motion. 

The results showed that simulator motion did not affect, in any operationally 

meaningful way, initial evaluation, training progress, or ToT (Go et al., 2000). 

Simulator motion also did not, in any consistent way, affect the pilots’ perception of 

performance, workload, training, comfort in the simulator, or acceptability of the 

simulator. According to the authors, there remain the possibilities that the simulator 

motion system used in this experiment may not have been typical of other Level C 

simulators and that the level of lateral acceleration produced by this particular motion 

base as a consequence of simulated engine failure may not have been sufficient to 

act as an alerting stimulus to the pilot. 

A follow-up experiment of the effects of a motion base on airline pilot training 

was done by Go et al. (2003) using the NASA B747-400 simulator at Ames Research 

Center. This experiment, in part, addressed a criticism of the prior research that the 

lateral acceleration motion cueing was attenuated. The NASA B747-400 simulator 

used in this research was FAA-certified Level D with hexapod actuators capable of a 

54-inch stroke. The motion washout filters were tuned and adjusted to provide the 

best possible lateral and vertical translation cues. 

Forty qualified B747-400 pilots, current airline Captains and First Officers, 

participated as subjects. They were assigned randomly to either the Motion or NoMotion simulator condition and flew the simulator in three phases: Evaluation,

Training, and Quasi-Transfer. After practice in the first two stages, both motion 

groups were evaluated in the simulator with the motion platform on (a quasi-transfer 

design). Dependent variables were task-relevant measures of pilot-vehicle 

performance that were derived from over 100 variables recorded in the simulation. 

Four maneuvers were chosen to emphasize the need for motion, including maneuver 

and disturbance cueing, asymmetric high-gain maneuvers, and high workload. 

Examples of the required maneuvers are takeoff with engine failure, precision 

instrument approach, and sidestep landing. Pilots received one familiarization trial on 

each of the four maneuvers, then three practice trials on each maneuver, followed by 

the quasi-transfer test comprising two iterations of the four maneuvers. 

Results indicated a significant difference of group (Motion compared to NoMotion) on 7 of the 17 dependent variables, although the magnitude of the 

differences was small. Post hoc analysis showed that the No-Motion group flew the 

landing maneuvers more precisely than the Motion group, but with less control input. 

This is a surprising result, because the typical finding is that motion supports insimulator flight precision, especially with experienced pilots. This group effect 

17 
transferred to the quasi-transfer trials, meaning that the No-Motion group still flew 

more precisely and with less effort than the Motion group when the motion base was 

active. In contrast, the Motion group had a faster response time than the No-Motion 

group in the engine-out on takeoff maneuver, probably because the motion provided 

a disturbance cue. This difference in response time only emerged during the quasitransfer stage, when both groups received motion cues. 

Both the Motion and No-Motion groups showed improved flight performance 

over time, indicating a training effect. The differences were small, probably because 

the subjects were qualified, experienced pilots and because their training time was 

short—only three trials. For some maneuvers, there were subtle differences between 

the two motion groups with regard to control strategy. Pilot opinions expressed in the 

questionnaires indicated that motion did not affect their perception of the quality of 

the simulator. 

Go et al. (2003) concluded that no benefit of motion was found for recurrent 

training. Based on their statistical analyses, they could have claimed that the NoMotion condition was better, at least on a minority of the dependent measures. The 

results suggest that, for a large commercial aircraft, training without motion helps 

pilots adopt a steady control strategy rather than over-reacting to motion cues. 

General Aviation 

In a classic ToT analysis by Koonce (1974, in Roscoe, 1980), three groups of 

Air Force pilots of varying levels of experience received two days of refresher training 

in instrument flight procedures using a Singer-Link GAT-2 simulator. Then they 

performed the same tasks in a Piper Aztec on Day 3. The three groups differed only 

in motion condition—one group had no motion, one group had sustained (no 

washout) motion, and the third group had motion with washout. 

There were several key outcomes illustrated in this experiment: (1) the 

performance of all three groups improved over the two days of practice and training; 

(2) all three groups continued to improve on the third day (in the aircraft); (3) there 

was evidence, though not statistically significant (0.10 > p >0.05), of an interaction 

between performance in the simulator and in-flight, where the no-motion group 

performed best. Koonce (1974, in Roscoe, 1980) concluded that simulator motion 

tends to increase the subjects’ acceptance of the simulator, improve performance in 

the simulator, and reduce workload, but these benefits of motion in the simulator do 

not transfer to performance in the aircraft. 

Another classic motion ToT experiment was performed by Jacobs and Roscoe 

(1980) at the University of Illinois Aviation Research Laboratory. Four groups of nine 

non-aviators (flight-naive subjects) received training in basic instrument flight skills. 

One group trained in the Piper Cherokee Arrow aircraft rather than the simulator. 

Three of the groups received training in the simulator, one group with normal 

washout banking motion, one group with no cockpit motion (fixed-base), and the 

18 
other group with the direction of the banking motion reversed half the time. One 

aspect of the results was particularly surprising—none of the subjects in the random 

reversal group commented, or seemed to perceive, that the roll motion was 

sometimes in the wrong direction. Results from the practice sessions indicated an 

interaction between the aptitude predictor score and motion condition. Students with 

high aptitude scores performed nearly equally under any motion condition. Students 

with low aptitude scores seemed to perform better with the normal washout motion 

than with either the random-direction or the no-motion conditions. Results from the 

transfer test to the aircraft indicated that performance was nearly equivalent for the 

normal motion and the no-motion groups. Performance of the random washout 

group was not quite as good, except for the high-aptitude students. 

Both the Jacobs and Roscoe (1980) and the Koonce (1974, in Roscoe, 1980) 

studies were done with a very limited motion base capability. The results are not 

necessarily indicative of more capable motion base systems. 

The generalization of empirical findings is always an issue. How meaningful 

are results from small motion bases on small civilian aircraft simulators to other types 

of aircraft? There is no simple answer. Overall, the evidence from all sources must 

be considered for their contribution to decisions about specific aircraft types, 

missions, maneuvers, and other application features. 

Fighter and Attack 

Martin and Waag (1978) performed a ToT experiment using the Air Force 

Advanced Simulator for Pilot Training (ASPT). Pilots were trained in the simulator, 

with and without 6 DoF motion, in basic contact, approach and landing, and aerobatic 

tasks. No information is available about the quality of the motion provided by the 

ASPT motion base. The authors reported that positive transfer occurred for both 

groups, but there were no significant differences between the motion and no-motion 

groups when tested in the T-37 aircraft. 

Hagin (1976) used the ASPT to expose Air Force pilot trainees to simulator 

training with and without 6 DoF motion. Flight tasks included takeoff, landing, and 

overhead traffic pattern. Transfer tests in the T-37 aircraft showed no significant 

differences between the motion and no-motion groups. In a follow-up experiment 

(Hagin, 1976) trainees progressed through the entire T-37 syllabus in the ASPT 

simulator, with and without motion. Subsequent performance ratings in the aircraft 

found no differences in the performance of pilots trained with or without motion in the 

simulator. 

Woodruff, Smith, Fuller, and Weyer (1976) used the ASPT and the T-37 

aircraft in another transfer experiment and found no difference between the motion 

and no-motion groups in the time to reach criterion performance in either the 

simulator or the aircraft. 

19 
The U.S. Air Force Scientific Advisory Board (1976, in Semple, et al., 1980) 

reviewed the existing evidence on motion platforms for simulation and concluded as 

follows: 

Based on the motion, no motion studies and experiments which 

have been run to date, a convincing case cannot be made for 

either including or excluding platform motion in flight simulator for 

tactical fighters. ... in the absence of valid, reliable measures of 

pilot performance, any attempt to assess the effects of training in 

a simulator on that performance will be unsatisfactory. (in 

Semple, et al., 1980, pp. 138-139) 

Martin (1981) summarized five experiments using the ASPT and one using the 

Simulator for Air-to-Air Combat (SAAC) and concluded that the data did not show 

positive transfer of training from a motion platform. 

The addition of task-correlated platform motion cueing results in 

negligible transfer of training for initial jet piloting skills ...Existing 

data do not support procurement of sophisticated six-post 

synergistic platform motion systems for pilot contact skill 

acquisition and existing simulators for pilot training possessing 

synergistic platform motion systems can be equally effective if 

the motion system is not used. Both of these outcomes would 

result in substantial cost savings. (Martin, 1981, p. 2) 

Summary of Empirical Evidence for Motion 

In many ways, little has changed in the quarter century since Paul Caro 

wrote, “Flight simulator motion has been demonstrated to affect performance in the 

simulator, but ... transfer of training studies have failed to demonstrate an effect 

upon in-flight performance” (Caro, 1979, p. 493). 

In a summary of motion cue requirements for flight simulators, Rolfe and 

Staples (1986, p. 126) concluded that, while extensive data support the beneficial 

effects of motion on the manner in which a pilot controls his simulated aircraft, “there 

are almost no results from transfer of training experiments showing that simulator 

motion is an effective training aid for most flight conditions.” Interestingly, they 

mentioned that the difficulties of conducting ToT studies make it probable that there 

never will be enough data from ToT studies to serve as the sole basis for a decision 

to provide inertial motion cues in a training simulator. 

Other Analyses of Flight Simulator Motion 

Hall (1989) analyzed the need for motion platforms in training simulators and 

the factors that should be taken into account when assessing their training value. He 

20 
offered a logical, reasoned argument for the benefits of platform motion under certain 

circumstances, namely, when: 

• A relatively unstable aircraft is being simulated (e.g., a helicopter or VSTOL 

aircraft) 

• The pilot must engage in high gain, high frequency, manual control 

• Pilot control activity and workload need to be similar to the actual aircraft 

Hall (1989) reviewed research that found pilot control activity to be more 

similar to that found in the aircraft when simulator motion is engaged. He suggested 

that it is reasonable to expect that similar pilot control activity in the simulator and the 

aircraft will contribute to good training transfer. Hall further suggested that the 

consistent failure to find positive TOT from motion might be due to inadequate motion 

systems used in the research. While this argument may have validity for research 

conducted prior to about 1980, more recent TOT evaluations have specifically

analyzed and tuned the motion systems prior to data collection, e.g., Go, et al. 

(2003). Nevertheless, Hall’s cogent arguments for the benefits of motion under 

certain conditions deserve further investigation via empirical TOT experimentation. 

We concur with his recommendation that the relationships among flight tasks, aircraft 

types, manual control activity, and motion cueing requirements would benefit from 

further research. 

Heintzman, Middendorf, and Basinger (1999) analyzed the force cueing 

requirements for tactical combat training devices. This ambitious review summarized 

the history of motion cueing systems including motion platforms, dynamic seats, and 

other devices. Heintzman stated that current motion platforms and other force cueing 

devices are far superior to the systems that were in use nearly 25 years ago when 

the Air Force decided to remove motion systems from fighter simulators. He 

recommended that a database of force cue requirements should be developed, a 

research program was needed to evaluate the benefits of various force cue devices, 

operational methods were needed for evaluating the contributions of force cueing 

systems, and flight test programs were needed to document pilot performance in the 

aircraft. Heintzman et al. recommended that the need for force cueing in combat 

flight training systems be determined on the basis of the assumption that, if the pilot 

in actual flight uses force cues, then they should be reproduced in the flight simulator, 

cost permitting. 

Heintzman et al. (1999) recommended engineering development of force 

cueing systems, but did not mention training processes or transfer of training. This 

“realism” argument is unpersuasive in this era when pilots are increasingly 

challenged to perform systems management tasks rather than just “stick and throttle” 

manual control. There is no doubt whatsoever that force cues occur in flight. The 

main question is whether providing force cueing in the simulator provides positive 

transfer of training and is cost-effective. Two secondary issues are whether force 

cueing contributes to similarities in manual control behavior and pilot acceptance of 

the simulator. 

21 
Longridge et al. (2001) summarized the results of an extensive literature 

review stating that simulator platform motion might improve the acceptability of the 

simulator, at least when pilots are aware of the motion manipulation. Also, motion 

seems to improve pilot performance and control behavior in the simulator, particularly 

for disturbance tasks and in aircraft with low dynamic stability. However, their review 

found no evidence that any benefits of platform motion result in training transfer to 

the aircraft. 

Are Motion Bases Necessary to Train Specific Tasks? 

Some authors have suggested that motion bases are needed for specific tasks 

where visual information is limited, such as landing in brownout or shipboard landing. 

Interviews with six qualified military helicopter pilots at the Naval Postgraduate 

School, led to a consensus that, if hovering at 10 ft altitude in a brownout, neither 

instruments nor motion cues would be sufficient to maintain a manual hover for more 

than a matter of seconds. A minority of the pilots claimed that, with a radar altimeter, 

they could maintain a hover in a large helicopter with no outside visual information. 

Under normal operational conditions of good visibility, holding a hover within 

approximately 1 ft displacement is normal. Hover requires visual information about 

position. The optical flow characterizing a velocity vector (change in position) 

becomes an error to be nulled in the closed-loop manual control task. It is highly 

unlikely that simulator motion cues in a flight simulator would be sufficient to support 

manual hover in the absence of visual information. If it can’t be done in the aircraft, 

why should it be possible in the simulator? However, there can be training benefit 

from certain departures from reality, as mentioned earlier. Would learning to sustain 

a hover without vision in a motion simulator have positive transfer to the aircraft? 

This is an empirical question. 

In a review of flight simulator training requirements, Semple (1980) indicated 

that simulator motion is beneficial for training pilots to deal with flight control in 

turbulence (e.g., Borlace, 1967). In addition, simulator motion has been found to be 

beneficial for training responses to emergency situations. Cohen (1970) found that 

response time to activate emergency brakes during a system failure was longer 

without motion cues. 

Dangerous tasks and emergency procedures can be practiced and trained 

without risk in flight simulators. One argument for simulator motion is that it can 

contribute to the simulation of dangerous tasks and emergency procedures by 

providing disturbance cues for various failures, such as engine failure. These 

hypotheses are difficult, if not impossible, to evaluate empirically because transfer 

performance in the actual aircraft would, by definition, be dangerous. Therefore, a 

pseudo-transfer design is the only feasible way to accomplish this type of research. 

Is it possible that a simulator motion base could provide negative transfer of training 

in this situation? It is unclear how this question could be tested because a pseudo22 
transfer design does not answer the question and transfer testing in the aircraft is 

high risk. 

Reasons Other than Training for Motion Bases in Helicopter Simulators 

In-Simulator Performance 

The research literature indicates a large contrast between the effects of 

simulator motion on training transfer and on performance in the simulator. As

reviewed above, positive ToT for motion has rarely, if ever, been found, but it is 

common to find that simulator motion leads to better, more precise pilot-aircraft 

performance in the simulator. This benefit of simulator motion is more likely to be 

found when the test subjects are experienced pilots. 

One example of this type of analysis was done by Ricard and Parrish (1984), 

who investigated the effects of simulator platform motion and G-seat cueing on the 

ability of qualified Navy pilots to maintain a hover over a simulated ship. The best 

hover control performance was associated with the motion base condition, whereas 

the poorest control was associated with the fixed-base condition. Performance with 

the G-seat was intermediate. This outcome exemplifies the common finding that 

experienced pilots tend to perform better in the simulator with motion. 

But the purpose of a training simulator is to train the pilot to fly the aircraft, not 

the simulator. In short, if performance in the simulator is the criterion, a motion base 

is justifiable. However, if positive ToT to the aircraft is the criterion, there are virtually 

no data to support the requirement of a motion base. 

Handling Qualities Research 

Schroeder (1999) performed a series of thorough investigations of the effect of 

simulator motion on pilot-vehicle performance. This research used the NASA Vertical 

Motion Simulator (VMS), which is one of the largest motion platforms in existence, 

providing approximately 60 ft vertical displacement and a 40 ft longitudinal or lateral 

displacement. For some flight tasks in this research, the motion provided by the VMS 

had a one-to-one correspondence with the visual cues to motion. Experienced 

NASA test pilots flew an AH-64A Apache model in the reconfigurable VMS. This 

series of five studies varied the available dynamic range from full motion to no 

motion. Four DoF were investigated: roll, yaw, lateral translation, and vertical 

translation. Pitch rotation and longitudinal translation were not investigated. 

The results indicated that both lateral and vertical translational motion cues 

significantly improved pilot-vehicle performance and reduced pilot workload. The 

yaw and roll rotational motion cues were not as important as the lateral and the 

vertical translational cues. When lateral translational motion was combined with the 

visual system optical flow consistent with yaw, pilots believed they were rotating 

when, in fact, they were not. Vertical platform motion influenced pilots’ estimates of 

23 
altitude. This finding casts doubt on the commonly held view that pilots in simulators 

estimate altitude and altitude change based solely on visual cues. Based on these 

findings, Schroeder (1999) recommended an alternative to the common hexapod 

motion platform, opting for an emphasis on translational (rather than rotational) cues. 

The research by Schroeder is an important contribution to understanding the 

role of motion platforms in simulated helicopter flight. However, the results do not 

provide insight into any training benefit provided by motion platforms. As noted by 

Schroeder (1999, p. 63), “This report has illustrated the performance and opinion 

differences that arise when simulator motion is provided, but it has not shown if there 

is any training benefit to the use of motion.” 

In addition, several of the significant motion effects were found with maneuver

motion as well as disturbance motion. However, Schroeder (1999) used a very large 

and powerful motion base and the experimental subjects were experienced NASA 

test pilots. The results could be quite different for a normal, less capable motion 

base, and for pilots who are inexperienced helicopter trainees rather than NASA test 

pilots. 

In another experiment performed with the NASA VMS, several visual and 

motion characteristics were tested for their influence on a pilot’s ability to perform 

precise landings in an autorotation (Dearing, Schroeder, Sweet, & Kaiser, 2001). 

Seven experienced NASA test pilots flew a representation of a UH-60A Black Hawk 

helicopter. Combinations of four terrain features, three terrain grids, and three 

motion platform displacements (none, very limited, and very large) were used in a 

repeated measures design. Platform motion had a small but statistically significant 

effect on touchdown sink rate, although all three levels of motion resulted in 

“adequate” performance. Post hoc tests found the “large motion” condition to be 

significantly different (lower touchdown vertical velocity) from the limited and the no 

motion conditions. The pilots also rated motion fidelity, and results were 

unsurprising—the large motion condition was rated as having the highest motion 

fidelity. The results of this research again showed that a large, well-tuned motion 

base, as provided by the NASA VMS, can contribute to improved performance of test 

pilots in the simulator and that pilots like motion bases. The results provided no 

input, however, to decisions about training or training effectiveness. 

Pilot Preference and User Acceptance 

Pilots like simulator motion. Perhaps it is more accurate to say that there is 

consistent evidence that pilots dislike a static, no-motion simulation. 

An experiment by Caro, Jolley, Isley, and Wright (1972) reported that pilots 

prefer motion cues in simulation, presumably because they increase “realism.” The 

authors also suggested that more experienced pilots might require more 

sophisticated motion systems because they would be capable of detecting more 

subtle differences from the aircraft motion. 

24 
 Parrish, Houck, and Martin (1977) reported an investigation of motion in a 

helicopter simulator. They found that pilots performing slalom maneuvers preferred 

motion, but objective performance measures indicated no advantage of the motion. 

The reduced control activity with motion suggests that pilots modified their control 

strategies with motion cues, supporting their subjective preferences. 

Hall (1978; cited in Burki-Cohen et al., 1998) used a moderately capable 3 

DoF motion base combined with a wide (200 deg horizontal) FOV visual scene to 

determine how various sources of information affected pilots’ ability to control a 

simulated Harrier aircraft. Using the Cooper-Harper scale, pilots indicated a 

consistent preference for motion over the no-motion condition. They rated motion as 

most important when the peripheral visual cues were eliminated and only instruments 

and motion were available. 

In an analysis of airline pilot response to variations in simulator motion, Reid 

and Nahon (1988) used a 6 DoF synergistic hexapod motion base and several 

conditions of motion -- classical washout, optimal control, coordinated adaptive, and 

no-motion. They found little impact of motion type on pilot performance and control 

activity, but a strong, nearly unanimous, dislike of the no-motion condition. 

An important contribution was made in an investigation of motion effects on 

pilot performance and preference using a B727 simulator (Bussolari et al., 1988; Lee 

& Bussolari, 1989). The simulator had a Level C motion base and a visual display 

with a moderate, 75 deg horizontal FOV. Three motion conditions were used: (1) full, 

6 DoF motion; (2) a 2 DoF condition comprising vertical and lateral translational 

motion; (3) a “special effects” vibration condition characterized by small-amplitude 

(.63 cm) displacement in the vertical axis. This small-amplitude motion condition was 

designed to provide cues for touchdown bump, runway roughness, and buffets 

associated with flap, gear, and spoiler extension. These special effects were 

provided in the two other motion conditions as well. The results showed no 

differences between the three motion conditions in pilot performance, control 

behavior, or pilot ratings of workload, utility for training, and realism. 

These results are distinct from previous research because a very limited 

amount of motion was found acceptable to pilots, as opposed to previous studies 

where pilots consistently disliked the extreme case of no-motion. This finding is 

consistent with an interpretation that a small amount of motion may be sufficient to 

contribute to immersion and presence in the simulation, supporting pilot acceptance. 

These investigations of pilot preference do not provide information about 

training transfer. But, in decisions about whether or not to purchase, maintain, and 

operate a motion platform, pilot preference and acceptance of the simulator are 

legitimate factors to be considered, independent from training transfer. 

25 
Motion Bases for Prevention of Simulator Sickness 

Since the early 1970s, researchers have suggested that simulator sickness 

might be reduced by simulator motion (Clark & Stewart, 1973; Puig, et al., 1978). 

This concept is not only simple and intuitive, but it is consistent with the major theory 

of motion sickness variously called sensory conflict, neural mismatch, or sensory 

rearrangement theory (Reason & Brand, 1975). The core of this theory is that motion 

sickness occurs when information from the visual, vestibular, and other sensory 

channels is not consistent with past experience. Anecdotal evidence in support of 

this theory as the basis simulator sickness is common. For example, studies of the 

incidence of simulator sickness in Army flight simulators mention that the consensus 

of instructor operators and trainees is that simulator sickness is more common when 

the motion base is off (Gower & Fowlkes, 1989; Gower, Fowlkes, & Baltzley, 1989). 

Despite the theory and the anecdotal evidence, neither survey data nor 

empirical data support the hypothesis that motion bases prevent simulator sickness. 

In a survey of 10 different types of flight simulators and over 1,000 flights, symptoms 

of simulator sickness were found in 10-60% of the pilots across all 10 of the 

simulators, both fixed-base and motion-base (Kennedy, Lilienthal, Berbaum, Baltzley, 

& McCauley, 1989). 

As mentioned earlier in this report, Horey (1992) tested three motion 

conditions—full motion, restricted motion, and no-motion in a CH-53E helicopter 

simulator and found that the motion condition had no significant effect on simulator 

sickness total scores or subscale scores. 

An investigation of the hypothesis that a large, well-tuned motion base would 

decrease simulator sickness was done by Sharkey and McCauley (1992) using the 

NASA VMS. Helicopter flight tasks, including a sawtooth hover pattern, were chosen 

because the large translational capability of the NASA VMS enabled nearly 100% of 

the maneuver motion displacement. Pilots were assigned randomly to the full motion 

group or the no motion group. Surprisingly, the level of simulator sickness was not 

significantly different between the motion and no-motion groups. Guidelines for the 

reduction of motion sickness in simulation and virtual environments were developed 

from this series of experiments at NASA Ames Research Center, but adding a motion 

base was not one of the recommendations (McCauley & Sharkey, 1992). 

Other Potential Advantages of Motion Bases 

Simulator motion appears to be beneficial in the evaluation of cockpit displays. 

In an experiment by Ince, Williges, and Roscoe (1975), the results showed that pilot 

evaluations of cockpit displays in a simulator corresponded more closely to 

evaluations in flight when the simulator motion system was on than when it was off. 

26 
Summary Arguments on Motion Bases 

Virtually no empirical evidence supports the position that flight simulator 

motion bases contribute to transfer of training. This result has been found 

consistently across a range of aircraft types, missions, maneuvers, and measures. If 

one’s perspective is that simulator features need to “earn” their way into training 

simulators, then motion bases have failed to do so. If one believes, like the FAA, that 

good training results have been obtained in the past using motion bases, so we dare 

not settle for anything less, then motion bases will be mandated. 

Given, that simulator motion bases are inherently incapable of providing high 

fidelity motion representation for anything but the most benign flight maneuvers, 

perhaps today’s highly capable visual systems provide such high quality motion cues 

(vection) as to render motion bases superfluous (Burki-Cohen, et al., 1998). 

Roscoe (1980, p. 216) concluded that, “Complex cockpit motion, whether 

slightly beneficial or detrimental on balance, is not worth much; it has so little effect 

on training transfer that its contribution is difficult to measure at all.” 

On the other hand, pilots strongly prefer to have motion bases in simulators 

(e.g., Reid & Nahon, 1988). Although there will always be debate about what type of 

motion is most preferred, or what parameters of washout are preferred, there is 

nearly unanimous consensus that pilots dislike the “no-motion” (fixed-base) case. 

Perhaps the pilot preference for motion is, in fact, a dislike of no motion. A 

stationary simulator is likely to work against the sense of immersion or presence. 

The vestibular and proprioceptive senses detect this type of extreme, quiescent state 

and signal a conflict with the vection induced by the visual system. Even if a small 

amount of motion does not contribute to training effectiveness, it may be worthwhile 

to avoid the extreme no-motion state by contributing to immersion, presence, and 

pilot acceptance. Adding a limited amount of motion, even a small amplitude 

vibration, as found by Bussolari et al. (1988) and Lee and Bussolari (1989) is highly 

likely to make a simulator more preferable to pilots. This recommendation is 

consistent with the suggestion by Burki-Cohen, et al. (1998) that adding vibration to a 

non-motion simulator may satisfy pilot preferences for motion. 

Other Motion Cueing Devices 

Force cueing devices, such as G-seats, G-suits, seat shakers, and helmet 

loaders have been used in military fixed-wing simulation to increase the realism of 

sustained G-loading and, sometimes, to simulate vibration situations such as 

turbulence, buffet, and runway rumble. These alternative force cueing devices are 

intended to convey sensory information to the pilot regarding acceleration cues and 

biomechanical events that would be associated with those events in flight. As long 

ago as 1978, there were attempts to integrate various force cueing features into a 

27 
single low-cost system to achieve acceleration onset cues similar to those in flight 

(Albery, Gum, & Kron, 1978). 

Although both motion platforms and force cueing systems provide motion 

onset cues, there are differences between them and, ideally, they can operate 

synergistically. Motion platforms are limited in displacement and, therefore, are 

limited to providing either motion onset cues in the correct direction or more 

sustained changes in orientation if they are of low magnitude. Also, motion platforms 

stimulate both the vestibular and the proprioceptive sensory systems, whereas force 

cueing systems stimulate primarily the latter. 

Force cueing devices can be implemented independently or as a complement 

to a motion platform. Although these devices are more applicable to the sustained 

linear acceleration found in fixed-wing fighter aircraft than in helicopters, they could 

be effective for dynamic flight tasks such as NOE, contour flight, and autorotation. In 

addition, the dynamic seat can provide motion cues in vertical acceleration 

maneuvers such as mask/un-mask and landing. 

Research Program to Support Simulator Decisions 

An ongoing program of research on training effectiveness is essential to 

support continued improvement of training effectiveness and efficiency. Listed 

below are recommended research issues and possible approaches. 

1. Determine whether replicating noise and vibration cues in the simulator can 

provide effective training while promoting user acceptance in initial entry rotary 

wing training. Analyze motion conditions including the full hexapod, a “special 

effects” vibration of less then 1 cm displacement, and a no-motion condition. 

Ideally, both pseudo-transfer and ToT designs should be implemented. Both 

disturbance cues and maneuvering cues should be included in the selection of 

the tasks and maneuvers. Criterion measures would include: (a) performance

in the simulator; (b) pseudo-transfer performance; (c) transfer to the aircraft; 

(d) opinion survey of trainees and instructors to assess the sense of presence, 

realism, and overall preference. 

2. Evaluate the benefit of dynamic seats, either independently, or in conjunction 

with #1 above. 

3. Compare the contribution of motion conditions and other force cueing devices 

to the training of specific tasks focusing on disturbance cues, as in loss of tail 

rotor emergency procedures. 

4. Apply the basic research paradigm in #1 above at different stages of training 

to test whether the level of pilot experience influences the outcome. 

28 
5. Apply the backward-transfer approach (Cross & Gainer, 1987; Stewart, 1994) 

to investigate the transfer between aircraft and simulator for various motion 

conditions. 

Instructional Design is the Key to Successful Training 

Simulators do not train. They are tools used by good instructors to achieve 

training objectives. Motion is but one of many technological components of a flight 

simulator for training. Quality instructional design, when implemented by quality 

instructors, will result in positive transfer of training. Contrary to the opinion of many 

simulator engineers and operational personnel, realism is not “the answer” and there 

is no certainty that the price of a simulator is related to the training benefits received. 

As noted by Caro (1979, p. 500), “Whether motion (or any other dimension of

simulation) is needed in order to achieve a particular training objective remains an 

empirical question. However, empiricism must build upon logical analyses that 

establish the relationships to be tested.” 

Advances in intelligent tutoring systems show promise for performing some 

instructor tasks. This approach has been investigated for application in a UH-1 

simulator for Army helicopter training (Mulgund, Asdigha, Zacharias, Krishnakumar, & 

Dohme, 1995; Stewart & Dohme, 2005). 

Research on training effectiveness has shown that how a simulator is used is 

more important than specific training technologies (Salas, Bowers, & Rhodenizer, 

1998). Issues such as instructional design, procedural fidelity, and visual system 

fidelity are likely to have much more influence on training effectiveness than whether 

or not the simulator has a motion base. 

A Perceptual Control Theory Perspective 

An alternative approach to determining what information provides training 

value derives from cybernetics and negative feedback control systems (Taylor, 

1999). Perceptual Control Theory (PCT; Powers, 1973; 1989) and more generally, 

control theory applied to human behavior (Jagacinski & Flach, 2003; Riccio & 

McDonald, 1998) provides not only a framework but an approach to analyzing human 

behavior to determine what perceptual information must be available to the operator 

to enable control in the task. One of the basic tenets of PCT is that the fundamental 

perception-action loop requires a reference value, which is the perceptual equivalent 

of an objective or intention. The reference value provides a specification for the 

desired state of the perceptual information that is under control—information known 

as the “controlled variable.” The reference value tells when the controlled variable is 

being maintained successfully within limits. Or, to say it another way, reference 

values represent what the operator would perceive when a task is being done 

successfully. 

29 
Figure 3. Simple closed-loop model; note Reference input (from Jagacinski & Flach, 

2003). 

For example, if a helicopter pilot in a hover were told to perform a hovering 

right turn of 90 degrees, the pilot would introduce right pedal and other appropriate 

control changes to maintain altitude and position over the terrain while yawing to the 

right. The key question is—what does the pilot do to perceive if/when the task is 

completed? In this case, he/she monitors the terrain and possibly glances at the 

instruments to determine heading. When he or she is approaching approximately 90 

degrees right—the reference value for the perception of orientation—the pilot will 

reduce the yaw rate to zero. When the pilot perceives visually that the new 

orientation matches the reference value, the task is complete. A visual criterion is the 

definition of the end state and visual information is being sampled during the 

maneuver until the difference between current status of a visual perception and the 

reference value becomes null. 

In this example, other sensory information was available, such as a rotational 

velocity, perceived by vestibular and proprioceptive senses, haptic feedback from the 

feel of the controls, and perhaps changes in sound and vibration associated with 

engine, blades, and so on. These information sources could be considered inside 

control loops with their own reference values. But it was the visual information that 

confirmed when the reference value for this task was attained: 90 degree right hover 

turn. If the pilot attempted to perform this simple maneuver based on the non-visual 

feedback information, he would be profoundly unsuccessful. What does this say 

about the information that is essential in a flight simulator for training? 

PCT, more than other applications of control theory, emphasizes the fact that 

many control systems can successfully operate simultaneously. Marken (2001) 

gives an example of two independent control systems controlling two different 

perceptual variables (vertical velocity and lateral displacement) simultaneously

without conflict. An entire flight scenario could be broken into a hierarchical set of 

closed-loop control tasks and the perceptual state associated with the reference 

value of each task could be identified. 

Figure 4 provides another example of a closed-loop control system. This one 

shows the reference signal “r” as the goal, intention, or criterion for the level of the 

perceptual variable (the “Percep Signal” in the diagram) that is to be achieved. Note 

30 
that environmental disturbance is another input that influences the state of the 

perceptual variable. The system varies its outputs (Output Var) so as to compensate 

for such disturbances and maintain the perceptual variable at the specified reference 

value (the value of r). 

Figure 4. Another control loop example, “r” is the Reference Signal (from Powers, 

1989). 

Figure 5, derived from Schroeder (1999), shows a control loop for a flight 

simulator. The reference value is implied in the “Task demands” input arrow. The 

question is: What is the sequence of task demands? For example, does a pilot set 

references for the control of all three of the perceptual variables shown in the figure 

(stick displacement, motion cues, and visual cues)? Do all pilots control the same 

perceptual variables? Do all pilots set the same references for these variables? How 

does training affect the variables controlled by the pilot? 

Figure 5. Control loop for a flight simulator (derived from Schroeder, 1999). 

31 
Because pilots rely on visual information for nearly all flight tasks, accurate 

representation of the visual world, both inside and outside the aircraft, is essential in 

a training simulator. A simulator motion base plus the force feedback of controls 

(cyclic, collective, pedals) may provide only secondary feedback in the sense that it is 

used by perceptual systems that run in parallel to those controlling visual variables. 

So control of non-visual variables may allow for some redundancy in control, which 

may lead to improved control performance in the motion base simulator. This 

concept is consistent with the work of Hess (1990, p. 482) who said that, “human 

fundamental compensation for the vehicle dynamics in the primary control loop are 

not created by motion feedback. Motion feedback merely serves to “tune” the 

pilot/vehicle dynamics to improve tracking performance by decreasing the highfrequency phase lags... after the fundamental pilot compensation occurs.” 

If one reads the literature pertaining to all of the examples of closed-loop pilotvehicle systems in the previous figures, it is apparent that considerable effort and 

impressive progress has been made through the mathematical and engineering 

description of the control loop dynamics of the control processes involved in piloting. 

It is also apparent that very little focus has been given to the sequence of reference 

values that occur over the duration of a flight scenario. Probably one reason for this 

knowledge gap is that engineering analyses are more tractable than determining 

cognitive states pertinent to “intentions” represented as reference values. 

An important part of flight training is to learn procedures, which involves 

learning the perceptions and the sequence of reference values for those perceptions 

that enable the pilot to accomplish the tasks in an acceptable manner. The trainee 

must learn many things including:

• What is the mission (the highest level reference value, which specifies 

what the perception of a successful mission “looks like”)? 

• What are the mission segments (the next level down; the sequence of 

reference specifications for the perceptions that make up “the 

mission”)? 

• What are the tasks and maneuvers (still more detailed reference 

specifications for the perceptions that make up the tasks and 

maneuvers that accomplish mission segments)? 

• What are the perceptual and reference values for control loops 

involved in all the tasks and maneuvers that comprise the mission? 

• How do trainees organize their control systems so that they can act to

counter disturbances and bring their perceptions to the required 

reference values? 

More work is needed on the definition and analysis of the perceptual and 

reference values involved in performing pilot tasks in order to determine the degree 

of simulator fidelity required to appropriately train pilots to carry out their missions. 

Key aspects of this analysis will be to determine the perceptual variables that pilots 

32 
actually control (Marken, 2005) and the sequence of reference values that must be 

set to accomplish a task. 

Determining reference values and corresponding perceptual variables that 

define the task demands for flying will inform the selection of necessary flight 

simulator features as well as the development of instructional design. Research 

aimed at identifying sequences of reference values that are used to carry out tasks 

can inform the development of learning objectives. Hendy and Ho (1998), for 

example, applied PCT concepts to identify the “goal setting” sequences carried out 

by C-130 crews. The result was a set of learning objectives described in terms of a 

sequence of perceptual goals the crew had to learn to achieve. Clearly, however, a 

pilot trainee needs to learn more than just the sequence of goals (reference values) 

to adopt in order to carry out specific flight maneuvers. The trainee also must learn 

the plant dynamics and control strategies that enable him/her to achieve each of 

these goals while countering environmental disturbances. 

The analysis of flying tasks into a series of reference values for perceptual end 

states offers an innovative approach to accomplishing effective training by defining 

what sources of perceptual information are essential to the training process. 

Conclusions 

• There is a substantial body of scientific data to support the training 

effectiveness of flight simulation. Flight simulators are unquestionably 

valuable for accomplishing training safely. 

• There is virtually no scientific evidence to support the training effectiveness of 

motion platforms. 

 

• Motion contributes to in-simulator performance, particularly for experienced 

pilots. 

• It is possible that motion cues may be beneficial for flight training in unstable 

aircraft and tasks involving disturbance cues, although the evidence is weak. 

• Motion, noise, and vibration contribute to the realism, sense of presence, and 

pilot acceptance of a simulator. 

• Detailed analysis is needed of the reference values in pilot-vehicle closed-loop 

models. 

o Flight maneuver tasks are primarily visual and have a visual reference 

value. 

o Pilot trainees cannot safely “close the loop” around a vestibular or 

proprioceptive reference value (without vision). 

• There is no reliable evidence that a motion base prevents simulator sickness. 

33 
• Instructional design is more important than physical fidelity for training 

effectiveness. 

Recommendations 

• Perform the research necessary to better understand the relationship among 

training effectiveness, training technology (including motion bases and other 

motion cueing devices), aircraft stability, pilot tasks and workload, and training 

objectives. 

• Consider implementing limited motion and vibration (displacement less than 1 

cm) to gain the following benefits: 

o Provide event cues (e.g., landing bump, effective translational lift) 

o Avoid the fixed-base doldrums 

o Increase pilot acceptance of the simulator 

• Investigate pilot performance including traditional manual control and 

Perceptual Control Theory relative to various flight tasks and sources of 

sensory and perceptual information. 

34 
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