DOT/FAA/AM-96/15 

Office of Aviation Medicine 

Washington, D.C. 20591 

19960606 111 

Use of Off-The-Shelf 

PC-Based Flight 

Simulators for Aviation 

Human Factors Research 

Dennis B. Beringer 

Civil Aeromedical Institute 

Federal Aviation Administration 

Oklahoma City, Oklahoma 73125 

April1996 

Final Report 

This document is available to the public 

through the National Technical Information 

Service, Springfield, Virginia 22161. 

0 

U.S. Department 

of Transportation 

Federal Aviation 

Administration 
NOTICE 

This document is disseminated under the sponsorship of 

the U.S. Department of Transportation in the interest of 

information exchange. The United States Government 

assumes no liability for the contents or use thereof. 
Technical Report Documentation Page 

1. Report No. 2. Government Accession No. 3. Recipienfs Catalog No. 

DOT/FANAM-96/15 

4. Title and Subtitle 5. Report Date 

Use of off-the-shelf PC-based flight simulators for aviation human factors April1996 

research 

6. Performing Organization Code 

7. Author(s) 8. Performing Organization Report No. 

Dennis B. Beringer, Ph.D. 

9. Performing Organization Name and Address 1 0. Work Unit No. (TRAIS) 

FM Civil Aeromedical Institute 

P.O. Box 25082 

Oklahoma City, OK 73125 

11. Contract or Grant No. 

12. Sponsoring Agency name and Address 13. Type of Report and Period Covered 

FM Office of Aviation Medicine 

Federal Aviation Administration 

800 Independence Avenue, SW. 

Washington, DC 20591 

14. Sponsoring Agency Code 

15. Supplemental Notes 

16. Abstract 

Flight simulation has historically been an expensive proposition, particularly if out-the-window views were desired. 

Advances in computer technology have allowed a modular, off-the-shelf flight simulation (based on 80486 processors or 

Pentiums) to be assembled that has been adapted, with minimal modification, for conducting general aviation research. 

This simulation includes variable flight instrumentation, forward, 45 and 90 degree left external world views, and a map 

display. Control inputs are provided by high-fidelity analog controls (e.g., damped and self-centering yoke, highperformance throttle quadrant, gear, flap, and trim controls; and navigation radio frequency select). The simulation is 

based upon two commercially available flight simulation software packages, one originally designed as an instrument 

flight trainer and the other as a "game" -type flight simulation. The provisions of these packages are discussed 

highlighting their particular research capabilities. as well as their limitations. The comparatively low cost and ease of 

assembly/integration allow multiple "standardized" systems to be distributed for cooperative inter-laboratoty studies. 

The approach appears to have utility for both research and training. 

17. Key Words 18. Distribution Statement 

Personal Computer-Based Aviation Flight Simulation, Document is available to the public 

Simulator Research, Instrument Flight through the National Technical Information 

Psychology, Applied Psychology Service, Springfield, Virginia 22161 

19. Security Classif. (of this report) 120. Security Classif. (of this page) 121. No. of Pages 122. Price 

Unclassified Unclassified 17 

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

This is the first study of a series planned to be 

conducted as a part of the CAMI general aviation 

(GA) human factors research program. The following mission statement guides the overall effort: 

Conduct applied human factors research in the 

laboratory and in the field on carefully selected GA 

problems, to obtain objective, scientifically derived data which will aid in identifying affordable 

options for reducing the risk exposure, and number of incidents and accidents in the general aviation community, and which will serve to enhance 

GA pilot performance under non-routine flying 

conditions. 

The CAMI general av1at1on human factors 

research program is consistent with the FAA policy 

statement on general aviation, promulgated by 

the FAA Administrator in 1993, and the goals of 

the Flight Standards General Aviation Action 

Plan, distributed in 1992. Development of the 

program was coordinated with AFS-800, AFS200, AIR-2, ACE-100 and with guidance by the 

General Aviation Coalition, accident prevention 

and pilot training working groups. FAA human 

factors program management support was provided by AAR-100. 

The CAMI GA human factors research program incorporates both near-term and far-term 

objectives. The primary near-term focus of the 

program, stressed by the General Aviation Coalition, is to develop approaches to current general 

iii 

aviation problems so that payoffs in reduced risk 

exposure, accidents and incidents can be realized 

relatively soon. The long-term focus of the program is directed toward future problem solutions 

utilizing advanced technologies that require longer 

development times and more substantial funding 

commitments. These two program approaches 

are non-redundant, mutually supportive, and provide for timely human factors research on general 

aviation safety and pilot performance issues with 

payoffs distributed over time. 

This report resulted from a FY'94-95 effort to 

consider GA cockpit innovations that were affordable and would promise a more-or-less immediate enhancement of GA pilot performance. 

Mr. Thomas C. Accardi, Director, Flight Standards Service, AFS-1, sponsored the study. Mr. 

RobertA. Wright, Manager, General Aviation & 

Commercial Division, AFS-800 and Mr. Michael, 

L. Henry, AFS-80 1, provided project oversight. 

Dr. Thomas McCloy and Mr. Ronald Simmons, 

Human Factors Division (AAR-100) of the Office 

of Aviation Research, provided human factors 

program management. 

The CAMI General Aviation Research Simulation Facility, Human Factors Research Laboratory (HFRL), was used in conducting the study. 

Dr. Robert E. Blanchard is HFRL manager. Dr. 

Dennis Beringer was principal investigator, assisted by Mr. Robert Touchstone and Mr. Howard 

Harris. 
UsE oF OFF-THE-SHELF PC-BASED FLIGHT SIMULATORS 

FOR AVIATION HUMAN FACTORS RESEARCH 

INTRODUCTION 

Flight simulation for training has been available in 

one form or another for over 75 years (Edwin Link's 

trainer in 1929; a simulation in France in 1917). 

Some of the early simulators were really more on the 

order of"trainers," representing a class of devices and 

not any specific aircraft. This was certainly true of 

Link's first device, which was relatively simple and 

was assembled from readily available components 

from a number of non-aviation applications. This 

simple device ultimately gave way to more complicated and far more expensive devices as the training 

community sought to approximate more closely the 

flight dynamics and mission environments for specific aircraft (Valverde, 1968; Eichler, 1974). 

The development of the digital computer greatly 

accelerated advances in this field, and these digital 

machines now offer the opportunity for a greater 

dissemination of flight simulation than ever before 

realized. Recent developments in processor speed, 

video memory/bandwidth, and memory speed/density as well as small hard-disk drives with previously 

unheard of capacity mean that flight simulations can 

now be run on personal computers at reasonable 

update rates and with out-the-window views that 

provide a moderate level of scenic detail. The potential for applications in both research and training is 

substantial given the represented reduction in acquisition and maintenance costs and ease of use. The 

comparatively low cost of such systems may justify 

reexamination of many of the previously held beliefs 

concerning what the necessary criteria are for useful 

flight simulation. 

Given the compromises that one must accept when 

conducting flight simulation on a personal computer, 

it is of definite interest to the simulation community 

to determine empirically how some of the specific 

tradeoffs engendered in the PC-based devices may 

affect both the efficacy of training and the applicability of research results to the real world. It is, in a very 

real sense, a continuation of the discussions about 

fidelity and its effect on both simulator task performance and learning. In these continuing discussions, 

answers are still sought for: 

1) how much fidelity is needed for effective transfer 

of skills or for research data to generalize to the 

operational environment, 

2) how much of the task can be effectively represented in simulation, and 

3) how much we should pay for that box (Hopkins, 

1975). 

Although these are not new questions, the economics of simulation have changed such that we can now 

get more simulation for less capital investment. This 

requires us to ask the question, "If we can get more 

simulation for the same investment, what is the 'more' 

that we should ask for?" Simply getting "more" does 

not mean a better or more effective simulation. In 

most instances, however, the question of what more to 

ask for is not being asked because the low software 

costs and the proliferation of personal computers 

make flight simulation much more affordable and 

available. There is no perceived need to weigh the 

features against the associated costs at this level of 

simulation. The result is that low-fidelity flight simulation is being used by more people in more places 

than ever before. The economic balance point has 

shifted because of the positive cost curve acceleration 

(Figure 1) being reduced (cost: time 2), as compared 

with previous simulation costs (cost: time 1), which 

theoretically increases the expected transfer per dollar 

for the lower-fidelity systems. This constitutes the 

difference between historic discussions of flight simulation and the current weighing of the issues, where 

cost is now a facilitating, rather than a prohibiting, 

factor. Some simulation programs cost less than onehour's rental of a single-engined aircraft. The degree 
of positive transfer available for such simulations 

needs to be assessed to determine if the actual cost of 

transferring a given unit of knowledge is less in these 

simulations than in previously available ones. Transfer in the training environment can be seen, to some 

degree, as similar to generalizability in the research 

environment. Taylor (1995) reported substantive 

positive transfer from such devices to the aircraft for 

a number of maneuvers. Other recent studies indicate 

that these simulations have utility for research as well 

(Thornton, Braun, Bowers and Morgan, 1992; 

Beringer, Allen, Kozak and Young, 1993; Hennessy, 

Wise, Koonce, Smolensky and Garland, 1995). 

SPECIFIC APPLICATION: A RESEARCH 

SIMULATOR 

Over the past 30 years, much has been published 

about flight simulation for training. Although much 

less has been generated dealing specifically with research simulation, the balance of publications has 

HIGH 

AMOUNT 

OF TRANSFER / 

/ 

/ 

/ 

/ 

recently shifted in that direction. Eichler ( 197 4) made 

reference to the use of flight simulators for training 

and for engineering research and development, but 

virtually no mention of behavioral research as an 

application area. It was interesting that in their Appendix, "Examples ofSimulators," Jones and Hennessy 

(1985) devoted five pages to engineering simulators, 

seven to training simulators, but only three and a half 

to research simulators. A quick look at the state of 

things in 1993 presents a picture of considerable use 

of simulation for behavioral research. In the Proceedings of the Human Factors and Ergonomics society 

annual meeting of that year, 27 presentations referenced flight simulation. Of these, 90% used it as a 

behavioral research tool and 10% used it for performing behaviorally oriented research on simulation. 

There are a number of reasons for one to simulate 

flight rather than engage in the actual activity. Jones' 

(1967) listing of many of those justifications bears 

repetition here: 

TRANSFER 

1 Additional cost benefit 

LOW 

I 

I 

I 

I 

I 

LOW 

COST: TIME 2 

HIGH 

FIDELITY OF SIMULATION 

Figure 1. The hypothetical relationship between system fidelity and system cost (from Roscoe, 

1980; Figure 17.1) 

2 
1) Consequences of inadequate performance. This 

can be reflected in economic loss or physical injury. 

2) Cost of using actual system for training. In the 

case of commercial airlines use of an aircraft incurs 

revenue plus salaries. 

3) Hazard of using actual system for training. Avoids 

possible undesirable effects on society. Can simulate 

system failures (aircraft crashes, nuclear power plant 

foils). 

4) Availability of actual system for training. Use 

where system is not available for training (spacecraft) 

or where first performance in new system must be 

accurate (single-place aircraft). 

5) Capability of actual system to provide emergency 

training. Conditions constituting an emergency cannot be reproduced in system without great expense or 

damage to system. 

6) Requirement to integrate complex team activity. 

Integration of activities of large number of people 

(complex information assembled and reacted on 

quickly). 

7) Susceptibility of task to stress. Tasks performed 

under stressful conditions (space flight) must be learned 

to high proficiency level, usually difficult on actual 

system due to impractical nature of repeating critical 

segments. 

8) Capability to centralize training location. Reduced number of training locations using simulator 

may reduce cost and achieve standardization. 

9) Face validity of training. "Realism" of simulator 

may be necessary to assure trainee participation. 

1 0) National need. Need for specialized skills may be 

important enough to prompt federal fundingfor simulation equipment to speed training process. 

Although this listing primarily addresses training 

issues, some are applicable to research. Both cost and 

hazard are issues that clearly favor the use of simulation for flight research. The face validity issue may 

also be a factor in the attainment of generalizable 

research results, inasmuch as failure of the participant 

to ego invest in the simulated process is likely to 

negatively bias the results; responses may not be valid 

if the participant does not have to "live" with the 

consequences of actions and/or decisions. A high 

motivation to "succeed" among pilots, even when 

3 

flying simulators, may have the posmve effect of 

reducing the likelihood of unmotivated performance, 

particularly when most such simulations appear to be 

intrinsically motivating. Thus, this motivational factor may compensate, in some degree, for shortcomings in face validity if task validity is high. 

Jones and Henry (1985) point out that: 

Simulators for research differ from simulators for 

engineering design and development principally in that 

the former use has the objective of gaining generalizable 

knowledge (i.e., discovering fundamental principles 

that are broadly applicable), while the latter use is to 

obtain specific data for the design of particular items of 

equipment, systems, or procedures ... Research simulators generally must allow for greater latitude in manipulating conditions, events, and fundamental functional 

characteristics than engineering simulators. 

This is particularly evident when one contrasts, for 

example, the simulation platform needed to develop, 

evaluate, and support a specific airframe product 

(Boeing 767, forexample)with that designed for evaluating different types of manual controls and control 

systems or for examining pilot response to different 

cockpit instrumentation and display formats. The 

differences between these two types of application 

platform appear, however, to be fading in many cases. 

One of the major concerns in research simulations 

is the extent of control available, particularly over 

ambient conditions not controllable in the real world. 

It should be recalled that most behavioral research is 

reductionist in nature, rather than holistic (Egon 

Brunswik): attempting to control all variables with 

the exception of those being studied. It can be argued 

that reductionist experiments may not require a high 

degree and fidelity of flight simulation to examine 

many of the paradigms of concern given that much of 

the experimental space is represented in a steady state. 

That degree, the extent to which the full range of 

operational modes are represented, can be curtailed is 

clear, specifically when only a particular aspect of 

operation (e.g., landing) is under examination. The 

case of fidelity (the accuracy with which the system 

reproduces operational behavior) may not be as 

straightforward. The goal is to generalize from observed behavior; the extent to which that is possible is 
a function of the extent to which the operator behaves, 

in simulation, similarly to what can be observed in the 

operational environment. Evidence suggests that task 

procedural fidelity is very important for facilitating 

the desired behaviors. Events should occur in the 

expected sequence with the expected consequences. 

In contrast with procedural aspects of the task, 

some of the psychomotor aspects may be compromises and still allow adequate performance by the 

pilot. Force characteristics and gain in manual controls, for example, might be of a lesser fidelity (given 

the flexibility of the human operator) so long as they 

provided adequate input to the system for achieving 

the specified tasks. Common sense can generally dictate many fidelity decisions with some notable exceptions. It should be clear that the study of navigation 

computer interfacing with the pilot, involving graphical interface and menu hierarchy design, will not 

likely require the fidelity of manual flight control 

input/output that one would need to execute manual 

control theory studies. This selective use of high 

fidelity has been the historical exception rather than 

the rule, with many simulation efforts striving to 

achieve high fidelity across the board. Such an approach generally increases both the acquisition and 

maintenance costs of a system. 

Previous barriers to the general use of flight simulations in behavioral research largely involved these 

costs of acquisition and maintenance and system 

availability because many of the simulators had been 

developed for training or as engineering simulators 

within a full-mission context. The research community now stands to benefit from the development of 

lower-cost simulations that can reasonably represent 

selected flight tasks of interest. Such simulations have 

the promise of allowing research to be conducted, for 

a greatly reduced investment (cost foetor), that will still 

generalize to the operational environment. The opportunity then is also present to use the lower-cost 

lower-fidelity devices to perform screening experiments, reducing the resources required from higherfidelity simulations (availability foetor) and freeing 

them for more focused investigative efforts. It should 

also be noted that simpler systems tend to have higher 

reliabilities as well as lower maintenance costs. 

4 

Hardware & Software Components 

Specific constraints imposed on the present system 

development were that it (1) had to be operational 

within 6 months of project initiation, (2) had to 

reasonably represent a familiar (popular) single-engine general-aviation aircraft and its environment 

(instrumentation, controls, and external visual cues), 

and (3) needed to meet the criteria of a "research" 

simulator, to the extent that it allowed manipulation 

of experimental dependent variables of present interest and the extraction of relevant performance data. It 

was with these goals in mind that the moderatefidelity general aviation flight simulation at CAMI, 

referred to as the Basic General Aviation Research 

Simulator (BGARS) (Beringer, 1994), was developed 

using widely available 80486-based personal computers (50 & 66 MHz) to generate a comparatively rich 

simulated flight environment. The criteria oflow cost 

and short development time argued in favor of using 

commercial off-the-shelf products as much as possible. Thus, all hardware and software selected were 

available as commercial products. Minor modifications were performed in cases where components 

needed to communicate but did not already embody 

the necessary features. 

The system includes variable flight instrumentation, forward, 45- and 90-degree left external-world 

views, and a map display. Left-side external views were 

included to facilitate VFR flight and the execution of 

visually referenced left-hand traffic patterns. A simplified block functional diagram of the system appears 

in Figure 2. High-fidelity analog control inputs are 

provided (e.g., damped/self-centering yoke, high-performance throttle quadrant, gear, flap, and trim controls; radio controls). The simulation is based on 

commercially available flight simulation programs, 

one (FS-1 00) an instrument flight trainer and the 

other (A TP), a "game" -type flight simulation. The 

modified FS-1 00 package provides the cockpit displays, control input processing, continuous collection 

of 16 performance variables, choice of either a Beech 

Bonanza (A-36) or Beech Sundowner aero model, and 

concurrently feeds six-degree-of-freedom data to the 

second program, producing the out-the-windowview. 

This latter program is used to produce all outside 

views, one per processor/display combination. Thus, the 
three outside views (Figure 2) require three separate 

processors, each running a copy of the same program 

but selected to depict the appropriate viewing vector. 

The forward view is projected to obtain accommodation distances exceeding 3 meters and a 55-degree 

field of view. All interprocessor communications are 

serial, obviating any need for network hardware or 

software. Although the initial configuration used five 

processors, at an overall cost of approximately $25,000 

(hardware/software), an acceptable simulation (i.e., 

forward view and instruments) can be produced using 

only two computers; each added function/view requires another processor (Figure 2). A more detailed 

system diagram depicting the revised system using 

Pentium 100 MHz processors can be found in the 

Appendix. Included in the diagram is a sixth processor 

used to deliver ATC and pseudo pilot verbal messages 

from digitized sources. 

/ 

"' ' / 

r+ 

serial 

links 

+ 

experimeter - map display - (80486/50} 

' vi / 

' 

Software Considerations for Integration 

The simultaneous use of two previously self-contained simulation programs, each with its own internal representation of the real world, required that a 

number of issues be addressed before an acceptable 

system could be fielded. These included issues related 

to the geographic database, communications between 

programs, and the specific requirements of the research application. 

GE projected o----

CRT 

""' 

/ I' 

D to A interface 

""' 

front 

outside world 

forward view 

(80486/50} 

outside world 

left 45-deg view 

(80486/50} 

outside world 

left 90-deg view 

(80486/50} 

flight dynamics . 

and instruments 

(80486/66} 

' v 

' / 

' / 

cockpit 

proje 

""' 

ction 

scree n 

""' ""' ""' 

119" CRT I 

119" CRT I 

/ analog 

"' controls 

World Map lnstru. 

/ ' instruments 

"' / 

display 

Experimenter displays: (vga} 

Figure 2. Simplified schematic of the BGARS, version 1. 

5 
Geographic location of airports. Although the system 

intercommunications considerations were relatively 

straightforward and elegant in their simplicity, the 

architecture requires that each processor/software 

package in the system contains a geographic database 

identical with those in the other systems. One needs 

to be aware that not all databases are equal and most 

low-end flight simulations distributed for the mass 

market use the National Oceanic & Atmospheric 

Administration (NOAA) database; it is readily available for minimal cost and does not require licensing 

for use. Some of the more expensive instrument training packages use the Jeppeson-Sanderson Q-S) database. This commercial product is expensive and 

requires licensing, but its data are updated very frequently. The two databases are not congruent; indeed 

we have found displacements orthogonal to runway 

centerlines ranging from 50 to 200 feet. This can be 

most unnerving when one flies a "perfect" Instrument-Landing-System (ILS) approach and finds, on 

short final, that the aircraft is not aligned with the 

runway. We have obtained editing functions for the 

package (ATP) using the NOAA database, allowing us 

to move the airports into alignment with the J-S database. In most cases, the adjustment required is small. 

A related concern is the fidelity with which airport 

facilities are represented. We regularly found discrepancies between the representation of an airport in the 

instrument-package database (and thus moving map 

display) and the depiction in the out-the-window 

scene. Secondary runways were missing from the outthe-window view in a number of instances. This 

appeared to be more likely at "secondary" airports as 

primary airports generally had accurate runway and 

taxi way depictions. It is not clear to what extent these 

discrepancies represent changes in the facilities requiring updating of the database and to what extent 

they are simply omissions. Thus, it is recommended 

that one not choose airports as primary or secondary 

destinations (or even emergency fields) without fully 

assessing the agreement between the two databases. 

Altitude. Differences in field elevation, however, 

are a more difficult problem. Each software package 

represents altitude in a different fashion. FS-1 00 

assumes terrain elevation to be that of the nearest 

airport. A TP uses an interpolative approach to deter6 

mining altitudes at locations falling between major 

reference points to approximate intermediate terrain 

elevations. Add to this small differences (50-1 00 feet) 

between the two source databases and the result is 

some interesting anomalies. We found an initial difference between databases of 50 feet at Will Rogers 

World Airport (OKC, runway 35 right), which occasioned a rather high and sudden contact with the 

ground on our first simulated approach (it was literally a highway in the sky), the field elevation in the 

visual scene database being lower than the field elevation in the instrument package database. Although 

ATP can make an initial adjustment on start-up to the 

current field elevation, differences at the destination 

of a flight can still produce the aforementioned effect. 

This problem was resolved by transmitting altitude 

above ground level (AGL) to the scene-generating 

packages. Flying over mountains represented in the 

visual database does not produce unusual effects, 

because FS-1 00 is not aware of the mountains if no 

airport is located there, and A TP uses the base of the 

slope as terrain elevation. 

Heading. One other concern is the method by 

which heading, also represented as the forward viewing vector, is communicated between packages. Recall 

that heading has both true and magnetic representations and that both simulation packages must agree on 

the method for handling and communicating those 

data. An early experience during development was, 

again, a distressing one on approach to San Francisco 

(SFO) when all attempts to fly straight down the 

runway produced extreme drift to the right. Mismatches regarding true and magnetic headings and a 

difference in the internal representations of data between the two software packages contributed to this 

effect. Processing of transmitted heading was modified to correct this mismatch. 

Collision with ground or objects. The enabling of 

collision detection has two levels. The first, already 

mentioned, requires that both packages operate from 

the same basic data. Compatibility is critical for a 

multimachine one-way communication environment 

because no handshaking or flow control is being 

executed; one machine is the transmitting "host" 

while the others are passive listeners (peripherals). 

The second level, object collisions, can be achieved by 
having the forward-view-generating processor determine, as the software is capable of doing, if an object 

in the visual scene has been struck and then send a 

signal back to the host. This would require only two 

processors to have full duplex operation, with the 

other machines remaining passive monitors of one 

side of the communications flow. 

Visual display considerations regarding color, brightness, and aliasing. Not all software packages present 

visual data in the same manner. The temptation exists 

to opt for the highest-resolution out-the-window 

imaging available in order to reduce aliasing along the 

horizon line and on any other features with linear 

boundaries. FSS (in VGA graphics mode), with its 

textured terrain depiction, does exhibit less aliasing 

than does ATP (in EGA graphics mode) as a function 

of the display resolution being used. However, FSS 

tends to have a much darker overall affect with its 

textures than does ATP with its uniform area-fill color 

(primarily light green or brown with occasional yellow or orange blocks). While this may not be of much 

concern when displayed on a large direct-view CRT, 

the brightness issue becomes critical when a projection system is used. The image produced by the GE 

projection CRT was of an acceptable level of brightness when the backgrounds were area filled and primarily light green or light gray (urban), but the brightness 

was not acceptable in the initial adaptation ofFSS and 

terrain features and runways were difficult to detect. 

A subsequent modification was made to brighten all 

of the colors, but the effect was to wash out much of 

the contrast and lose some of the definition. Some 

additional tuning of brightness and contrast may 

resolve this problem. Detection of runways and runway centerlines was also more difficult at a distance 

with the textured-terrain display provided by FSS 

than with the simpler area-fill graphics of ATP. This 

may or may not be desired, depending upon the tasks 

to be performed. 

Required modifications for research. Two modifications were required to make the system suitable for 

research. These were to provide (1) the ability to 

manipulate the independent variables of interest and 

(2) the ability to record dependent variables of interest. The first two studies required selectable inst~umentation, as we were interested in piloting 

7 

performance with both conventional navigation displays, as represented by the very-high-frequency omni 

range (VOR) indicator and directional gyro (DG), 

and integrated displays, as represented by the horizontal situation indicator (HSI). Additionally, we were 

interested in the effects of simple memory aids/instrument bugs. The HSI was already available in the 

software; the modification allowed selection/ deletion 

of bugs on the DG and altimeter. Thus, requirements 

of (1) were satisfied. Meeting the requirements of (2) 

was facilitated by the fact that most of the dependent 

variables ofinterestwere already being recorded in the 

replay memory. This required only the addition of a 

header record to identify the data file, a sample number for each data slice, an event marker that could be 

inserted by the experimenter in real time from the 

keyboard, and lateral error, in feet, from the VOR/ 

localizer course (for a total of 16 variables). An additional switch was added to allow data collection to be 

paused during a run while the aircraft continued to 

fly. A package was also provided that allows data files 

to be accessed and rewritten in ASCII format for 

subsequent use by data reduction and analysis packages. 

Flight task difficulty/aero models. The original aero 

model provided was a Beech BonanzaA-36. This was 

used in the initial evaluation with instructor pilots 

and was found to be too sensitive to control inputs 

and somewhat unstable longitudinally. It did, however, provide a significant challenge to the participating pilots, and thus, a good task loading that was likely 

to exercise the pilot and system in such a way as to 

expose effects due to the experimental manipulations 

being used. A simplex (single-engine, fixed-pitch prop, 

fixed gear) model was desired for use with the private 

pilot samples to be examined and a Beech Sundowner 

model was added. Its flying characteristics were quite 

similar to the actual aircraft, and pilots without complex 

aircraft experience found it comparatively easy to fly. 

Update rates and throughput. The initial installation of the system used 80486 processors for the flight 

instruments/aero model package (66 MHz) and outthe-window views (33 MHz). Different update rates 

were obtained for the instrument package and the 

external views. The instrument panel updates were 

generally on the order of 12 to 16Hz. The out-thewindow views involved much more in the way of 
graphics and generally did not operate much faster 

than 6 to 10 Hz. This update rate was not objectionable for most operations and only became noticeable 

in steep-banked turns. The upgrading of the system to 

100 MHz Pentium processors with the PCI bus for all 

computers excepting the map display (486 66MHz) 

after conclusion of this study significantly increased 

throughput. Instrument and all out-the-window view 

update rates appear to be at or above 16 Hz. Some 

occasional stepping (discrete observable movements) 

can be observed in instrument indications, particularly in the CDI needle, but this appears to be a 

function of calculational and display-resolution artifacts and not system throughput. 

Advantages 

The advantages of this approach are (1) low cost of 

hardware, often already available on site, (2) comparatively low cost of software, as modifications were 

minor, as compared with development of a completely customized system, (3) modularity of both 

hardware and software, allowing upgrade of any of the 

components or easy expansion of simulation by adding components, and (4) simplicity of the communications protocol. The low cost and ease of assembly/ 

integration allow multiple "standardized" systems to 

be distributed for cooperative inter-laboratory studies. This approach appears to have great utility for 

both research and training. 

Disadvantages 

One should expect that the advantages noted do 

not come without cost. The use of commercial offthe-shelf software without access to the source code 

poses a potential problem for investigators who wish 

to manipulate variables not directly accessible through 

the program. Although we have had reasonable success in working with the developers of the software to 

obtain modifications necessary to make the simulation useful for research, there are yet some areas where 

desired modifications are not immediately obtainable. This is due either to scheduling conflicts in 

securing development time or to changes that have 

major impact on the structure of the software. One 

solution to the problem that we have pursued is the 

8 

addition of processors on the serial distribution to 

provide additional features (i.e., ATC and pseudo 

pilot digitized and automated voice inputs). The 

researcher then maintains control of the auxiliary 

functions and can modifY and develop the code as 

needed. This approach can also be used to develop 

auxiliary instrument displays, given that the requisite 

data are available on some communication line coming from the host processor. Additional modifications 

are being made to the software that will provide access 

to more data variables in real time as well as to some 

discrete failure modes, multiplying the options available to the experimenter. 

EMPIRICAL VALIDATION 

Having now fielded a functioning system, it was 

necessary to validate the utility of this system for 

research. A problem area was selected during development, as previously mentioned, that would allow 

experimental outcomes to be compared with outcomes of other aircraft- and simulator-based research 

for at least a preliminary empirical validation of the 

BGARS as a research tool. 

Problem 

The selected comparisons were (1) between alternate ways of presenting course deviation information 

for very-high-frequency omni range (VOR) navigation and (2) between instrument formats both with 

and without short-term memory aids. The Horizontal 

Situation Indicator (HSI) has seen considerable use 

and combines the functions of the very-high-frequencyomni range (VOR) and directional gyro (DG) 

indicators within a single instrument (a design suggested by Walter Grether; Williams, 1949, as reprinted in Roscoe, 1971). There has been little doubt 

that the HSI simplifies the pilot's task of integrating 

the various pieces of data, with some attendant gains 

in the performance of tracking and orientation tasks. 

Short-term memory aids or "bugs" are available to 

relieve the pilot of the tasks of recalling target altitudes 

and headings. It was anticipated that the aided (HSI 

and bugs) conditions would produce performance 

superior to that obtained in the unaided (VOR/DG 

and no bugs) conditions. 
The question at hand was one of cost effectiveness: 

Did performance enhancements associated with the 

HSI and bugs justify the expense of acquiring and 

installing such devices in comparatively inexpensive 

general aviation aircraft? The questions relative to the 

simulation were several, involving (1) sufficient task 

fidelity to motivate generalizable behavior, (2) ability 

of the system to collect adequate continuous, realtime performance data, and (3) stimulation of the 

same types of procedural errors as those seen in the 

operational environment through appropriate task 

and workload representation. The reliability/availability of such a system was also of interest as compared with other such devices. A brief summary will be 

presented to address these questions. 

Task Fidelity and Generalizability 

More than 36 pilots flew the simulation over the 

course of three phases of the initial study. Of these 

individuals, 12 were experienced pilots (with more 

than 500 hours, of which at least 30 hours were logged 

in the last 6 months), most of whom were instructors, 

with the remainder being private pilots (with less than 

200 hours of flight time and less than 20 hours in the 

last 6 months). Each participant flew the simulator for 

two 2-hour sessions, the first session for familiarization and training and the second for data collection. 

Training included traffic patterns, constant-altitude 

standard-rate turns, VOR radial interception and 

tracking, and a simple positive-control scenario that 

incorporated all previous components. The subsequent data collection consisted of more challenging 

VOR navigation courses and compliance with ATCissued vectors and altitude changes as well as an ILS 

approach. 

Pilot subjective reports were collected using posttest 

questionnaires. Comments and ratings concerning 

handling qualities and workload consistently indicated that pilots judged the A-36 simulation to be 

more sensitive to control inputs and more difficult to 

fly than the aircraft. These assessments, however, 

appeared to correlate with piloting style (i.e., interventionist versus noninterventionist). Ratings on the 

flying qualities of the Sundowner were also to the 

"sensitive" side, but not to the degree found for the 

Bonanza. 

9 

Pilots generally reported that the experimental scenarios were more challenging than their usual flying 

and thus, presented a significant workload. This, of 

course, was a positive bit of news, as the intent was to 

load the pilots sufficiently to detect performance 

decrements. Obtained ratings also indicated that participants felt the simulation reasonably represented 

flight tasks in the ATC environment. Ratings were all 

high on the "task realism" scale. A number of individuals expressed the desire to spend additional time 

in the simulator and several instructors indicated their 

interest in using such a system for training. Behaviors 

observed during the flights also indicated that the 

participants were ego involved in the process and were 

responding to the simulated flight much as one would 

expect them to respond during an actual flight. This 

was true of continuous aircraft control, radio navigation, and communications with ATC. 

Continuous Real-time Performance Data 

Flight data were sampled and stored at 0.5 Hz. 

Variables recorded included latitude, longitude, magnetic variation, altitude, airspeed, heading, crosstrack error, DME indication, and a number of status 

variables (event mark, gear, flaps, marker beacons, 

etc.). Examination of the data suggests that performance variables that can be sampled at lower frequencies (2 Hz or less) and that represent outcome states 

(i.e., location of the aircraft in three dimensions 

relative to desired altitude and ground track) can be 

effectively monitored with the system and provide 

adequate measures of aircraft system performance for 

navigation and altitude maintenance tasks. Examples 

are shown in Figures 3A & B where the plan views are 

shown for one pilot to compare the HSI course tracking with the VOR/DG course tracking. It is evident 

that better acquisition and tracking performance was 

obtained using the HSI, consistent with the procedural data previously mentioned and with previous 

studies of integrated navigational displays. 

Higher sampling frequencies up to at least 16Hz 

are possible with the system, but storage becomes a 

problem as variables are held in memory until the end 

of a flight. The present system could be suitable for 

control-theory studies of manual flight control where 

the expected frequency of control reversal activity is 
(A) VORIDG (B) HSI 

Figure 3. Example flight paths for one subject for (A) VOR/DG and (B) HSI 

instrumentation. Dotted lines indicate desired tracks. 

not likely to exceed the measurement capabilities of 

the system during most normal realms of flight. The 

limitation, as suggested, is more one of available data 

storage space, limiting the duration ofhigh-frequency 

data collection. Flight attitude data are presently 

being transmitted from the program at 16 Hz, so 

evaluation of maneuvers based upon sampling of 

aircraft attitude can apparently be accommodated, 

although such were not evaluated in the present study. 

A revision of the software is presently under way that 

would allow flight data to be transmitted to another 

computer system, thereby alleviating the storage space 

restriction and increasing the recordable flight durations even at high sampling rates. 

Observed Procedural Errors 

Two categories of procedural/ discrete errors were 

expected to be observed related either to the navigation/orientation problem or those related to memory 

of heading and altitudes or elements of the verbally 

issued clearance amendments. Navigation/orientation errors included inappropriate setting of the omni 

bearing selector (OBS), flying through radials without any corrective action, and turning in the wrong 

direction for an intercept. Memory errors included 

callbacks for heading, altitude, or radial, and failure to 

recall present assigned altitude. Errors observed for 

the experienced pilot sample are summarized in Table 1. 

10 

These findings ~ere largely as anticipated, demonstrating more errors with the VOR/DG combination 

and without bugs than with the HSI and bugs. The 

direction and frequency are largely consistent with 

other research in the display aiding/predigestion literature. This suggests that the simulation system can 

be useful for examining problems of this nature where 

procedural compliance and navigational decisionmaking are involved and information is being derived 

from a dynamic instrument representation. 

Reliability and Ease of Use 

The system, as of this writing, had been operated 

for over 880 hours (over the course of 18 months). 

During this time, only two failures occurred that 

required the halting of data collection. Both of these 

were microprocessor-system related, one being a disk 

controller failure. One transient failure of the GE 

projection system was observed, but it did not interfere with data collection. No failures of the custom 

hardware were observed. The audio system amplifier 

experienced one failure but was immediately replaced 

by on-site available equipment, as was the case with 

other components. Maintenance of the system can 

generally be performed on site by individuals with a 

knowledge of personal computer systems. The system 

is very easy to use, as all programs are run automatically following initial system boot using batch files 
Table 1. Procedural errors, 11 subjects. 

VOR/DG HSI 

Error No Bugs Bugs No Bugs Bugs 

VOR!Nav 17 12 

Memory 5 4 

Total 22 16 

and all operator-software interfaces are straightforward and easy to understand. A cold start of the system 

(from power off to full operational status) requires 

approximately one minute. 

CONCLUSIONS 

The data obtained to this point indicate that the 

simulation described herein has sufficient task fidelity 

to motivate generalizable behavior, producing outcomes that are comparable to those obtained in other 

simulation devices and, in fact, aircraft. The ability of 

the system to collect adequate continuous, real-time 

performance data has been demonstrated with reference to tasks limited to maintaining aircraft altitude 

and track. Control theoretic studies are likely to 

require some modifications of the software to provide 

sampling rates of sufficiently high frequency. It was 

also evident that the task environment simulated was 

sufficient to the degree that behaviors/errors likely to 

be observed in the real world were also observable in 

the simulation, allowing for the examination of procedural error, as well as continuous performance. The 

simulation has been comparatively inexpensive to 

integrate and maintain, and has had a very high level 

of availability. 

The preliminary indications are that this modular 

microprocessor-based flight simulation system can be 

a useful and economical tool for examining experimental questions involving general aviation pilotage. 

No data are as yet available for the use of this tool in 

investigating tasks that are primarily VFR in nature. 

11 

6 8 

5 1 

11 9 

Software (textured visual databases) and hardware 

(1 00 MHz and faster processors and faster bus architectures) developments are becoming available that 

will further enhance the possibilities for research on 

visually guided behaviors beyond geographical orientation, pattern flying, and visually guided approaches. 

REFERENCES 

Beringer, D. B., Allen, R. C., Kozak, K. A. and Young, 

G. E. (1993). Responses of pilots and non pilots to 

color-coded altitude information in a cockpit display of traffic information. Proceeding.r of the 37th 

annual meeting ofthe Human Factors and Ergonomics Society, 84-87. 

Beringer, D. B. (1994). Issues in using off-the-shelfPCbased flight simulation for research and training: 

historical perspective, current solutions and emerging technologies. Proceedings of the 38th annual 

meeting oft he Human Factors and Ergonomics Society, 

90-94. 

Eichler, J. (197 4). A survey of flight simulators. Chapter 

2 in Paul Brock (ed.), Spanning the applications of 

simulation, Simulation councils proceedings series, 

Vol 4, No.2. La Jolla, CA: The Society for Computer Simulation. 

Hennessy, L. W., Wise,J. A. and Koonce,]. M. (1995). 

The effects of a pathway-in-the-sky display on the 

performance of a two-axis tracking task by instrument-rated pilots. Proceedings of the Eighth International Symposium on Aviation Psychology, 

Columbus, OH, 1073-1077. 
Hopkins, C. 0. (1975). How much should you pay for 

that box? Human Factors, 11(6), 533-541. 

Jones, E. R. Professional paper. Simulation Applied to 

Education. McDonnell Company, April 1967. 

Jones, E. R. and Hennessy, R. T. (eds.) (1985). Human 

Factors Aspects of Simulation. Washington, DC: 

National Academy Press. 

Roscoe, S. N. (1980). Transfer and cost effectiveness of 

ground-based flight trainers. Chapter 17 in Aviation Psychology, Iowa State University Press, 194-

203. 

Taylor, H. L., Lintern, G., Hulin, C. L., Emanuel, T. 

W., Phillips, S. I. and Talleur, D. A. (1995). The 

transfer of training effectiveness of personal computer-based aviation training devices. Proceedings 

of the Eighth International Symposium on Aviation 

Psychology, Columbus, OH, 1210-1215. 

Thornton, C., Braun, C., Bowers, C. and Morgan, B. 

( 1992). Automation effects in the cockpit: A lowfidelity investigation. Proceedings of the 36th annual meeting of the Human Factors Society, 30-34. 

Valverde, H. H. Flight simulators - a review of the 

research and development. Wright Patterson Aerospace Medical Research Laboratory Technical Report 

No. 68-97, July 1968. 

Williams, A. C. (1947) Suggestions concerning desirable display characteristics for aircraft instruments. 

Interim ReportSDC 71-16-4,July 1949; reprinted 

in S. N. Roscoe (ed.), Aviation Research Monographs, 1(1), July 1971, U. of Illinois Institute of 

Aviation. 

12 
APPENDIX A 

GE projected J ---------

CRT ~ front ~ projection D to A interface ~ 

~ screen 

/ I ~ " outside world ~ 

~ forward view ~ 

7 (100 MHz Pentium) ~ 

serial ~ 

links "---

outside world (RS-232) ~ left 45-deg view ' / 119" CR~ ' 

/ 

(100 MHz Pentium) 

a~ ATC/pseudopilot 

~ [)1 voice generation r/ outside world r- (100 MHz 80486) ' left 90-deg view / 

(100 MHz Pentium) 119" CR~ Environmental 

Sounds 

experimeter flight dynamics audio 

map display ' and instruments / / 

r--'\ (66 MHz 80486) / " serial (RS-232) " (100 MHz Pentium) 

~ E 

~ + Copilot's 

Pilot's cockpit 

instruments / ' ...... World Map ~ Display f-7- Instruments display 

/ distribution (vga) 

\V 

DME 

llanalog ;~ Avionics ATC 

jmonitorl ~ monitor 

' lnstru. ~ videotape controls controls 

/ scripts stamp) l transponder 

~ Experimenter di:"lays 

video f--1 vi~eo I recorder video 

" m1xer v 

audio OUT / 

-system ' r-"- / 

~ E /I'IN/f' audio 

'--

digital VO 

Figure 1A. CAMI BGARS schematic diagram, 6-processor configuration. 

*U.S. GOVERNMENT PRIN11NG OFFICE: 19M -7~ 

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