NBSIR 73-422

A Study of Air Traffic Data

Requirements and Sources for

FAA Analyses

William F. Druckenbrod

Judith F. Gilsinn

Richard H. F. Jackson

Lambert S. Joel Tao K. Ming

Technical Analysis and Applied Mathematics Division

National Bureau of Standards

Washington, D. C. 20234

May 1974

U. S. DEPARTMENT OF COMMERCE

NATIONAL BUREAU OF STANDARDS

NBSIR 73-422

A STUDY OF AIR TRAFFIC DATA

REQUIREMENTS AND SOURCES FOR

FAA ANALYSES

William F. Druckenbrod

Judith F. Gilsinn

Richard H. F. Jackson

Lambert S. Joel Tao K.Ming

Technical Analysis and Applied Mathematics Division

National Bureau of Standards

Washington, D. C. 20234

May 1974

U. S. DEPARTMENT OF COMMERCE, Frederick B. Dent, Secretary

NATIONAL fiU<fSAU OF STANDARDS. Richard W. Roberts. Director

TABLE OF CONTENTS

Page

1.0 Purpose and Overview 1 2.0 Introduction 1

3.0 Data Requirements . 2 3.1 Users , 2

3 . 2 Data Required 7 3.2.1 Terminal Area Data 7 3.2.2 En Route Data 8 3.2.3 Oceanic Data 8 3.2.4 Requirements Matrices (Table 1) 9 3.2.5 Non-Traffic Data 9

4.0 Data Sources 9 4.1 Existing Sources 9 4.2 Requirements-Sources Matrix (RSM) , Table 2 15

4.3 Data Not Now Available from Continuing FAA Data Collection

Efforts 24

4.3.1 Why Are Data on VFR Flights Needed? 25

4.3.2 Forecasting VFR Traffic 26

5.0 Data Sets To Satisfy User Requirements 27

5.1 Terminal Data Set - Type 1 28

5.1.1 Description 28

5.1.2 Source 29

5.1.3 Forecasting 30

5.1.4 Potential Users 31

5.2 Terminal Data Set - Type 2 32

5.2.1 Description 32

5.2.2 Sources 32

5.2.3 Forecasting 33

5.2.4 Potential Users 33

5.3 En Route Data Set - Type 1 34

5.3.1 Description 34

5.3.2 Sources 35

5.3.3 Forecasting 35

5.3.4 Potential Users 36

5.4 En Route Data Set - Type 2 36

5.4.1 Description . . 36

5.4.2 Sources 37

5.4.3 Forecasting 37

5.4.4 Potential Users 37

5.5 Oceanic Data Set 38

5.5.1 Description 38

5.5.2 Sources , . . . . 38

5.5.3 Forecasting 38

5.5.4 Potential Users 39

i
TABLE OF CONTENTS (Continued)

Page

6.0 Findings and Reconunendations 39

Appendix A . . ' 42

References 46

Glossary 47

LIST OF TABLES

Table 1. Requirements Matrices 10

Table 2. Requirements - Sources Matrix 16

" ' ' LIST OF FIGURES

Figure A.l. Data Flows in the NAS Stage A System 43

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ii
1.0 PURPOSE AND OVERVIEW

This report describes activities undertaken by the National Bureau of Standards

(Technical Analysis and Applied Mathematics Divisions) on behalf of the Federal

Aviation Administration (FAA) * to assess the practicability of establishing a single

file or a set of files of standard reference air traffic data samples, and to specify

the characteristics of such files as might be feasibly constructed. These prospective

files would, in concept, serve as a common data base for ongoing and (anticipated

future) forecast and analytical investigations relevant to the accommodation of air

traffic in the National Airspace System (NAS)

.

It is well known that existing traffic data are not at all complete, if only

because of huge gaps in information about VFR operations. Consequently, basic

interest was focussed on the extent to which current, accessible data satisfy analytical

and forecast needs, the extent to which existing raw data in diverse collections could

be brought into user-accessible files and, if the shortfall were substantial, the

magnitude of the task of redressing it.

The study entailed surveys of past and present air traffic data collection

activities, of existing data files and of all identifiable users of air traffic data

(i.e., groups within FAA and those of its contractors whose work requires air traffic

data as input). In the present context, "survey" comprises a spectrum of actions:

literature search, perusal of reports and manuals, examination of file specifications

and data listings, visits to operational and research facilities, and several rounds

of interviews with data collectors and data users. Information produced by the surveys was structured into tables based on definitions

of data types, uses and availability, then analyzed. In brief, the analysis leads to

the conclusion that, with some intensification of current data recording procedures,

a moderately comprehensive data base can be created and organized in five data files,

split into three groups categorized according to the flight operations under primary

consideration: terminal, "CONUS" enroute, and oceanic. Guidelines were developed

for identifying and treating a hierarchy of critical priorities in data requirements,

data collection and processing, and redefinition and reduction (or, in some cases,

expansion) of user data requirements. Estimates were made of the resources required

for producing a data base which would satisfy user needs for all anticipated flight

conditions. . .

2.0 INTRODUCTION

In addition to being charged with day by day management and operation of the

National Airspace System, the FAA is also responsible for the development of improved

systems and procedures required to keep the system responsive to changing aviation

user needs. In the course of developing and validating these system and procedural

improvements, analytical studies which require air traffic situation data as inputs

are conducted by FAA in-house groups and by outside contract groups. Over the years

the FAA and its predecessor organizations have collected and continue to collect a considerable volume of air traffic activity data, but these data in their present

form are not usually suitable for direct use in the analysis of air traffic situations.

Consequently, those who carry out various analytical studies must manipulate the

existing air traffic activity data into those traffic-describing formats which best

fit their particular requirements. As a result, two independent research groups

working on the same air traffic situation problem may base their studies on two quite

different sets of data, each group employing its own assumptions to define its representation of that traffic situation. This can tend to reduce confidence in analytical

results, and it precludes valid comparisons of independent efforts or approaches in

investigating the same problem. For example, there have been cases where two

contractors worked in parallel on a common problem, taking different approaches. Each

analysis produced results demonstrating that its approach was reasonable. However,

if the different assumptions and associated air traffic descriptions were interchanged,

neither analysis would show satisfactory results. Such difficulties illustrate the

need for standard air traffic sample reference data usable by most investigators.

This study explores the feasibility of satisfying that need.

A list of mnemonics and abbreviations used in this report appears in the Glossary

on p. 47.

1
The traffic samples required for these studies can be catalogued under three broad

data structure classes: tracks, snapshots and activity summaries. A track is a complete flight history (in time and space) of an aircraft, usually recorded at

intervals of about 4 seconds (the sweep rate for most commonly used FAA radar). A

snapshot is an instantaneous status report on all tracks in some portion of airspace.

(Snapshots normally include instantaneous speed and direction, which are obviously

unnecessary for tracks. Both tracks and snapshots might include altitudes, profile

information, meteorological and other "external" data.) Activity summaries are aggregates of the type found in annual activity reports, but possibly tailored for

particular studies with additional time and geographical details (e.g., "hourly

activity by a/c class over the northeastern U.S. in blocks 10 nautical miles square

X ft. altitude layers").

It is clear that some studies, say of handoffs in ATC, may require a small set

of tracks, and that neither snapshots nor aggregates, no matter how extensive or detailed, would be very useful. On the other hand, analyzing traffic "clutter" requires

snapshots; detailed single tracks or exhaustive summaries (unless very fine-grained)

would not suffice. For estimating various levels of manpower and equipment requirements,

only large numbers of tracks or snapshots over time, i.e., good summary statistics,

arc appropriate.

Data sample requirements can also be structurally differentiated by the "typicality" relevant to a particular study. Some analyses require "typical" data, while others

refer only to "critical" data, such as various kinds of peak traffic (or in one ongoing

CAS study, low activity periods) . "Typical" may range from specifying averaged data to

deletion of statistical outliers (e.g., peaks). In statistical terms, the distinction

is analogous to representations of "mean", "median" and "mode". In some instances the

probabilities of occurrence of various traffic situations may be required inputs.

For this study, data requirements were explored initially in meetings with all

identifiable FAA in-house groups engaged in analytical efforts requiring air traffic

situation data. Meetings were also held with FAA contract groups who are doing (and are expected to continue) similar support analyses. The purpose of these meetings was

to gather information on the groups' current and anticipated requirements for present

and future air traffic data. Their requirements, in fact, include not only air traffic

data per se , but also other relevant information on topics such as aircraft performance

characteristics, airborne equipment, and routing. In addition to meeting with the

data using groups, the study staff met with FAA personnel from Management Services and

the Office of Aviation Economics in order to obtain a thorough understanding and

knowledge of existing FAA air traffic data sources and forecasting procedures.

The information obtained from these direct contacts was evaluated and aggregated

to identify data which will satisfy most of the requirements expressed by the data

users. Two data sets were specified for terminal area requirements, two sets for en route requirements, and one set for oceanic requirements. These data sets will not

satisfy all input requirements for all anticipated analysis efforts. Depending on the

type of study, supplemental information will be required in some cases and is identified in various parts of this report. To avoid possible misunderstanding, we emphasize that the purpose of this analysis was not (nor is it an appropriate goal) to

develop data or traffic sample models which can be used as direct inputs to analyses.

The analyst who uses standard data sets must design an air traffic data model to fit

his specific problem or method of analysis. The intent here is to provide common

data and sources to be used by all analysts as a consistent basis for and input to

any special-purpose traffic situation descriptions.

3.0 DATA REQUIREMENTS

3 . 1 Users

In order to identify FAA traffic data requirements the NBS project staff discussed

with FAA and contractor personnel various current and projected programs which might

utilize air traffic situation data. Several of these programs are described below.

The list includes all known types of analyses which will be required by the agency in

the next few years, although some specific efforts may have been omitted.

2

/
Micro-Wave Landing System (MLS)

A micro-wave landing system (MLS) is being developed as a possible replacement to

the present conventional instrument landing system (ILS) . The MLS is being designed

to provide more precise heading and altitude information in the cockpit; should permit

all-weather operations with greater safety; would allow curved approaches and a flexible

glide slope angle; and might permit simultaneous IFR approaches to parallel runways

at lesser separations than are now required. Studies of the performance of proposed

or prototype MLS systems, relative to these goals, are anticipated. Current MLS

studies are aimed at ensuring that particular systems meet technical performance

specifications, and thus do not require traffic data. However, such data will be

necessary in order to evaluate the operational effectiveness and safety of an MLS

system, how the curved approaches and variable glide slope angle operate in the ATC

environment and how these capabilities can best be exploited, and whether the system

will permit safe conduct of simultaneous IFR approaches to close parallel runways.

Ground Guidance

As the system of airport runways and taxiways becomes larger and more complex,

safe and effective control and guidance of aircraft on the ground, particularly under

conditions of poor visibility, become increasingly difficult. Several different systems

are being considered to accomplish this function and it will be necessary to evaluate

their effectiveness under different traffic situations.

Frequency Spectrum

Frequencies in the vhf spectrum, currently separated at 100 and 50 kHz intervals

are assigned to control positions in ATC facilities for voice communications. Similar

frequencies are also assigned to various surveillance and navigation activities. As

air traffic activity increases and additional ATC facilities are established, the

frequencies now available for assignment will no longer accommodate the demand by all

aviation users. Since the probability of additional frequencies being allocated to

the ATC system is low, it might be possible to increase the number of available

frequencies by reducing frequency separation in the presently allocated spectrum. If

such a reduction is to be implemented, care must be taken in the reassignment of

frequencies to control positions and other functions, since frequency protection from

neighboring facilities must be maintained. Thus it is necessary to evaluate the

magnitude of the demand as a function of expected traffic levels, to be able to assess how soon and where frequency shortages will become acute and to analyze and

plan any change in frequency reassignment before the situation becomes critical.

STOL

Short takeoff and landing (STOL) vehicles may be introduced into the civil air

fleet at some time late in the decade. Special STOL-ports may be built near city

centers so that STOL passengers can be delivered closer to their ultimate destinations

than they are with today's airport system. STOL aircraft may also be expected to use existing airport facilities, either sharing runways with conventional aircraft or,

most likely, using special STOL runways. Since STOL vehicle landing and takeoff

characteristics (speed and flight profile) are significantly different from those of

conventional aircraft, it is necessary to analyze the interaction of the two types of

aircraft in the common terminal area. Wake Turbulence

Wake turbulance, the disturbance of the air behind a heavy aircraft, particularly

at and immediately prior to touchdown or lift off, has become a more severe safety

problem since the introduction of the jumbo jets (B747, DCIO, LlOll) . As a result,

increased separation (5 mi.*) of aircraft following a large jet is required. As better

(more accurate) means of terminal navigation and surveillance are developed, it may

well be that wake turbulence will be the major constraint in determining minimum safe

separation distances between aircraft. Traffic data will be required in the evaluation

of increased separation requirements and other rules changes caused by wake turbulence

problems

.

Nautical miles.

3
Pollution

As air pollution in our cities becomes more critical, airports may have to limit

or curtail operations during pollution alerts. Although some experts have expressed

the opinion that the contribution of aircraft toward severe pollution is slight, many

local jurisdictions are considering the possibility of curtailing aircraft operations,

for they are more easily controlled than other pollutant sources and their pollution

is more visible. A second type of aircraft pollution has also come to the fore, namely

noise pollution. Noise abatement procedures have been instituted at several large

airports, approach and departure routes and altitudes being specified and reduced

engine power prescribed in order to minimize noise and to concentrate it in areas affecting the smallest population. To assess the effect of aircraft-caused pollution

on the near-airport population and to evaluate means of reducing it (with regard to

the degree of reduction and also to the economic impact of curtailed operations) , it

is necessary to have air traffic data.

Before and After ARTS III and NAS Stage A

The FAA is currently completing the installation of ARTS III equipment at large

and medium hub airports and of NAS Stage A in ARTCC's,in order to automate some air

traffic control functions. To evaluate these systems ability to provide increased

controller workload capacity and/or additional operational safety, it is necessary to

compare controller activities and aircraft operations before the equipment is operational with those after it has been in use for several months. This effort requires

traffic data for these two time periods.

Capacity

Traffic congestion and accompanying delays are being experienced at some of the

highest activity terminals, and in a few cases restrictions have been placed on the

acceptance of IFR traffic. The increased use of wide-bodied jets by the air carriers

will delay the onset of system saturation only a short time, and may in fact be

offset by the increasing volume of general aviation IFR traffic. The terminal area

is the critical point with respect to the capacity of the ATC system. However, it

should be noted that not all terminals are heavily congested, and that most terminals

which experience backups during peak hours have excess capacity at other times. Thus

estimates of future traffic levels are needed to assess the magnitude of the problem

of restricted capacity, to evaluate its consequences, and to investigate methods of

relieving the situation.

Although the most critical part of the ATC system is the terminal area, it is

necessary as well to study the capacity of the en route system, both to ascertain

what residual capacity is available and to identify points in the system which are

near saturation. It is also necessary to evaluate the effects of possible route and

procedure changes on the capacity of the system. Capacity of the en route ATC

system may be defined in two ways: one involving the physical capacity of the

airways structure under current separation procedures and the second related to the

workload capacity of controllers under current staffing and sectorization levels.

Studies utilizing both concepts are needed, but the second clearly addresses the more

critical situation.

General Aviation (GA)

Most of the traffic data regularly collected by the FAA concerns IFR traffic,

traffic handled by FAA air traffic control facilities, or traffic which files flight

plans. The bulk of general aviation (GA) traffic flies VFR, is out of and into nontower airports, and does not file a flight plan. Its main contact with the FAA

system is through Flight Service Station (FSS) activities such as pilot advisories

and briefings. However, it is virtually impossible to relate such FSS activity

directly to GA traffic volume and activity. The only data collected by the FAA which

include all of GA are concerned with aircraft (the aircraft registration data) and

airmen (pilot licenses and medical data) . Special surveys have been and are conducted

for specific purposes, including, for example, the CAP survey [19]* and FAA surveys

at airports, which are candidates for towers or navigation aids. The CAP survey

varies in precision from area to area, hence may be quite unreliable as a basis for a nationwide data base. The special surveys at FAA facility candidate airports are

* Numbers in square brackets in the text refer to articles in the reference

section, page 46.

4
limited to fairly high activity airports, and so there is no record of the substantial

GA traffic at lower activity airports. Overall, sources of GA data are meager or nonexistent.

With an expected increase in general aviation IFR operations and proposed

regulation changes affecting GA flights, more data on present day GA activity are required. Whereas GA now constitutes less than half of the total IFR operations, it

is projected that GA will soon become the major portion. It is therefore necessary

to have better information on the flying habits of this segment of the flying population. In addition, the institution of Terminal Control Areas (TCA) and other proposed

rules changes may increasingly segregate the VFR general aviation flight from IFR

traffic. To assess the effects (including changes in safety as well as possible

economic hardships) of such rules, it is necessary to have a more accurate representation of GA traffic levels in various types of terminal areas.

Synchronous Garble

Beacon responses from two aircraft within the same 2° band width and within 1-

1/2 mile slant range from the same beacon interrogator source interfere with one

another, garbling both responses. It is possible to decode the garbled responses if

not more than two aircraft are involved. It is therefore desirable to investigate

the frequency with which three or more aircraft will be in this situation, as an increasing fraction of traffic chooses, or is required, to use a transponder.

Communications Requirements for Upgraded Third Generation (UTG) Equipment

In the automated ATC environment, various subsystem elements must communicate

with one another. Examples include (1) flight plans sent from an FSS to an ARTCC,

from the ARTCC to a tower or back to the FSS, and from one ARTCC to another; (2)

messages from the computer to print flight strips at the appropriate sector positions;

(3) messages from sector positions back to the computer to update flight records;

(4) voice messages between controllers and pilots in aircraft under control; (5)

radar signal responses received from aircraft; and (6) FSS advisory activities.

Additional communications requirements may be imposed as presently non-automated

activity is automated. Estimation of the equipment required rests on traffic data.

Area Navigation (RNAV)

RNAV is a means of providing navigation which permits straight-line flights

from point of origin to point of destination. Airborne computer equipment determines

the route by calculating waypoints given by pre-determined distances from a VOR.

The pilot then navigates to and from en route waypoints, using the VOR bearing

indicator in the same manner as in flying to or from an actual VOR. Airborne RNAV

equipment varies in cost depending on its complexity and sophistication, but the

least expensive set presently costs about $5,000. Owners of small aircraft will

therefore be less likely to invest in this equipment than will owners of larger, more expensive, aircraft.

RNAV equipment is increasingly being used as pilots and controllers gain experience with it. Since straight-line routes may intersect one another as well as conventional routes, it has already become necessary to establish designated RNAV

routes and approach procedures to facilitate handling of RNAV flights by controllers.

Some RNAV routes may coincide with existing air routes, but in most instances they

will be different. It is projected that in the post-1982 period only RNAV routes

will exist in the altitude structure above 18,000 feet. To plan for the interim

period it will be necessary to analyze comparative usage of the two systems and to

investigate their interaction.

Collision Avoidance System (CAS)

One proposed type of CAS relies for its distance calculating ability on the

availability of accurately synchronized time signals. These signals, broadcast from

ground stations, would be recevied by all CAS equipped aircraft within some radius

(say about 60 miles) of a station. The aircraft could thus continually maintain the

calibration of their airborne clocks. Aircraft beyond range of a ground station

would haVe to recalibrate their clocks with those in aircraft within broadcast range

of a station, with a commensurate degradation in accuracy of distance calculations.

It is assumed that, because of the high cost of equipment, only air carriers would

be able to provide recalibration services to other aircraft. In order to know where

the accurate time ground stations should be located, it is necessary to know where

5
air carrier traffic is not sufficiently dense to provide recalibration service. Of

course, if such low density areas also have very low levels of other traffic, the

service may not be warranted: the tradeoffs of cost and coverage for low traffic

levels must be evaluated.

Sizing NAS Computers

The automated NAS system uses several different versions (implying different

size configurations) of the IBM 9020 computer. Since this equipment is unique to

the FAA application and will be in production only until the original purchase order

is filled, any subsequent equipment orders will incur start-up time lags and associated costs. It is therefore necessary that computer equipment requirements be accurately

specified before the initial production cycle ends.

Interrogator Interference

As an aircraft nears U.S. airspace, it must be identified as friend or enemy

for air defense purposes. Airborne interrogation equipment (IFF) is available to

perform this function automatically, but it is subject to jamming, either deliberately

or due to the proliferation of electromagnetic radiating equipment. It is therefore

necessary to study how often jammed IFF response might occur, to investigate methods

of detecting deliberate jamming, and to develop means of identifying intruders in

spite of the various possible interferences.

TACAN and DME

The distance-measuring portion (DME) of the tactical navigational aid (TACAN)

is interrogated by airborne equipment to provide the pilot with distance information

from the navaid site. With the radial information normally provided by a passive

VOR (the combination with the DME being termed VORTAC) , position can be determined

with a single navaid. As the number of aircraft possessing the DME equipment increases,

there is danger of saturating the ground equipment, hence it is necessary to evaluate

when and where DME saturation is likely.

Frequency Reassignment for Enroute Sectors

Each sector control position in an ARTCC is assigned a discrete 50 kHz radio

frequency for voice communication between pilots and the controller of that sector.

Frequencies for adjacent sectors must be sufficiently separated to avoid interference.

As traffic increases and as rules and procedures change, sector boundaries are redrawn and new sectors may be formed, with frequencies reassigned whenever new

sectors are created. Changes in traffic patterns affecting relative traffic levels

in different sectors may also necessitate frequency reassignment.

OMEGA

The standard short range air navigation system over the U.S. land area utilizes

VOR, which is limited to line-of-sight operations, but no system with equivalent

accuracy exists for oceanic navigation. The most common navigation system now in use for trans-oceanic air travel is inertial navigation, which does not require

ground stations, but which computes present position from known past positions by means of a gyro-compass, speed, and weather data. Most aircraft carry two inertial

systems, for redundancy and cross-check capability. Loran navigation is also available for use by both aircraft and marine vessels. However, Loran relies on signals

broadcast from ground stations and its coverage is not complete, leaving a gap in

the middle of the ocean where another system must be used. Satellite navigation

systems have been considered but were not recommended in the ATCAC report [15]

because of their cost.

Another navigation system, OMEGA, has been proposed for adoption. It broadcasts

vlf signals, and only a small number (five or six) of ground stations would provide

complete coverage of the Northern Hemisphere. Information for trans-oceanic air

traffic is required to assess the benefits of such a system in terms of increased

safety or a reduction in the present trans-oceanic separation standards.

Flight Information Region (FIR) Reconfiguration

Coastal radar equipment provides surveillance coverage of flights for only a limited distance over the ocean. In the strictest sense, oceanic flights are not

under control, since their movements cannot be monitored independently by ground

personnel. Over the ocean, where radar coverage is lacking. Flight Information Regions

6
(fir's) have been established. In these areas, ground personnel from (and in) the

country which has control responsibility for the particular region advise aircraft

on conditions and monitor positions as reported by the pilots. As traffic increases

and traffic patterns change, it is necessary to reexamine regional boundaries to

determine if a new configuration (size or number) of regions might expedite oceanic

air traffic.

Satellite Navigation Power Requirements

Satellite navigation systems are expensive, in large part due to the power

requirements of on-board equipment. Since a satellite's life is expected to be at

least five years, care must be taken when estimating power requirements that the

initial supply of power is sufficient for the full span. This must be carefully

balanced against the extra launch cost of additional payload entailed by overestimating

power requirements.

3 . 2 Data Required

The programs described above may be broken down into three categories: those

where studies are concerned primarily with the terminal area, those concerned with

the en route ATC environment, and those requiring data on oceanic flights. Each

category has unique data requirements, which can be described under the following

headings

:

a. geographic area

b. desired traffic level

c. type of traffic sample

d. time length of sample

e. traffic to be included

f . data items required.

A more complete description of the data requirements under each of these headings

appears below.

3.2.1 Terminal Area Data

a. Geographical area - Users of terminal area data require them for one or more of four different sets of terminal environments. Those who are studying problems

for which high traffic density is the critical factor require data from several of

the large and medium terminals (as determined by number of operations, possibly in

various categories such as itinerant or instrument operations) . For some applications

the density of the environment is only one of several factors which are being investigated. In this case, data are desired from a relatively small number (say less than

10 or 12) of airports which can be said to be representative of the whole spectrum

of airport environments. Of course, care must be taken in choosing such representatives to insure that all important types of environment are included; it may not be

possible to restrict the representative set to as few as 10 or 12 airports. Depending

on expected applications, the representative set of terminals may or may not include

non- tower airports, for which data are difficult to obtain. Some analyses may focus

on GA traffic activity, the major user of such airports, so the category "non- tower

airports" has been separately included for such applications. Each of the other

three categories refers to only a single terminal or airport, providing data required

by most studies which focus on landing and takeoff operations and ground activity.

Some studies, however, need data on all flights airboarne within a radius of 30 to

60 miles of an area and need to know about any flight in the airspace, whether it

lands or takes off from the major terminal, from a satellite airport in the area or

is a through flight. An additional category provides d.ata for all flights airborne

in a large hub area (defined by the FAA as SMSA's whose airports have at least 1% of

the total U.S. enplaned passengers). These hubs usually contain at least one major

terminal and several smaller airports.

b. Desired traffic level - Since the FAA ATC system is designed to facilitate

safe traffic flow, many system elements must be able to handle any traffic level

which is attained. Design parameters are therefore determined from peak traffic

conditions. Other analyses must evaluate system performance under average or typical

traffic conditions.

c. Type of traffic sample - Although many FAA studies require traffic data,

there are differences from study to study in the specific <iata needed. One type of

needed data is the instantaneous "snapshot", which provides; a complete picture of

all airborne aircraft at a single point in time, including the aircraft positions

7
and other relevant information about each aircraft. The snapshot may be required

for studies concerning relative positions of aircraft at a given moment. Another

type of terminal area data concerns counts of operations per time interval, including

such activity categories as instrument approaches, all approaches (landings), or all takeoffs, each of these usually being provided as hourly arrival and departure

rates on each runway. Such data might become inputs to simulation programs for

subsequent calculations of any required relative position data. In addition to

data on airborne operations, there is some need for information about ground

operations at the more complex terminals.

d. Time length of sample - The snapshot described just above corresponds to an instantaneous picture of the situation in the sky, with one-minute periods,

perhaps, used as surrogates for the instant. Studies requiring simulation of

terminal area operations would most often require hourly data for as many as three

hours, and some would call for traffic throughout an entire day. For rapid changes

in traffic levels it may be desirable to have data for 15-minute intervals (rather

than hourly) over the period of interest. In addition, some studies may require

data on how traffic levels vary weekly and seasonally relative to usage in the

base time period.

e. Traffic to be included - If data on all traffic were equally easy to

obtain, a data sample could include everything, allowing selection of the most

relevant information for particular studies. However, since it is more difficult to

obtain data on some classes of traffic (notably VFR traffic not filing flight plans)

than on others, it is desirable to know if some studies might be performed with a smaller (and presumably more easily obtained) set of data. IFR traffic is already

recorded on flight strips and is therefore most readily available. On the assumption

that those VFR flights for which flight plans are filed are made by the larger and

better equipped aircraft, one might obtain from flight plans the data required to

conduct studies regarding those aircraft which might be expected to carry the more

sophisticated types of new equipment. Data are not currently collected on VFR

flights not filing plans, and would have to be obtained by special surveys if data

are required on all flights.

f. Data required - Various pieces of data are needed for the different studies.

Position is included in snapshot data, but must be simulated by studies using operations rates. Some analyses need data broken down by category of flight rules (IFR or

VFR) , by user category (AC, GA, or MI) , or by flight type (local or itinerant)

.

Flight duration has to be an input for some studies where the persistence of various

conditions must be identified, or in the form of distributions over all flights where

specific tie-ins cannot be established. These data items include aircraft type

(sometimes called mix), avionics carried (transponder, communications equipment,

navigation equipment), assigned or actual altitude, and speed and heading. Some

studies need data on the fraction of aircraft executing such maneuvers as turns,

climbs or descents. In addition, it is necessary to have information on the utilization of communications equipment, and message frequencies and length. Finally, some systems under study will have special airborne equipment associated with them. For

these, the fraction of aircraft having such equipment will have to be known by the

user, but this information will not be a part of the traffic data.

3.2.2 En Route Data

a. Geographical area - En route studies encompass larger geographical areas

than do the terminal studies. Some analyses require data for the airspace over all

of CONUS (the contiguous 48 states) ; others require the high density Northeast and

Southwestern U.S. areas. A third category includes en route sectors from different

ARTCC's. The sample set of sectors should be as small as possible, consistent with

containing representatives of as many different types of en route environments as possible. I

b. Traffic level desired - As with terminal area studies, most en route analyses

require data either for peak or for average traffic levels. However, one study

concerned with adequate coverage by airborne equipment, has a specific need for data

on low traffic density areas.

c. Type of traffic sample - As with the terminal area analysis, some users

require snapshots containing positions of all airborne aircraft; others would use

only counts of the aircraft airborne at a given time. A third group calls for the

route flown by each flight or even the actual track, including deviations from the

planned route, and a fourth calls for the origin and destination of each flight, but

not the route or track flown.

8
d. - f. The categories under the headings "Time length of sample" and "Data

required" are the same as those described for the terminal area. 3.2.3 Oceanic Data

a. Geographical area - Several studies being conducted by the FAA require data

on trans-oceanic flights, primarily in the North Atlantic area. One study requires

data from oceanic sectors of the NAS system, and another concerns the evaluation of a world-wide navigation system, requiring data from all over the world. All studies,

with the exception of that of NAS oceanic sectors, call for data on flights over the ocean in areas not covered by radar or ground-based navigation systems, areas in

which it is difficult to obtain data on actual tracks of aircraft, but may use intended

flight paths.

b. Desired traffic levels are the same as for the terminal and en route data

sets, namely peak and average densities.

c. Types of traffic sample desired include three of the categories described

for en route data: the snapshot, the route flown, and the flight described by origin

and destination without reference to route.

d. - f. The remaining categories are the same as itemized above for terminal

and en route data.

3.2.4 Requirements Matrices (Table 1)

The following matrices display the data requirements expressed by users and

interpreted by the NBS project staff in accordance with their experience in modelling

and analysis. An "X" means that the indicated user requires the data item, whereas a blank means that it is not now expected to be required.

3.2.5 Non-Traffic Data

In the course of discussions with people analyzing air traffic control problems

and systems, they expressed a number of desires for data not specifically on air

traffic. Most of these data are available from sources within the FAA or other

sources krfown to the FAA. They concern ATC system, airport, and aircraft characteristics, navaid and radar information, and weather data, and are listed below.

1. Air traffic control system characteristics

a. procedures

b. airways, SIDs and STARs, intersections

c. sector boundaries

d. computer system operations

2. Airport characteristics

a. runway configurations and standard operation procedures

b. terminal locations

3. Navaid and radar data

a. locations

b. coverage C3-dimensional)

4. Weather

5. Aircraft characteristics

4 . 1 Existing Sources

The FAA collects a substantial volume of air traffic data on that portion of

aviation activity which uses its ATC and FSS facilities and services. These data

range from manually updated flight strips in air traffic control towers and air route

traffic control centers to the vast amount of data contained in and outputted by the

a.b. aircraft operating characteristics

airborne equipment.

4.0 DATA SOURCES

9
Table 1, Terminal Area Matrix

Data Item

Xiu

tnp

8

.SQ_

Geographical Area:

1. Targe and medium terminals

2. Representative terminals

3. NDn-tower airpcrts

4. Large hub areas

Tcciffic level desired:

1. Peak

2. Average

3. Lcfw density

Type of traffic sanple:

1. Snapshot

2. Instrument approaches

3. Terminal area arrival rates

4. Terminal area departure rates

5. Ground operations

Time length of sanple:

1. Instant

2. Minute

3. 15 Minute

4. Hour

5. 3 Hour

6. Day

7. Diurnal Fluctuations

8. Seasonal Fluctuations

Traffic to be included:

1. AC only

2. IFR only

3. IFR and larger VFR

4. All traffic

Data required:

1. Category of flight rules

IFR/VFR

User category AG/GA/t-H

Flight tipe-local/itinerant

Flight duration

Aircraft type

Avionics

7. Altitude

8. Speed

Heading

Ntoeuvering

CcHTinunication rates Connunication iressage length

Special airborne equipnent

9. 10.

11. 12. 13.

10
Table 1. Enroute Area Matrix

r

Data Item i

I

Before

and

after

NAS

stage

A

I

Capacity

sizing

I\IAS

conputers

Ccmmunications

reqpiirements

for

UTG

Equip

IFF/ecm

Interference

lACAN

and

DME

Frequency

Assignitent

For

Enroute

Sectors

Geographical area:

1. All of CXMJS

2. Representative enroute

sectors

X X

1 X X

X

X X

X

X

X

Traffic level desired:

1. Peak

2. Average

J • JJLAV UcJiisX t-y

X

X

X

X

X

X

X X X X X

T!ype of Traffic Sample:

1. Sn^shot

2. Track flown

3. Route flown

4. Origin/Destination

5. Instantaneous count

X

X

X X X

X

X

X

X

X

X

X X X

X

Time length of saitple:

1. Instant

2. Minute

3. 15 Minute

4. Hour

5. 3-Hour

6. Day

7. Diurnal fluctuations

8. Seasonal fluctuations

X

X

X

X

i

X

X

X

X

XX

X

X

X

X

X

X

X

X X

11
Table 1. Enroute Area Matrix (Contd.)

Data Item

Is

u cn

(0

C 3

N e H o w u

o

EHD

uo

aO CQ

•P c

(0 0) -P o e c

H (U <U cue

CT 3

O Q) CT D H <U

0)U

>4-l

fa c H H

W M

0}

y o

Traffic to be included

1. AC only

2. IFR only

3. IFR and larger

VFR

4. All traffic

Data required:

1. CategD]ry of fligh

rules IFR/VFR

2. User category AC/

GA/MI

3. Flight type-local

itinerant

4. Flight duration

5. Aircraft type

6. Avionics

7. Altitude

8. Speed

9 . Heading

10 . Maneuvering

11. Coininunication

rates

12. Communication

message length

13. Special airborne

equipment

X

X

X

X

12
Table 1. Oceanic Area Matrix

Data Item

(0u

0) +j3

e u

o o

u

1^ m

o

C C

N 0) H U

cn p

c

o

-P -p

10 c

e

0)

3

cr

H U

Q) 0)

rtJ o

cn g _ Geographical Area:

1. North Atlantic

2. U. S. Coastal

3. All oceans

Traffic Level Desired:

1. Peak

2. Average

3. Low density

Type of Traffic Sample:

1. Snapshot

2. Route flown

3. Origin/Destination

Time length of sample:

1. Instant

Minute

15-Minute

Hour

3-hour

Day

Diurnal fluctuations

2.

3.4.

5.

6.

7.8. Seasonal

fluctuations

13
Table 1. Oceanic Area Matrix

Data Item

m

u

0)

Oi m

e u

o o

u

o

CO 0)

a>>

o

Oi

c

o o

•r4 +J

nj

(d CP 3 >

cr CO C -Mc

c (U (U O +J e

O H 0) 0) f-i u

M fH •H

(U 3 « 4J cr H (0

o:) u Traffic to be included:

1. AC only

2. IFR only

3. IFR and larger VFR

4. All traffic

Data required:

1. Category of flight

rules IFR/VFR

2. User Category AC/GA/

MI

3. Flight type-local/

itinerant

4. Flight duration

5. Aircraft type

6 . Avionics

7. Altitude

8. Speed

9 . Heading

10. Maneuvering

11. Coininunication rates

12. Communication message:

length

13. Special airborne

equipment

14
NAS and ARTS computer systems. The data are generated in the ATC facilities during

the course of conducting day-to-day air traffic control and management functions.

Except for that portion of the data which is normally transmitted to FAA Headquarters

as the basis for FAA published air traffic information (see references [3], [11],

[12], and [18] for example) and other in-house uses, the data are destroyed after

some specified interval of time. Most of the data used and published by FAA Headquarters,

although providing long term (usually annual) measures of air traffic activity, are primarily workload factors which serve as a basis for ATC facility staffing. The

primary sources of these data are as follows:

FAA Form 3588

FAA Form 3444

FAA Form 723 0 FAA Form 7230

FAA Form 7230

FAA Form 7230

With the possible exception of the IFR Peak Day data, the above sources all provide

long-term activity data which are not adequate for use in analyses requiring short-term

or instantaneous air traffic situation data.

In addition to the above air traffic activity data sources, other related data

sources are available to users. These are: The Official Airline Guide [14]

CAB Airport Activity Data [1] which cover air carrier operations, passenger em- planements and mail cargo data.

Voice tapes recorded in the ATC facilities

Aircraft and airman registration data maintained by the FAA in Oklahoma City

Special air traffic studies such as the Los Angeles basin model [7], [8], and

[9] and the Long Beach surveys.

4 . 2 Requirements-Sources Matrix (RSM) , Table 2 The Requirements-Sources Matrix (RSM) has the same structure as the requirement

matrix given in Table 1, differing only in the matrix elements. Whereas an "X" in the

requirement matrix represented a requirement for a particular user, the corresponding

matrix element in the RSM employs the following set of numbers to represent a set of data

sources. The primary sources for each requirement appear at the top of the cell in

square brackets, with less important ones below in parentheses.

All sources containing any information on a particular data item are listed

immediately to the right of the row heading of that item. Similarly all sources having

any information required by a particular user appear directly below the column heading

identifying the user. In each case, as a convention, the more important data sources • are cited in square brackets at the top of the cell. The data sources are referred to

by number in Table 2, as follows:

(1) IFR peak day

(2) 2% sample of filed flight plans

(3) Facility workload

(3.1) ARTCC

(3.2) Airport

(3.3) FSS

(3.4) IFSS

(4) Aircraft registration data

(5) Official Airline Guide

(6) NAS & ARTS computers

(7) Voice Tapes (FAA ATC Facilities)

(8) Weather Reports (NOAA and FAA)

Since the above sources are not adequate to satisfy all users' needs, three

"pseudo-sources" have been created. The data contained in these sources are not

presently available from continuing FAA collection efforts, but have been included

here for completeness and to point up graphically where data gaps exist. These

"pseudo-sources" and their codes in the RSM are:

- IFR Peak Day Flight Plan Summary

- FSS and CS/T Flight Plan Survey

-12 - ARTCC Operations and Instrument Approaches, Monthly Summary

-11 - Airport Operation and Instrument Approaches, Monthly Summary

-13 - Flight Service Station Monthly Activity Record

-15 - International Flight Service Station Flight Service Activities

15
TEBMINAL AREA

\ USKR

J

i

(:i;-ni;:!»

I'll III! 1iiiA'*rr l'<tii<

1 id.i.lil liCY STOl.

WAK1-: TtlRIUM.FNCK POLLUTION

BEFOKE i AFTER

ARTS III

\ PKIMAUV IIATA \ SdUUrK

, - - —

1 1 1 ( 6 i 10. 2 1 (11 (0.2 1 (11 in 11 ( A

(O.ll (61 (0.2) 11

(1) (6)

^^1 ro;;!iAir, OA 1 A ^^IIPUCI

(0.2) (H) (7) (". I) (')

1 . .

(0. 1) (2) (3.1)

(:l.2)(5)(6)

(7)

( I ) (0.2) (?) (3.1)(1.2)(3.31

('•)(7)

( I ) (0. 2) ( ') ) I ' ) (O . t 1 W ) (3.2)(H)

\'' . 1 ) \ i r \ ' • ^ / (0.2)('.)

IiMA in 'jiiiKi.:ir;ii HA 1 .\ '.1 'inter.

1 !. ;\\ iiiuM Ti.V) (iT,') ( 1 )(.') 0(1.'.)

'!) ('•) ( /) ("1

1 1 1161(0.2)

(11) |o.2||l)

(7)(0.l)((.)

.-_ 10.2|(1)(0.1) (2)(3.2)(i)(6)

\"/

(1 1(61(0. 1)(2) (0.2)(3.2)

HI :-KI M NIATIVK (0. 1) (II..') (n (2) 1.?) ( 1. 1) ((.)(')(») (1)(6)(B)

1

|n.l|l(.l(0.2)(7) !(l)(J.2)(3.3)(2)

-L

(0.1 116] (1)(0.2)

l..iN-|n'ji:i(

1 i BMi:i,\i.r. 0. /) i J) Ci. n

i

1 a;:i:i; iiuii A'-l A*".(0. 1 ) ((I. .0 (,.(!)

( 1. 1 1 i (;)

•

! 10.21111(2)

! ((.)(;) (O.I)

,M,i, nv cn;.'i'':

IK' ) iii '.•)( \ 1 (Tj (1.1) ('.) Ill (.,1 ,i}<'>

1 h

1. REPRESENTA 4"(n. 1 1 (i|. .'l c.l (/)

. . —

u

N'luni AiiANTii:

(Li '

' 1 ' 1 • 1 ) ( • 1 j

:

( 1 ) (.'1 ( 1. 1 1 ( 1.4) (M (hi (I). 1 ) (r,. ;i —

in. 1 ) (11. Jl 1 1 ; 1.') t

11. ciiAsrAL ( 1. 1 )().•.)' ) ((>)

I'll, n :i

AI 1, (11 1 ANS 11). 1) ( .1 ( 1.'. 1

i 1

r. n.AK 0.1) (II..') ( ; ){'>)

1 *»)(/)( U .) )

1 I11I(.1{0.2)

11 110.21(7)

(0. 1 ) (()) (0.1)10.2111)

((') (7)

; lo.iiKii

; (o.2)(l) |0.2)11)(6)

(5)

u. a

AVI.RjMiE

CI. 1)1 1. 1) .J.i'XJ. ))(!.'.) 'i)(^)(O.U'ii)

(0.1) (6)

10.1 1|(.1(J.3) (3.1)(2)(5)

(3.2) (0.11(61 (61(0.l)(2)

(3.2)

LEVEL I.OU DENSITY ,0.2) (2) (3.1)

:6)

SNAPSHOT (0.1) (6) (0.1X6) —1 i1 (61(0.1)

INSTRUMENT

.PPROACIIES (1)(6)(3. 1X3.2) (11161 (11(61(3.2)

rER.MlNAL AREA

\RRtVAl RjMES

(O.I)(0.2)(l)(2)

(5)(6)(.3.2) 111(61(0.2) (0.21(11(0.1)

(6) (0.11(6K1)(2)

(5)(3.2)(0.2)

10.1)161 (1X0.2)

I0.2)(l)(2) (0.1)(5)(6)(3.2)

riRMlNAL AREA

DEPARTURE RATES (O.l)(0.2)(l)(2)

(5)(6)(3.2) 10.21(11(0.1)

(6) (0.11161(1)(2)

(5)(3.2)(0.2)

10.1)(61

(1)(0.2) (0.21[11(7> (0.1)(5)(6)(3.2)

i

:riwnd operation (7) (7)

^FFic

;

TRACK FLOWN (2)(6)(0.1)

c

ROUTE FLOWN (0.1)(6)(0.3)

(0.2)(2)

p

IIRICIN/ nESTINATION

(0.1)(0.2)(2)

(5)(6)(0.3)

INSTANTANEOUS

COUNT (O.I) (6)

INSTANT (0.1)(6) (O.I)(6)

HINUTE (0.1)(6)

15 MINUTE (n.l)(6)

HOUR

(0.2) (0.1)(6)(1) (11161 (0.2)111

(0.1) (6) (0.11161 (1X0.2)

|0.1)(6) (0.2X1)

u.c

3 HOUR (0.1)(0.2)(l)(6) |0.21[1)(0.1)

(6)

10.21(11

(0.1)(6)

Il)(6| (0.1)(0.2) X

UJ

HAY (0.1)(0.2)(1)(6)

(0.3)(2)(5)

10.21(1)

(0.1) (6X2)

u5

DIURNAL

FLUCTUATIONS

(0.1) (2) (5X6) (0.1)(6)

(0.1)(2) (5X6)(61(0.1)

(2)

SE,\Si>NAL ! (0.1) (3.1) i

1 ;(3.2) (3.4) (5)

'

1

1

t

Table 2 - Requirements - Sources Matrix

16
—T1TOITOl"7r-ea

HLS GROUND

GUIDAKCE

FREQUENCY SPECTRUM

STOL WAKE TURWLENCE POLLUTION

BEFORE 6 AFTER

ARTS III

RIMARY DATA

. SOURCE

{1)161 (0.21(11 [0.21(11 (0,11(61 [0.11(61 (0.21(1) (1)(6).

\sECONDARY \ DATA \ SOURCE (0.2)(8) (7}(0.1)(6) (0.1) (2) (3.1) (3.2)(5)(6)

(7)

(1) (0.2) (2) (3.1)(3.2)(3.3)

(S)(7)

(1)(0.2) (6)(5)(0.1)(2)

(3.2)(8)

(').1)(Z)(3.Z) (0.2X4)

DATA REQUIREMENT DATA SOURCE

TRAFFIC

TO

BE

INCLUDED

IFR ONLY (1) (3. 1) (3.6) (0. 3) (3.2)(5)(6)(7)

IFH & LARGE VFR (2)(3.3){3.4) (3.1)(3.2)(5)(0.1)

1111*1(0.2)

(61(0. 11(0. 5){2) (3.1)(3.2)(3.3)

(5) (1) (7)

(1) (61(0.1)(0.2)

(2) (3.2)

ALL TRAFFIC

(0.2)(U('>)(7) (2)(3.3)(3.4)(0.3)

(3.1)(3.2)(5)(0.l)

(1)10.21 (7)(0.1)(6) [0.21(11(7) [0.11(61

(1)(0.2) (0.2iri)(0.1X5) (6X2)(3.2)

1

DATA

RCgUIRED

CATEGORY OF FLIGHT

RULES IFR/VFR (0.1)(0.2){2) (3.3)(3.4)(0.3) (0.1X0.2)(2)

(3.2)

USER CATEGORY

AC/CA/HI

(0.1){0.2)(3.1)

(0.3)(6) (3.2)(3.3)(3.4)(2) FXIGHT TYPE

LOCAL/ITINER.

fO DO 2) (ft'i (0.2)

FlICHT DURATIOn

(0. 2) (2) (S) (0.3)(6)(0.1) (0.21(2)(5)

(0.1)

AIRCRAFT TYPE

(0.1)(l)(2)(4)

(5)(0.2)(0.3)

11(0.2) [0.21(11(0.1)

(0.11(1)(0.2)

(2) (5) (0.11(0.2X1)

(0.21(1)(2)(5)

(0.1) [1)(0.1)(0.2) (2X4)

AVIONICS (0. 1) (4) (6) (0.2) 61(0.2) [0.21(0.1)(6) (61(0.1X4)

(0.2)

ALTITUDE (0.1) (I) (2) (6)(0.2)(0.3)

1)161

:o.2) (0.11(61(1)(2)(0.2)

SPEED

(0.1) fl)(2) (6)(0.2) 11(61(0.2)

10.21(11

(0.1)(6) (0.11161(1)(2)

(0.2) (0.11(6) (1X0.2)

|0.2)(11(0.1)(2)

(6)

HEADING (a.l)(6) (0.11(6)

MANEUVERING (0.1)(6) (0.1)(6) (61(0.1)

COMMUNICATION

RATES (6)(7) 6) (7)(6) (6)(7) (61(7) (6)

COMMUNICATION

MESSAGE LENGTH 0(6) (6) (7) [6)

SPECIAL AIRBORNE

EQUIPMEOT TES NO NO YES NO NO NO

Table 2 - Itequireirents - Sources Matrix

(Ctontinued)

17
K

All IS in

lliri.l 111 IIIATIIIN

SClll IHll.l,

1 \rAi:iTif

^PEA CCNTIIiUtl

i:a

>

r.viciipiiiioiis

riAi! iii.i; (iiiTKi;)

j, ni.TiliSICATfONS ;

Ki.'.'ii 1 in2ir%TS

ii.ii II n; H)uii :;i sr

('SO)

Vkl'dlHAHV DAI A

1^111-2) 11110.21 10.1 l|0.2| (0.1 1161 (0.11(61 \ SI ( ii;:ii.\iiv \ liAIA \ '.oiikCi; (I) (6) (0.1)

(0.2)

II') ^0. I) (I) (f.) (i?) (1.1)0.2)0.3)

O.'.)

(1X4) (I) (2) (7)

i5

l.ABI.K 1, Hr,llli:H

I I l^llrlAl.^

(il.I)(0..')(l M2)

( 1. 1)( 1.'.) ^''X'S) (/ ) (")

(2|n.21(l)«>)

(U. 1X0.2)

1". Mil 1 (II. IX*.) 0.11(61(1)

rj)(7)

1 n r.si \IATIVK

II I r;i:iAi-S (O.IKH.-'XIM.')

( i.2)( 1.

|o. 21111 (o.lXf.)

(0.1 110.21(1X2) 0.2X I. ))((.)

;(•;: tdui h

ii:i;Mi:;Ai.s ((i.2)(^) 1 1.:') 10.2) (0.2) (2X3.2)

i^\i!> f: mill

\1!|:as

U.I. iir 1 1'Mi:;

(y.l)(o..')(.'Mi)

( 1. 1 )( 1. .•)((.>. /) (ii.iM0..'lll((.'l

( 1 . 1 11 'r U ) < 1. )

1 /)("!

(II. 1 ) ("i..'i (1.) ( ;)

^ 1 1 (:•! 1 1. 1 ) (•)

(0.21(5) (0.1) IU [0.11161(1) 0.11(61(1)

f2)(7)

\

nVE ENROUTI -SECTOR - norTM ATIJMIIIC u II -•) ( 1. 1 n 1.'.) '

"

('i»('.l(II.IWn.,')

|0. 1)

1 ) in. .'Ill ) I.')

( 1. 1 ) 1 1.'. ) (, . .h) "' "

111. 1) 1'. 1 1 1.'.

)

i.S. CUA'iTAL

.

M.L OCEANS

1

.

i

I'KAK (0. 1)111. .'((DC.)

('.)(.•)(•). 1)

1 1 110.21

(O.l).l.) ili.lll0.71(l)(6) (0.11161(1) 0.1|(61(1)(7)

AVKHAOF.

(u. IK 1.1) 0.2)0. 1)( 1.'.)

1 J) > (11. I M'l I

12113.21(0.1)

(6) (O.U(ft)

0.] 1(2X(.) (l.l)().2>().3)

(3.4)

LOW DENSITY

(o.2>(2)().;)

(0)

•s

I

SNAI-Sllor (0.1)(f,) (0. !)(() (ii.n((.) in.il|(.| (0.11(61

I'. .r r:ii sr

Al I l.i s (l)(C)( 1.1 )( I.V) (1X'.)I)-21 161(1)

1

1! i,::iN,\i. AKi-A

Ai-l-.IVM. KAll.S (U.l)(0.?)(l)(2)

(•i»('.)0.2)

1 1 ;io..-i

in. Dli.)

|0.1 110..M(I) (2)(l.)0.2)

] Ti :-.MlNAi. m : \

iil.i-Akr;:iii. liAii'.s

(II. 1 XL •.•)(!) (J I

, ('>X(.X1.2) niri.ri

c". U(i.)

10. 1 1!". 21(1) <2)«.)( 1.2)

(iKOIIMI OI'KIIATUCT (') (7)

1

ivvr i (2)((.)(ll.l)

i

:

li'.Mi. Fi.o;v; (O.IX'.XO. J) (0.2X2)

I'KU i:;/ Hi si ISAi ION o.i)(ii.;x.')

(5)(iO(n.-,)

\.';taneoi:s

j ('1. !)(')

1

7.

l-t

i;.-. lA.'ir t— '

I (11.11(1.) io.ilif.l 10.1111,1

MIM'TE (O.nc.) (0.11161

n ;u:;uiE i 1)11.1 10.1116] ;

i (0.2) (0.1X1. XI)

i

Mil ..•)

i.l. 1 , l:.)

1.1.1 no. .-•;('.)

) "":'!( ! {•;. 1 ) (II,.') (1 ) ((,) (1X1.1(11. )>(0..-' 1 1 II-'.

'•'. IX'.i

,11.1 11'.. 21(1)

('.)

;. ((.,n(ii.?)ii)('.)

', (0. )) I/' 1 (.)

' 1 • Dinr.Ai. (O.IX.") iui iu.\rio:is (5)(ii) !21C0. ))((,) (ll.IXA) |0.11(2X")

10.11(61

(2)

Si:A'.(>:iAi, ; (o.i)(i.l)(i.2) VLUCIUATIOSS 0.3)(}.4)(5) (O.IK 1.1X3.2) (3.3)0.4)

(0.1)(5)

Table 2 - RBquirenents - S<3urces Matrix

(Ctontinued)

18
TERHINAL AREA CONTINUED j

. • USE« ARTS III IHPLQ1FNTATI0N SCHEDULE

(OPACITY CA

SYNCHRONOUS GARBLE

(HITRE)

'

COHMUNICATfONS

REQUIREMENTS

FOR UTC

EQUIPHENT

(CSC)

IMARY DATA SOURCE

12)13.21 11(0.21 (0,11(0.21 (0.11(61 10.11161 \ SECONDARY \SCURCE \

(1X6X0.1)

(0.2)

(6) (0.1) (1)(6)(2) (3.1X3.2X3.3)

(3.4)

(1)(*) (i)(2)(;)

DATA REqUIREHENT DATA SOURCE '

TRAFFIC

TO

BE

INCLUDED

IFR ONLY (1)(3.1)(3.4)(0.3)

\3 . 1} \y Hn} { / )

-

trp. & LARGE VFR

(0.2)(n(6)(7)

(2)(3.3)(}.4) (3.1)(3.2)(5)(0.1)

2113.21(1) (0.2X6X0.1)

,VLL TRAFFIC

(0.2)<1)(6)(7) (2)(3.3)(3.4)(0.3)

(J.l)(3.2)(5)(0.l)

11)10.2] (0.1X6)

10.1)10.2|(1)(6) (2X3.1X3.2)

(3.3)(3.4) |0.1)16)(1)

(0.1][6](1)

(2) (7)

DATA

REQUIRED

CATEGORY OF FLIGHT

RULES IIR/VFR (0.1X0. 2)(2) 121(0.1X0.2) [0.21(0.1) (0.1)(0.21(2)

(3.3)(3.4)

USER CATEGORY

AC/CA/Mt

(0.1)(0.3)(3.l)

(0.3) (5) (3.2)(3.3){3.4)(2)

|2|(0.1)(0.2)

13.21 (6)

(0.11|Cl.2)(2) (3.n(3.2)(3.3)

(3.4)(6) FLIGHT TYPE DCALJUflNERa£LX

(0.1)(3.2)(6)

(0.2) 3.21(0.1X0.2)

(6) I0.2)(0.1)(6) (0.1)10.21 (3.2X6)

FLIGHT DURATION

(a.2)(2)(5)

/n i \ / £. \ / n i\ (U. JMoJ to. ij |0.21(6)(0.1)

10.21(2)

(6.1)

AIRCRAFT TYPE

<0.l)(l)(2)(4) 121(0.1X0.2)

(1) 11)10.21

(0.1) 10.1)10.2)(1)(2) (0.11(1X2)

AVIONICS (0.1)(4)(6)

(0.2) (0.1X0.2X6) 10.11(0.21(6) 10.11I6H*) 10.11(61

ALTITUDE (O.U(l)(2)

(b)(0.2)(0.3)

11110.21 (0.1)(6) 10.11(0.21(2)

(6) (0.11(61

(1)(2)

SPEED

{0.i)(l)(2)

(6)(0.2)

111(0.2)

(0.1)(6) (0.11(0.21(1)(2)(6) (0.11(61 (1X2)

I1E.VDING (0.1)(6) (0.1)(6) (0.11161

M\NFUVFRINC (0.1)(6>

COMTIVNICATION RATES (6X7) (6) (61(7)

COMMUNICATION MESSAGE LENGTH (7)(6) 1 1

1

(6) (61(7)

SPECIAL AIKBORKE

EqOIPHENT YES/^

HO NO NO NO YES

Table 2 - Beqviireinents - Sources Matrix

(Continued)

19
usra .

emouTe aiia

CAS

(TIMF.)

llKl ui'.K k

Ai' 1 ill HAS SI act: a CAPACITY

s.rwi'1 iiAS COMPUTERS

(HITKE)

( iVlMIIKlf ATinN.-i m.lillllMMF.NrS FOH IITC FOIJII'MLNT

(i;r.c)

IFF/l'MC INTKKFI KFNCE

(ECAC) RNAV

lO.IUf.l 111(01 (0.21111 10) 10.11 161 10.1)101 (11(0.21 \ si:i:ii::iiAKV \ DATA (1) (2) (3.1)

(3.2) (3.3) (3.4)

(0.2) (5)

(0.1) (2) (3.3)

(0.2) W

(0.1) (6) (1) (0.1) (0.2) (0.2) (1) (2) (7) (0.1) (2) (5) (8)

(6)

DATA m-:niMui:rir.NT HA 1 N -.I'lMMM-:

Lil

i

u

lASl.lC A MI-.DIUM

ir,K:iiriAi.s

i:Ki'i?i::,i;.T,\TIVE iKici] r:AT.s

(II. 1 ) (II./) (1 ) (.!)

( 1.2) ( 1. I)( 1.'.) ('.)('•)(;)(>!)

(o.i)(i).;')(l>(.') (1.2)(J. I)((.)(7)(H)

((l.2)(?)( 1.7)

_

•IDN- rOWl R

1 KI'.'IINAf.S

LAKCF. mm

ahi;as

ai.i, ok cumis tEPRESENTAriVE ENROUTl SECTOR

MIRTH ATljXtiriC

(II. I)(ll. /)(,')(!)

( 1. 1 1< i.:')(i,|l 7) (II.IMS.,'1(II(.') (1.1)1 .) C.l (..) (/)( 1

10. 1) |6| 0) (2) (3.1) (0.2) C^) Id (1) (0.1) (0.2) 0.11(61

(11(0.21(0.11

(2)Cj)(8)(6>

,(ii.l)(U..')(i.)(7) .(!)(.)( 1. 1 )('.! [11 (61 (0.1) (0.2)

(2) (4)

(o..-;i(ii (0.1) ((,)lOI (1) (0.1)

(0.2) 10.11 (61 (1)(2) (0.2) (7)

( 1 1 < .') ( I, 1 1 ( i.'.)'"~ (.)(i )(li.l)(i>.2)

(11. 11

U.S. rOASTAI.

(11. 1 ) (0. . ) ( 1 ) (;) (!.!!( 1. '.)(',)(!.)

(1.. li

l0.2iiU(0.1)

(1.)

ALL Ot.T^MIS (0. 1) l\\ 1 1.',)

_

ft 1'1'AK (".!) '".;•)( DC.)

(!.)(/) (11. 1) (61 (I) (0.1)

(0.2) 10.11 161 (0.2) (U (7) 0.11161

( 1 110.21(0.1)

I5)(0)

.iVKiUCii

(11. ll( ).l) (1.2)(1. !)()./.) (>) (7 ) (n. 1 ) (A) (0.2)(2)(J.l)

(6)

(01(0.1) (2) (3.3) (0.1) ;.i) (0.1)(2)(5)

(6)

LOU DKNSITY 161 (0.2) (2) (3.1)

•NAI'SIIOT (o.u (f.) 10.11101 (f.UO.U (0.1) (0) 161 (0.1) (0.11(01 10.1116)

M'i';:-iAi:HLS (1) (C) (1.U (3.2)

I -

. n-lINAL' A'T.A

\i(,.IVAL ItAli-.; (O.U (»..?) (u (2) : .i i'.MO) ("(.;•) :

j 1 ii riir.AL a;-i a ' (o.i) [.u.n (1) (2) '

|j 'i.i'.\KirKi; KAiiS (S) (0) I J./) ij

1 ' ^1

.RiU'Mi) oi'i inrioM (V)

u.I

t

(?) (•'.) (H. i i CXO.U 10.11161 i!

(O.u (• 1 (11. J) (0.2) l.'l •1.21 (0.1)

I'.)

, 10.21(0.1)(2)

: (0)

.iM.;,:,7 w-\ 1 .-.A r 1 (O.U (II.."') (2)

( ;)(•) (11. 1) r

1 !0.2K0.1)(2)

( (5) (6)

I ir.-iiAMASi'.prs

i'-iii-:.! (O.DC) . (i.KO.U

INStANT (O.UC') iO. 11161 li-,l(O.U 10.11 ICI

'

Ml Mil E (O.U(-.) 101(0.1) 10.11 IGI

I'. MIS-JTE (O.UC-) 10.1116)

HnllR (0.?) lOlllf.l (O.U(.-,)(U (...l)(r,) lu.im.l

1

o

p

U

1 II'UR

ilAV

( .)) I..:) (U (6)

j (D. J) (.:) ('.)

(O.u (0)

10.11101 rTnio.2i(i)

(2)((.)

HliTNVL

tUCTL'AriONS

: (O.U (.:)

' (1.) (6) 101(0.1) (0.1)161(2) (0.U(2>r,)(6)

SLASPNAL

fLUCTU.UIO.'iS (0.1)().U(3.2)

1 (3.3) (3.4) (5) Table 2 - Requirements - Sources Matrix

(continued)

20
ENROUTE AREA CONTINUED

USER CAS

(TIME)

BEFORE & AFTER

NAS STAGE A

CAPACITT

SIZING NAS COMPUTERS

(HITW)

COMMUNICATIONS

REQUIREMENTS

FOR UTG EQUIPMENT

(CSC)

IFF/EMC INTERFERENCE

(ECAC) RHAV

PRIMARY DATA ^ SOURCE

0.1)161 111(61 (0.21U1 (6) [0.11(51 (0.11(6)

(1)(0.2) \ SECONDARY \ DATA (I)(2)(3.1)

\3.*7 (j. J) 13.4) (0.2X5)

(0.1X2)0.3)

(0.2) (4) {0.1X6) (1)(0.1)(0.2) (0.2)(1)(2)

(7) (0.1)(2)(5X8)

(6)

DATA REQUIRraENT DATA SOURCE

'

llJ

a r

IFR ONLY

(I)(3.1)(3. 4X0.3)

C3.2)(S)(6)(7) (61(1)

IFR & LARGE VFR

(0.2)(1)(6)(7) (2)(3.3)(3.4) (3.1)(3.2)(5)(0.1)

[11(61(0. 1)(0. 2) (2)(3.3) 111(0.21(0.1)

(2) (5) (6)

ALL TR.AFFIC (0.2)(1)(6)(7)

(2)(3.3)(J. 4X0.3)

(3.1X3.2)(5)(0.1)

(I.11I6K1XJ)

;3.1)(3.2)(3.3)

:3.4)(5)(0.2)

10.2)111(0.1)

(6) 161{1)(0.1)

(0.2) [0.11(61(0.2)(1)(2)(7)

10.11(6)

atil

r>olU

a:<

CATEGORY OF FLIGHT

RULES m/VFR

(0.1X0.2X2)

(3.3)(3.4)(3)

(O.i)(0.2)(2)

(3.3) (0.21(0.1) (0.1)(0.2) (0.21(0.1X2)

USER CATEGORY

AC/GA/Ml

(0.1X0.3)(3.1)

(0.3)(6) (3.2X3.3)(3.4)(2)0.11161 16I(0.1)(0.2) (0.21(0.1)(2)

(6)

7T T^Uf 'I'V L>T7 :.(^|)^ITINER-

(0.1X3.2X6)

(0.2) (0.21(0.1)((1) (0.21{0.l)(6)

FLICHT DURATION (0.2X2)(5)

(0.3)(6)(0.1)

(0.2)(6)

(0.1) 10.2I(2)(J) (6X0.1)

AIRCRAFT TYVE (0.1)(1X2X4)

(5)(0.2)(0.3) (0.21(11(0.1) (1X0.1)(0.2)

(0.11(0.2)(1)

(2)

(1) 10.21(0.1)

(2) (5)

AVIONICS (0.1)(4)(6)

0.2) 0.11161(0.2) (61(0.1)(0.2)

(4) 16)(0.1)(0.2)

10.11(61

(0.2) (0.11151 ; (0.21(0.1X6)

ALTITUDE (0.1)(1)(2) (6)(0.2)(0.3)

(0.21(11

(0.1)(6) (61(1)(0.1)

(0.2) (0.11(61(2)

(1)(0.2) (0.1)(61 (11(0.21(0.1)

(2) (6)

SPEED (0.1X1X2)

(6)(0.2) :o.2in)(0.1)(6)

(0.11(51 (0.2)(1)(2)

(0.1116) (0.21(11(0.1) (2X6)

HEADING (0.1)(6) . (0.1)(6) (0.1115)

M\NEUVERING (0.1X6) (61(0.1) (0.1)(6) (0.11(61 10.11(6)

CO>CIUNICATI0N

R,\TES (6)(7) (61 (6) (6) (51(7)

COM>aJNICATION MESSAGE LENGTH (7X5) •61 (61 (61(7)

SPECIAL AIRBORNE

EQUIPMENT

YES NO NO NO YES NO YES

Table 2 - Requirements - Sources Matrix

((Santinued)

21

/
HUHDUTE AKEA OCKTL'^UED ' OCEANIC ARtA

\ UStR

TACAN

(KCAC)

1 i:: iiii! xt

A'.'.li:;.>-r:NT FlIK I.MInulE

MiCl'OilS (ki:ac)

I'MKCA

HUi'-'. JiNS COMPUTERS

(11 lANIC sn lORS

(MllKF.)

FIR RECON- FIGURATION

(CSC)

SAIIIMIt

navii;ai kin mui K

RFIJIl|l:i.Mi:NIS (ISC)

V rHIH\KV UATA —

10.11(61 I0.1II6I in.iiiM 10.31(51 10.3)151 10.31(51

V SK:n:.i)\nY \ IIATA «•) (2) (2)(l.'.) (1)(6) (1)(2)(3.4) (2X3. 4)

PATA Kri)iiim;Mi:NT l),M A innnci:

ARci: f, ni:i>iUM li-.RMINM.S

(n. 1 > (I), ,.')(!)(.'

)

( 1.^) (1. IM J.'.) r.).('.l(7)iH) _

:i:i'Hi::.i.:iiATivK

lilUMI.'IAI.S (ii.i)(o.?)(l)(:.')

iDM-Titwr.H ii:rmin.m,s (ll.2)f2)(t.i)

i.AiiCK mm (i).i)co.2>(2)(:)

( 1. 1 ) 1 1. .'J (CI (•/)

'i \i.L OF u;:ius/(I ^'.IJl'l..' \ 1 t \ 1 t \

} \ \ } \ .'. i

( I. I)('.)('l<(il 10.11(61

(?)

O TIVE^ENROUT

,(().l)(ii.2)(r.)(7) in)(.')(j.i)('.) I0.1II61 (M

• o

NORTH ATLANTIC ('•) (''((O. 1 ) (11./)

('I. II

10.31151(1X2)

( l.«) 10.31151(2)

(1.4)

U.S. COASTAL

(II. 1 ) Ml. .; ( 1 ) (2) (1.1)1 l.'.)(0)(h)

111. 1)

10.31151

(1)(6)

AM, ocrah:; (11. 11 f',1 I 1.',) I". <ll 'l(3)('.)

o i'i;ak

(II. 11(0..') (DC)

(1.) (/I (11. 1) I0.l|I51(M

10.3115)

(1)(6) I0.3U51

(1) lO.lllSI

AVtRAfX

lO. 1) ( 1. 1) (l.2)(3.J)(l.'.)

('j>(2)(0. !)((,)

(0.311i| <2)0.4) >

LOU DENSITY (0.2)(2)(3.l)

(6)

SNAP<;ill>T (0.1)((i) 10.1)161 L

l-.-;TliI-Mi NT

Ari'SilACMI.S (I)((.)(3.l)(J.2>

Tl R-MINAL AREA

AI.:ilV,\L RAir.S

(0. 1 ) (0. 2)(1 ) (2) (5)(l')(1.2)

aj

li.KMINAl. AKEA

IM I'AIJtVRK K-\Tr.S

(0. 1 ) (0.2) ( n(2)

(S)('.)(J.2)

!h

_

J

( n.iUNi) ori,K,\T;o;; r- —

= <7)

i

_ H \

\ " ' .

'

?5

IIIACK FLOU:) (2)C.)((I. 1)

t

1 i

E

OFT

I'.'ilTE Fl.oViN

( 0 .

I ) ( ) ( . i

)

(l)..')(.'l

j

'

<l. 11(2)

Mr Si INUION

(0. I ) (0 . 2 ) (2

)

(5)(i,)(r,.i)

i

i

-1

0.31151 ' (2) 0.31(51(2)

INSfANIANFOlIS

, (0.1)(6) ,li).i||'.|

i

-1

i;. ;rA::T {0. !)((•) 10.1)161 |0.11|(.| (6)

MINliTE (11.1) (A) i — H ^ C) ;

1

15 MINTITE : (0.1)(l.)

1

1

1 i _ [ \ (n.?) f (0.1 )(*.)(:)

1

i1

!

1—

d

: (0. 1 ) ((., 2) (u (1.) i - j

i

t

;

! 1 H

O

DAY

1 (0. 11(11. 2)(n((.)

; (l).l)(2)(-.) I

10.11151(2) I 10.31151(2)

(1) 0.31151(2)

»-

111' i(::,M, H.l-'Tl'ATIONS (0.1)(2)

(i)('>) (51(6) 151(2) 51(2)

5EA-;0NAL rLUCIUATIONS

; (0.1)(3.1)(1.2)

. <}.J)0.4)(5)

!i

1

t (51(3. 4>

j^

1

(5)(3.4)

Table 2 - Requirenents - Sources Matrix

(Continued)

22
ENKOUTE AREA CONTINUED OCFJVNIC AREA

\ USER

TACAN i DME

(ECAC)

FREQUENCY ASSIGNMENT

FOR EN ROUTE

SECTORS

(ECAC)

0.1ECA

SIZING HAS COMPUTERS

OCEANIC

SECTORS

(MITRE)

FIR

RECON- FIGURATION

(CSC)

SATELLITE NAVIGATION

POWER REQUIREMENTS

(CSC)

\ RIMARY DATA \ SOURCE

0.11(6) 0.11(6] 10.31(5] (0.3)15) 10.31(5] 10.31(5] \ SECONDARY \ DATA \S0URCE A) J) (2)(3.4) (1) (6) (1) (2) (3.4) (2)(3.4) DATA REQUIREMEKT DATA SOURCE

IRAfFCC

TO

BE

INCLUDED

IFK ONLY (I)(3.1)(3.4)(0.3)

(3.2)(5)(6)(7) 6] 15110.3](0.3) (3.4) (0.31(5)

(3.4)

IFR & LARGE VFR

(a.2)(l)(6)(7)

C2)(3.3)(3.4) (3.1)(3.2)(5)(0.1)

ALL TRAFFIC

(0.2)(l)(6)(7) (2)(3.3)(3.4)(0.3) (3.1)(3.2)(5)(0.1)

0.1116]

[0.3)15) (U(6)

1

DATA

REQUIRED

CATEFORY OF FLIGHT

RULES IFR/VFR

(0 1 WO 2 W21

(3.3)(3.4)(3) 10.3)

USER CATEGORY

AC/GA/HI

(0.1)(0.3)(3.1)

(0.3) (6) (3.2)(3.3)(3.4)(2)(2)(3.4)(0.3] (6)(0.3)

FLIGHT TYPE

LOrAL/ITINERklfl

(0.1) (3.2) (6) (0.2)

FLIGHT DURATION

(0.2) (2) (5) (0.3)(5)(0.1) 0.1)16]

(2)

inlU. iit^l J J I?

J

(2)

AIRCRAFT TYPE (.l)(l)(Z)(^}

(5)(0.2)(0.3) 0.1] 10.3)151

(2) I0.3](5)(l)

AVIONICS (0.1)(4)(6)

(0.2) 0.11(61(4) 0.11(6) 10.3) 10.31(6) [0.3]

ALTITUDE (0.1)(1)(2)

(6)(0. 2X0.3)

C.ll(6) 0.11(6] 10.31(2) 10.3](1)(6)

SPEED

(0.1)(l)(2)

(6)(0.2) 0.11(6]

HEADIHG (0.1)(6)

MA.SEl'VtRINC (0.1)(6)

COLVl'NICATION RATES

(6)(7) 61(7) (6)

COCfUSICATION

MESSAGE LENGTH

(7) (6) 61(7)

SPECIAL AIRBORNE

EQIPMENT YES/^ TES MO YES YES

Table 2 - Reqiiireitients - Soiirces Matrix

((Zontinijed)

23
(0.1) VFR tracking data

^ Contents: Position (x, y, z), class of user, type of aircraft, 0/D,

IFR/VFR classification, local/itinerant, avionic instruments. (Data

accumulated every few seconds or few minutes.)

• (0.2) VFR peak day data (corresponds to IFR peak day data). Contents: class

of user, type of aircraft, route flown, 0/D, IFR/VFR classification, local/

itinerant, duration, speed, altitude and avionic instruments.

(0.3) Non-AC Trans-oceanic peak day data. Contents: Class of user, type of

aircraft, route flown, 0/D, IFR/VFR classification, speed, altitude, and

, . avionic instruments.

4 . 3 Data Not Now Available From Continuing FAA Data Collection Efforts

Current FAA continuing data collection efforts do not include data in the

following categories:

1. VFR traffic not filing a flight plan,

2. Instantaneous positions of aircraft,

3. Avionics usage as distinguished from the fraction of aircraft equipped,

4. Departure and arrival time distributions for all flights as well as the

actual arrival time of any given flight,

5. Positions or tracks of oceanic flights (track data will soon be available

from NAS computer output for IFR flights over CONUS)

.

The most critical lack of data for FAA planning efforts pertains to VFR flights,

since many policy decisions can be affected by these flights, now of only peripheral

interest to the ATC system. Since data on VFR flights are difficult to obtain, the

needs for such data and possible ways of obtaining them are discussed more fully in

section 4.3.1 below.

The lack of instantaneous position data stems from the fact that most FAA

continuing data efforts were designed primarily to collect workload data for planning

personnel assignments and other day to day operations. Most of the current data

consist of monthly or yearly summaries, so that peaking characteristics disappear

and events which occur relatively infrequently, but which have great effect on the

system (e.g., accidents, very heavy fog, equipment failure), are lost among the

averaged data. Some of this lack of instantaneous position data will be remedied

when the tracking programs become operational as part of the NAS computer system.

Some were scheduled to be operational at certain ARTCC ' s in 1973. Even with the

data from the NAS system, only IFR aircraft will be tracked and therefore the lack

of data on VFR tracks will continue.

The accomplishment of some studies depends on knowing what fraction of the

aircraft airborne at any one instant are using a particular type of avionics equipment

(e.g., beacon transponder, VOR, DME, RNAV, radio on each frequency, etc.). The

aircraft registration records contain data on the type of equipment installed in

the aircraft but provide no indication of usage. The frequency of use might be

approximated by assuming that it is proportional to hours flown, which is included

in the registration records. However, such data are too highly aggregated to be

useful for assessing peak loads on various navigation and communications systems.

Better information on equipment usage under various specific conditions is needed,

and this must be tied to the instantaneous data requirements previously discussed.

Departure and arrival time data have serious gaps. Departure times, both

requested and actual, are recorded for all IFR flights. The CATER program in

operation at the three New York area airports (LGA, EWR and JFK) records departure

times for all flights; similar data are potentially available from many FAA towers

with a comparatively minimal data collection effort, and comparable efforts might

collect such data at many airports. Arrival time data are not now recorded.

Flight strips do not presently include these data, and future ARTS computer systems

will send only a drop track message to the NAS computers about 2 miles from touchdown.

More accurate arrival time distribution data are, of course, potentially collectable

in a manner similar to that used for recording departure times. The single set of

arrival time data most difficult to obtain consists of the touchdown times for

specific flights so that, for instance, the peak day flight information would

contain both departure and arrival times.

One more area where data are critically lacking concerns positions and tracks

of oceanic flights. Since there is currently no surveillance system for such

24
flights, actual positions and tracks are unknown. It does not seem that this will

change greatly in the near future, unless some surveillance system which can provide

complete oceanic coverage (perhaps using satellites) is established.

The most critical data lack, as discussed above, is the lack of any data on most VFR flights. This situation will therefore be discussed in greater detail

below.

4.3.1 Why Are Data on VFR Flights Needed?

Considering the difficulty of obtaining data on VFR flights and the fact that

the system has managed without them until now, one might well ask whether these

data are really needed. The answer is strongly affirmative, and the need is becoming

more sophisticated. Several underlying reasons are discussed below.

In the first place, VFR flights form a substantial (but unknown) fraction of

all flights. Although VFR traffic may comprise up to four fifths of all aircraft

operations at flight terminals in the United States, very little information exists

on which to base an accurate estimate of the actual number of VFR flights, their

distribution by geographical area or time interval, total number of hours flown, or the net impact of this traffic on the ATC system.

In fact, the four fifths cited above is a very rough approximation derived

from the fraction of VFR traffic in the 2% sample of filed flights plans for 1967-

71, and the number of aircraft contacted in 1969. It is further realized that

these data will not yield a precise estimate of the VFR/IFR mix since most air

carrier flights, which are still the predominant IFR users, file directly through

the ARTCC's. On the other hand, the FAA air traffic activity counts include only

those operations which come in contact with or use FAA ATC facilities or services.

These facilities and services are either available or readily accessible at perhaps

something less than 20% of the nation's almost 11,000 airports, leaving completely

unaccounted for what could be a substantial portion of all VFR operations.

A second reason for collecting data on VFR flights is that many of these

flights impinge on the control environment, and thus affect the ATC system. Three

areas in which this occurs are voice communications, particularly those involving

advisory services, terminal operations (these two constituting activities in which

VFR flights "compete for the available resources"), and radar detection and tracing

by primary returns, in which uncontrolled aircraft (VFR traffic) become "bogeys",

i.e., clutter and noise which degrade radar performance. In the past, actual

encroachment of VFR traffic on control activities has been relatively small.

However, because of recent expansion of controlled airspace where VFR flights are required to operate under air traffic control (such as TCA's) and the increasing

use of transponders in general aviation aircraft, VFR operations have become more

visible to the ATC system.

VFR flights also affect system capacity. The local effects of expansion of

control have generally been a decrease in VFR traffic, some of which is diverted to

other areas, and an increase in IFR operations, some of which represents shifts in

flight mode by pilots who heretofore have flown VFR. In consequence, the contribution

of current VFR traffic to future saturation may not always be apparent.

Finally, data are needed on VFR traffic because such traffic utilizes the same navigation and communications facilities as do IFR flights. Two clear examples are

DME and beacon transponders, both of which are only moderately expensive to install

in aircraft, are under consideration as possible mandatory equipment, are used by

both VFR and IFR traffic, and whose use is subject to capacity or saturation limita

tions. Too many aircraft operations with DMEs or transponders in the same area can create electromagnetic interference problems and degrade the ATC system. In addition,

the assignment of discrete transponder codes could become a problem because the

available number of codes is fixed.

There appears to be a tendency for VFR and IFR traffic to become progressively

more segregated from each other. An exam.ple is the regulatory altitude limitation

excluding VFR traffic from the Positive Control Airspace high altitude structure.

In general, the increasing segregation has indirect causes, and the present degree

of separation is not known precisely. If segregation should become virtually total

in the future, then VFR data would clearly not be essential to the analysis of IFR

traffic problems. The possibility that future IFR/VFR interaction may be reduced

is suggested by the indicators of growth if VFR traffic. While these indicators

continue to be positive, the rates of increase have diminished. At the same time.

25
the rate of growth in GA IFR flying is increasing at a level which more than

compensates for the decrease in VFR activity. This suggests a leveling off in the

volume of future VFR traffic, which may therefore be amenable to being "contained

in more limited airspace."

Some recognized causes of the trend toward geographical separation of IFR and

VFR traffic can be cited. One is a growing tendency to impose landing fees at

large terminals, thus discouraging use by privately owned, small aircraft which

constitute the bulk of VFR traffic. Another is the establishment of air traffic

control towers (even VFR towers) at moderate activity airports; it has been noted

that these drive away two activity classes which account for substantial non-filed

VFR traffic, namely flight schools and recreational flyers. Also, as previously

mentioned, the expansion of the airspace where VFR users are required to operate

under control has encouraged the more serious users to convert to IFR operations.

Further evidence for the existence of the separation is seen in the fact that fewer

than half (12) of the 2 5 terminals in the U.S. with the largest number of IFR

flight plans filed in 1969 were also in the high 25 for filed VFR flight plans.

Moreover, of the FSS's which contacted the largest number of IFR flights, only 5 were in the high 25 for VFR operations. It might then be concluded from these

observations that separation between non-filing VFR flights and IFR flights in

"busy" areas is greater than the filed VFR/IFR split, but because of the minimal

interface of IFR operations with FSS's, more evidence would be desirable.

A typical characteristic of VFR flights is the general absence (except in the

vicinity of an airport) of other air traffic visible to the pilot or passengers

throughout the duration of cross-country trips, even when traversing the busier VOR

airways. With the increased use of RNAV, the same conditions would presumably

continue to occur in spite of any possible increase in air activity over, say, a five-year period.

On balance, the arguments for requiring VFR data outweigh those against, since

the continuing lack of such data leaves most information on the impact of VFR

traffic in the realm of supposition and conjecture.

4.3.2 Forecasting VFR Traffic

Accurate forecasts of the growth of VFR traffic are difficult because of the

lack of present data. This is so especially because growth may be determined to a great extent by FAA and Congressional policies and such other factors as the availability of fuel for non-essential travel.

The general aviation community and some analysts recognize that progressive

increases in user charges, avionics requirements, fuel shortages, and further

restrictions by extension of controlled airspace could eventually eliminate GA,

except for some business operations. Despite this possibility, it is believed that

the short term consequence will be a leveling off or decrease in VFR flights, and a continuing expansion of IFR operations. Much of the pilot population is probably

willing to accept some increased ATC requirements along with a reasonable increase

in operating costs in return for higher aircraft utilization and the navigational

and safety benefits of instrument flight. This implies that projections of future

IFR traffic must include estimates of this conversion, as well as growth which is

"externally" induced.

Based on studies conducted in the sixties, aviation traffic analysts generally

believe that filed VFR flight plans represent about 1/7 of all VFR flights. No recent

efforts to validate this estimate came to light during our study. VFR flight

plans accounted for about 40% of all those filed at FSS's, IFSS's, and CS/T's

according to the 2% sample in 1972. Assuming that about 1/2 of all IFR flight

plans are covered by the sample (the remainder, almost exclusively air carrier

flights, having been filed directly through ARTCC's), a crude approximation of the

VFR percentage of total flights is given by:

7 X .4

6 + .6 + 7 x .4 X 100 = 70%

26
It is problematical whether this estimate can be refined without massive expenditures.

The CATER program, instituted in connection with studies of noise abatement, undertook

to record and store for analysis all operations at five major airports: LGA, EWR,

JFK, ORD, and DCA. To date, the program has been operative only at the three New

York terminals. It could be expanded to include operations at a variety of moderately

large terminals representative of different areas. However, the traffic originating

at small airports, particularly non- tower terminals, would still go unrecorded.

"Aircraft contacted" data from the 1970 FAA Statistical Handbook of Aviation

[12] show that VFR flights accounted for about 8.6 million out of 9.9 million total

contacts by Flight Service Stations, or about 87%. The corresponding figures for

GA are 7.8 million out of 8.4 million, or about 91%. These percentages are of

particular significance because the data are not limited to filed flights, but

include flights which had no other contact with the FAA's ATC facilities or services.

Therefore, unlike the 2% sample (which records only arrivals and departures) , they

give some indication of the VFR/IFR in-flight ratio over time. However, they are subject to two immediately identifiable distorting factors: 1) IFR and filed VFR

flights are likely to be airborne for a longer time period than are unfiled VFR

flights, and so may represent more contacts per flight, and 2) IFR and filed VFR

flights may request and receive advisories from other ATC facilities, such as ARTCC ' s

.

Using hours flown data from the FAA Statistical Handbook (1970) [12] , it is

possible to make crude estimates indicating that about 80% of GA traffic (measured

in hours flown) is VFR, if it is assumed that all Business and Executive flights

are IFR and all other GA flights are VFR. Such crude estimates are shown in the

following table:

Hours % Business & Executive 5,324,000 21.1

Personal 7,694,000 30.5

Instructional 6,826,000 27.1

Aerial Application 1,427,000 5.7

Air Taxi 2,238,000 8.9

Other 1,711,000 6.8

As mentioned elsewhere in this report, instantaneous distributions (snapshot)

of IFR and some filed VFR traffic in the airspace could be approximated by collecting

flight strips from ATC facilities. No such process is available for supplementing

IFR snapshots with distributions of VFR traffic.

If instantaneous snapshots of total air traffic are required for the analysis

of an ATC system, and if adequate simulations cannot be designed to use existing

data sources, then a suggested pilot questionnaire, which is more fully discussed

in Section 5.1.2, is one possible avenue to obtaining the snapshot data.

5.0 DATA SETS TO SATISFY USER REQUIREMENTS

In the early stages of this study it was hoped that a single set of data might

satisfy all users. It soon became clear that user requirements differ enough that

data collection efforts could be most efficiently designed around five separate

data sets based on the subsystem of the air traffic control system on which the

data are focussed (terminal, en route or oceanic) and the type of data sample

required (snapshot, operation counts, origin/destination data, or instantaneous

counts)

.

It may be instructive to examine some of the considerations which indicate the

infeasibility of a single data file for the desired data sets. The spectrum of

data requirements for ATC analyses could, in principle, be satisfied by a file

containing tracks of all flights in the U.S. for a single year if the following

conditions are all satisfied: (a) any requirements for meteorological, electromagnetic

radiation, or other non-aircraft data are disregarded; (b) traffic outside CONUS is

ignored; (c) all flight data for a full year can indeed be recorded, which is not

at all likely; and (d) growth factors are well enough known to permit projection of

detailed flight activity from one year to another (which is even less likely than

acquiring the historical data) . Given this hypothetical file, users would be able

to extract data relevant to their analyses, albeit at considerable software cost.

It may be conseirvatively estimated that CONUS flights now total 60 million annually.

Assuming an average flight duration of 30 minutes and a 2-second data recording

interval, there would be an average of 450 data points per track. This necessitates

27
a storage capacity for 70 million flight track data "blocks" per day, an overwhelming

mass of data even with current advanced information processing technology . As a result 5 separate data sets (described below) are proposed to satisfy user requirements.

The proposed data sets will be based on traffic data current for the year of

collection and on forecasted traffic levels for a ten-year horizon (perhaps with

some intermediate points). The following section provides, for each contemplated

data set: a description of the contents, a discussion of methods by which the data

may be obtained, forecasting requirements and possible procedures for meeting them

and a discussion of how the data set meets the requirements of each anticipated

user of the set. Before discussing these five sets, some general observations on forecasting air traffic data are in order.

Any approach to the formulation of air traffic activity forecast requirements

must consider what might happen to the general aviation fleet. In fact, since GA

represents approximately 97% of the total civil aircraft fleet, it could be the

major concern of the forecast effort. The future growth or decline of the GA fleet

could be directly tied to user charge legislation. For example, if severe user charges are levied on aircraft owners, GA could be virtually eliminated. The

expected increase in the amount of GA IFR traffic (e.g., more executive jets) might

cause a considerable change in the makeup and ATC requirements of the GA fleet.

These and other factors affecting GA must be considered in detail during investigations

into forecast requirements.

The amount and kinds of avionics equipment to be installed and the level of use are certainly difficult to forecast, although a number of methods have been

suggested. One method relies on information gleaned from market analyses performed

by manufacturers. A simpler technique would apply previously observed rates of

introduction of comparable equipment. A variation would be an analysis of cost

variation over time to estimate how soon the price of a piece of equipment decreases

to a level "reachable" by the general flying public. On the other hand, the

installation of avionics equipment may not lend itself to this type of forecast

analysis, its history perhaps suggesting only a reaction to FAA's regulations and

other actions requiring or encouraging such installation.

Attempting to forecast the amount of usage of avionics equipment leads rapidly

into the realm of FAA procedures changes. If, for example, it is required that all

aircraft entering or leaving a terminal control area have and use a particular

piece of avionics equipment, the usage figures will reflect that requirement.

However, it is very difficult to predict changes in procedures, hence it is not

unusual to assume simply that procedures remain the same, which is unrealistic.

Forecasts of altitude and speed distributions utilize forecasts of aircraft type

mix since optimal cruising altitude and speed depend on aircraft performance

characteristics and ATC personnel accede to pilot requests whenever possible.

Although forecasts of altitude and speed are published for hub areas, they are not

made for specific terminals. Unless the data and forecasting procedures permit such

localized forecasts, alternative techniques must be developed.

Air traffic forecasts must also take into account, in some manner, changes in

the existing air route structure. Modifications to existing routes, additions of new routes or the introduction of RNAV routes must all be considered. In the first

two cases, it may be possible to redistribute the traffic since the changes are

known. With RNAV, however, one must first assume that the routes are essentially

straightline , then redistribute the traffic (alternatively the allocation of flights

to RNAV routes may be left to the user)

.

A final consideration must be addressed: peak day or peak hour operations do

not necessarily grow in the same manner as do total yearly operations. If a particular

airport is currently operating at or near capacity during its peaks, it is unrealistic

to forecast a growth in its peak hour operations which would push it beyond capacity.

On the other hand, the duration of peak periods or the number of days that an airport operates at or near peak level may increase. Therefore, annual growth

rates must be modified before being applied directly to peak or busy-hour data.

5.1 Terminal Data Set - Type 1 5.1.1 Description

This data set will consist of a peak instantaneous shapshot including all

airborne aircraft. Each record will include for each airborne aircraft the following

information:

28
1. Position (x,y) (for instance, latitude and longitude)

2. User category (AC, GA, MI)

3. Flight type (IFR, VFR)

4. Whether flight is local or itinerant

5. Aircraft type category

6. Avionics carried

7. Altitude

8. Speed

9. Heading

In addition, the fraction of all aircraft executing such maneuvers as turns, climbs,

and descents will be included, as will the fraction engaged in various communication

and navigation activities. Snapshots with these data should be provided for 3 to 5 Large Hub Terminal areas. 5.1.2 Sources

Since this data set consists of snapshot data, data on both VFR and IFR flights

and data on avionic equipment usage, three major areas in which existing sources

are deficient, a special collection effort will have to be mounted. Two alternatives

are described below.

Since the data set is very similar to the data obtained from the LAX Basin

Model snapshots, a modified version of the procedures used to generate those snapshots

may be suitable. Experience gained in the Long Beach survey will also be used as a guide for the collection procedure. Observers stationed at the airport (at runways,

parking aprons, and gates) should record tail numbers and times for all departures

and arrivals during a 3-hour period. Other observers should question a sample of

pilots on the apron area to obtain information about VFR flight patterns and other

relevant matters. IFR flight strip data can be coordinated with the VFR data to

obtain input to the Digital Simulation Facility (DSF) at NAFEC or other simulation.

(The DSF takes as input a list of flights ordered by departure time and the route

flown by each flight together with other information (aircraft speed, for instance)

and produces instantaneous flight track data at preset short time intervals. The

number of routes which may be provided is limited and each route must contain

change points for altitude and heading. ) On-board avionics may be obtained from

the Aircraft Registration Data using the aircraft tail number, and avionics usage

may be assessed from the sampled questionnaire respondents. A special study of

communication activity rates may be required.

Several problems arise in conjunction with the above simulation process. The

limited number of available routes are used again and again, and the simulated

airspace is not utilized as uniformly as in the real world. This tends to obscure

anomalies and real situations which occur infrequently. Thus, for studies focussing

on infrequent events rather than the typical situation, the data are too averaged

to permit meaningful distinctions. In addition, the simulation procedures do not

take into account required mid-air separation criteria, so that unrealistic densities

occur. Some hand manipulation of 10 to 20% of the data points was required in the

LAX basin study to alleviate this condition. However, such manipulation may destroy

precisely those situations of interest to some studies (e.g., CAS).

A second method of obtaining current snapshot data would utilize a pilot

questionnaire to elicit the required data. A preliminary educational or promotional

program would be aimed at the aviation community in general and the GA segment in

particular. Questionnaires then would be distributed to all registered pilots, to

be filled in at a fixed instant or within a given 30-second interval in time, e.g.,

"1500 GMT adjusted to local time zone, Saturday, October 13, 1973." The information

to be entered could include aircraft type, flight origin and time of origin, destination

if known, and for the instant of recording, altitude, position, speed, bearing,

attitude and maneuvering if other than straight and level flight. This much information

can be accommodated on a short, easy-to-use form without unduly inconveniencing the

pilot.

The difficulties and uncertainties of this procedure are, of course, substantial.

First, there are analytical problems: temporal variations -- seasonal, day of week,

and hourly, and their interaction with regional factors. These will determine the

number of surveys to be made. Administrative and feasibility considerations are more serious. Pilot response to non-obligatory questionnaires could be poor. A

larger problem is that the variability in pilot cooperation is probably not all

random, but rather inversely related to the value of the desired information. Air

carrier pilots will likely exhibit the highest response rate and the most reliable

29
responses, while recreational pilots in small aircraft flying VFR, at whom the

survey is really aimed and for whose data there is no reliable, independent check,

may be the most recalcitrant. The bias arising from total non-response will be

compounded by those who avoid flying at the predetermined time of the survey so that they can evade the request to file a questionnaire "with a clear conscience."

Despite the disadvantages, the survey technique has the great advantage, if

response can be encouraged, of obtaining directly many of the data which must

otherwise be estimated roughly in a simulation procedure, and it should result in

better estimates of real world instantaneous separations, altitudes, and avionics

usage rates, none of which are presently known.

5.1.3 Forecasting Considerations

A method of "time compression" similar to that used in the 1982 LAX Basin

Study [7] can be used for forecasting. Let t^ be the departure time for a given

flight in the current sample, and suppose that the growth rate for this flight

category at this airport is g. Then the departure time for a similar flight in the

future sample would be t^ + (t^ - t^) /q where t^ is the start of the sample time

interval. To insure that the future sample time period is the same length as the

present, the flight is replicated by dividing the whole interval (say of length L)

into g sections and having the flight depart not only at t + (t-j^- t^)/g, but also

at t^ + (t-j^ - t^)/g + n • (L/g) for n = 1, 2, . . . , as long as the departure time

is within the present time period. An example is shown below to explain the procedure

more fully.

Example

:

Assume g = 2.3

t^ = 1.5 hours

t = 0 o

L = 3 At present we have a departure 1.5 hours after start:

0 1 2 3 (where the x represents a departure)

.

For the future we have:

I I ^—I 1 0 .65 1 1.95 2 3

since t^ + (t^ - t^)/g = .65 and t^ + (t^^ - t^)/g + 1 • (L/g) = 1.95 for L/g = 1.3

(Note: For n = 2, the next departure would be at 3.25, outside the time interval.

Separate growth rates were provided to the LAX Basin study for each departure airport,

category of flight rules, user category and aircraft type category.

Several problems arose in using this procedure for the LAX Basin model study. No

changes from year to year in altitudes, speeds, or avionics usage were assumed.

(Such changes can of course be exogenously imposed if they can be accurately forecast.)

Furthermore, the 1972 routes were also used for 1982; with the route restrictions

from using the DSF, this increases bunching of aircraft. A final and even more

important problem occurred when average growth rates were used in the LAX basin time

compression while the sample time period chosen had heavy traffic. This resulted in

departures at some airports violating separation criteria. One could envision using

a separate airport simulation to modify departure times to insure a reasonable separation. However, the problem of bunching on aircraft routes is not as easily solved,

and a further study of this problem is necessary to determine which technqiues are applicable to the route problem.

30
Whereas the first method described in 5.1.2 above for collecting a current base

for this data set is similar to the LAX Basin effort, and may be amenable to time

compression, it is not at all clear that the technique could be applied to the second

method, where data are recorded at only one point in time. The compression technique

generates data at many different time points and no data have been collected for the

other flights which should be included at those points. It might be possible to

replicate each flight at different points along its route as determined by a time

compression technique, but this would entail collecting route information initially.

A further investigation of forecasting techniques for use with an instantaneous

airborne sample should be pursued.

5.1.4 Potential Users

1. Frequency Spectrum Analysis

This data set will provide traffic data for analyzing how soon and where the

shortage of frequency bands available for ATC voice communication will become critical.

Frequency spectrum analysis will require peak traffic levels. Therefore, although it

is necessary to insure that any allocation would satisfy users throughout the country,

it is sufficient to focus on activity in those areas having the densest traffic, the

large hub areas. Although the desire was expressed for including all traffic in an ARTCC, a hub area of 120 miles in diameter would suffice at least for preliminary

analysis, since it would approximate the size of an ARTCC sector. A snapshot would

be the most useful form of presentation since it would give relative positions of the

aircraft in the hub area. Communication and navigation activity rates could then be

used in conjunction with maneuvering rates to determine which aircraft are utilizing

the frequency spectrum at any one instant and how they might interfere with one

another. Changes in equipment requirements could also be modeled. Thus a snapshot

of all traffic activity in several large hub areas would satisfy, to a great extent,

the requirements for frequency spectrum analysis.

2 . Studies for Which Accurate Representation of General Aviation Traffic

is Needed

Several studies which are concerned with the consequences of expanding some equipment usage to include all traffic or at least more of the GA traffic, have a self-evident need for GA data. Most such studies need the relative positions of

aircraft at a peak instant in time (although some may also require routes flown)

.

Traffic in a large hub area, including GA traffic from satellite non-tower airports,

will represent a worst-case situation upon which to test new requirements for GA

aircraft. Such data items as aircraft type, altitude, and whether a flight is local

or itinerant would be required, since GA flights undoubtedly differ more in profile

than do other categories of traffic with respect to these variables.

A primary factor in the acceptance of the LAX Basin Study was its detailed treatment o GA traffic which had been lacking in previous work. Any further traffic data sets

offered for general use throughout the Agency must also contain realistic data on GA

traffic

.

3 . Analysis of the Synchronous Garble Problem

The LAX Basin snapshots were used to perform this type of analysis under the

assumption that all aircraft were using transponders. The primary data required were three-dimensional positions, used to determine which other aircraft would interfere

with any particular aircraft. The analysis showed that the density of traffic in the

LAX basin in 1972 was so great that most beacon replies would be garbled if all

aircraft were using transponders. This problem raises the question as to whether it

is feasible or desirable to require that all flights, including VFR flights, use transponders. At the present time, an estimated 60,000 GA aircraft are transponderequipped, and this number is increasing.

4 . Analysis of Communications Requirements for the Upgraded Third Generation

(UTG) Equipment

A large part of the total communication activity is determined by the number of

potential conflicts and overtakes as well as the fraction of traffic maneuvering,

hence it is necessary to have relative positions of aircraft. The ratio of IFR to

VFR traffic is also desired.

31
Two items are not included in the Type 1 Terminal Data Set, namely (1) diurnal

variation to describe the duration of peak and near peak conditions and (2) ground

operations. Depending on the method used to obtain this data set, some data on duration of peaks may be available as a by-product of the collection process. In

addition, analysis may be useful to quantify the relationship between duration of

peaks and communication requirements. The general pattern of ground operations is a consequence of the traffic level and the physical facilities available; this relationship should permit simulation of ground operations, or perhaps a direct representation

of the dependence of communication activity upon traffic level and physical facilities

can be developed.

The analysis envisioned here emphasizes the general relationship between the

communications required and the traffic levels and patterns expected, rather than

direct information about the communication activity at any specific airport. Data on specific areas which are candidates for UTG equipment must be collected separately.

(It has been assumed from the outset that data commonalities would be stressed, and

that analyses which depend greatly on differences in data from different locations

could not be fully satisfied by this work.)

5. Analysis of TACAN/DME Saturation

A primary requirement for accomplishing the analysis of how soon the DME portion

of a VORTAC is saturated is information on which aircraft have and are using DME

equipment, both today and in the future. This information should be collected and

included in a current data set. In the event that forecasts may not be available,

several different levels of DME usage could be examined to assess the sensitivity of

saturation.

Some analysts expressed a desire for data covering quite large geographical

areas. However, it is felt that large hub areas should suffice since saturation

levels are desired, and only traffic within a comparatively small radius (say 40 or

50 miles) of a navaid would interrogate its DME equipment. Terminal Data Set - Type

1 should provide the essential information required for study of DME saturation,

namely the relative positions of aircraft interrogating the DME at any one time.

5. 2 Terminal Data Set - Type 2 5.2.1 Description

This data set will contain data for five to ten terminals where traffic (in

terms of volume of operations, aircraft type mix, user category mix, local/itinerant

ratio, and any other relevant factors) and configuration (in tenns of facilities,

runways, taxiways, weather, and geographical peculiarities) are representative of the

spectrum of those factors found among large and medium-sized terminals. The data set

for each airport will contain peak hour arrival and departure rates for all types of

air traffic. The fractions of arrivals and departures using each runway will be

specified; for each runway, the fractions of traffic which are IFR and VFR, the

fraction in each user category (AC, GA, and MI) , and the distribution of runway usage

by aircraft type category will be provided. In addition, the data will include the

fraction of each aircraft type carrying various kinds of avionics equipment, and the

average approach, lift-off, and the runway exit speeds.

5.2.2 Sources

Most of these data are already available at the three large New York area airports

(EWR, LGA, and JFK) from the CATER data, which includes for each operation: identification, time, type of operation (landing or takeoff), user category, category of flight

rules, aircraft type, and runway used. This type of data is potentially available at

any terminal at which flight strips are prepared for VFR flights as well as IFR

flights. The assigned runway must also be identified on the flight strip. The data

could certainly be obtained at any airport with a control tower by stationing extra

people in the tower to record the information for each flight.

Data concerning aircraft operating characteristics (such as average landing,

taxiing, and lift-off speeds and avionics carried) are available from other FAA

sources. Thus this data set is potentially available with a minimum of additional

work.

32
5.2.3 Forecasting

Forecasts now published by the FAA contain most of the types of data required

for this data set, except that busy hour operations are predicted for hub areas

rather than specific terminals. If a method can be found to modify hub forecasts or

to obtain terminal forecasts independently, the basic traffic forecasts will become

available. However, it will still be necessary to obtain information on runway

utilization. It may be possible to estimate runway usage by assuming that it depends

on aircraft type and that the present fraction of each type will be assigned to the

same runway in the future. Thus, given the fractions of each aircraft type using a given runway as calculated from 1972 data, the mix of aircraft types, and total

operations as already forecast by the FAA, one can estimate the number of aircraft

operations on each runway in 1982. If this estimate should exceed the runway capacity,

some diversion of aircraft to alternate runways may be necessary and decision rules

will have to be adopted at this point.

5.2.4 Potential Users

It is assumed that Terminal Data Set - Type 2 will be input to a user-designed

simulation or analytical model for each of the analyses described below. For example,

the data set will provide arrival rates for each runway, but an MLS study would have

to simulate any desired curved approaches. As a second example, the data set provides

arrival and departure rates by aircraft type category for today's conventional aircraft

types, but not projections for STOL type aircraft. Those analyzing STOL operations

would have the responsibility for such projections.

1 . Operational Analysis of a Micro-Wave Landing System (MLS)

As indicated above, it is assumed that simulation and analytical models will be

used to study MLS systems in an operational environment and that Terminal Data Set - Type 2 will provide the necessary inputs. The primary data requirement is the

number of each type of aircraft desiring to land on each runway in a given time

period. Discrimination among aircraft types must be maintained because the MLS

requires new equipment in the cockpit, and the fraction of aircraft possessing that

equipment may depend on aircraft type. (More expensive aircraft can be expected to

carry more equipment.) Peak conditions are the most relevant to test since it is for

them that the expeditious flow of landing traffic is most critical. The availability

of data for different terminals with different traffic characteristics may also allow

studies of trade-off between the benefits of an MLS system and the cost of its installation and operation.

2 . Analysis of Airport Surface Control Ground Guidance Systems

Terminal Data Set - Type 2 provides the traffic input data required to simulate

systems for guiding aircraft through complex runway and taxiway systems, the primary

need being information on the number of departures and arrivals for each runway in a given time period. The main tool for this analysis will be a simulation of the runway,

taxiway, apron, and gate areas of the airport surface. Times to taxi along various

parts of the system will not be provided in Terminal Data Set - Type 2, but taxiing

speeds will. The traffic data will also lack information on the actual taxiway system

and gate facilities at any airport; however, this information is available from other

sources

.

3 . Operational Analysis of STOL Systems

Terminal Data Set - Type 2 will provide input traffic data for a simulation of the

interactions of STOL and conventional traffic. The major required data items include

departures and arrivals on each runway by aircraft type. User category may be of value

in selecting the traffic replaced by STOL aircraft. Non-traffic data on airport

configurations and operating characteristics for conventional and STOL aircraft are also required.

It is assumed that a user-designed simulation will be the primary tool for analyzing

the operation of STOL aircraft in an environment including conventional aircraft. STOL

analysts will have to specify the market share allotted to STOL aircraft and to indicate

changes in the shares of other aircraft types. The data required to make such projections can be obtained from a study of the economic viability of the STOL concept in

various markets, together with projections of demand (in terms of the desired number of

trips) between pairs of cities suitable for STOL operations.

33
4 . Analysis of the Wake Turbulence Problem

Studies of the wake turbulence problem, its magnitude and the impact of increased

separation or other corrective procedures will require traffic data, primarily aircraft

type and runway utilization, as available from this data set.

More than likely, simulation will be a study tool, but analytical models of the

vortices created and their dissipation may also be required. (Again, these models must

be furnished by the user of the traffic data.) In addition to traffic data, data on runway configuration (in particular, the runway layout, including length, intersection

points, and relative positions) will have to be furnished. These data are not part of

the traffic data set, but are available from other FAA sources.

5. Analysis of Pollution Problems

The most critical data for analyzing the impact of air traffic on the noise and

air pollution of our cities are the levels of traffic landing on and taking off from

each runway and the distribution of runway usage by aircraft type. Peak traffic levels,

which contribute most to air pollution, are of greatest interest. However, peak air

traffic may not coincide with peak air pollution, for other factors (such as nonaviation pollution sources and atmospheric conditions) are significant.

The primary analytical tools are expected to be simulation or mathematical modeling.

Data such as emission rates or noise levels as a function of aircraft type will be

required, and departure/approach routes will have to be provided by those analyzing the

problem. The population distribution in the airport vicinity may also be required. In

order to assess the impact of aircraft-caused air pollution, pollution levels from

other sources must also be known. In addition, it may be desirable to have data on the

diurnal distribution of traffic, since the length of peak and near-peak conditions are relevant to pollution studies.

6 . Studies Concerning the Capacity of the Air System

Simulation and, possibly, mathematical models are the major tools available for

studying terminal capacity. The primary data requirement is the distribution of

landings and takeoffs by runway and the runway usage by aircraft type (since different

aircraft have different flight characteristics, such as speed, which affect runway

capacity) . Other necessary data include the mix of IFR/VFR traffic since different

separation rules apply. The duration of peak and near-peak conditions can affect

delays, so it is also desirable to have the diurnal variation of traffic level.

7 . Studies Which Require Accurate Representation of GA Traffic

The scarcity of data on VFR aircraft operations has made it difficult to assess

the impact on the ATC system of many proposed changes in FAA rules and procedures.

Better data on VFR activities are expected to be helpful for performing a number of

analyses

.

The primary data required are levels of terminal operations by user category (to

ascertain the fraction which is GA) , by category of flight rules and by aircraft type.

Some of the problems described above may require only those data for their analysis,

but others, particularly the evaluation of various rules changes, may require simulation

or mathematical models in addition to the traffic data. Since so little is now recorded

about actual patterns of GA traffic, any increase in knowledge about this segment of

the flying population enhances the FAA's ability in planning to accommodate GA traffic

in terminal areas.

5. 3 En Route Data Set - Type 1 5.3.1 Description

This data set will include for each departure in CONUS

:

1. flight or aircraft identification

2. origin airport

3. destination airport

4. route flown (airways or fixes)

5. departure time (GMT)

6. arrival time (GMT)

7. category of flight rules (IFR/VFR)

8. user category (AC, GA, or MI)

34
9. aircraft type category

10. assigned altitude

11. speed (preferably ground speed)

.' 12. avionics carried.

Users have expressed the desire to have these data for all aircraft for the period of a day, but since many GA flights in small aircraft never use the ATC system, it would be

difficult (if not impossible) to obtain these data on all flights. However, the users

named below may be able to perform their analyses using IFR flights plus those VFR

flights for which flight plans are filed. As with the Terminal Data Sets, models

specific to particular studies may be required to exploit and supplement the information

provided by the traffic data effort.

5.3.2 Sources

The data for this set are essentially available from the FAA IFR peak day sample

augmented by VFR traffic with filed flight plans. However, the peak day sample now consists of data based on the individual peaks of the various reporting ATC facilities;

it would be preferable to obtain these data for the same reporting period from each

facility. This requires selection of a common period which is most representative of a system-wide peak.

Two items (route flown and arrival time) are not now collected. Route flown might

be approximated from flight plan information, but this would require much hand-matching

of data. Route flown would also be directly available from the NAS computer system,

another source of the IFR data, since the route is part of a stored flight plan record.

Processing computer tape output from all 20 NAS centers would be a large job, but

the possible benefits might warrant the effort. In addition, once programs have been

written to accomplish this task, they could be repeated on future outputs. Arrival

time is not currently included in the computer system, nor will it be in the foreseeable

future. If and when metering and spacing programs are implemented at ARTS III terminals,

a "drop track" message will be relayed from ARTS to NAS when an aircraft is about 2 miles from touchdown. Such a message could be used as a surrogate for arrival when it

is implemented, but even then it will be available only at ARTS III terminals (and

possibly not even at all of these) . If route information is available through the NAS

computer output, it should also be possible to approximate arrival time from the last

reported time and fix. Though not taking into account the effect of terminal delay,

this would be better than approximations based on average speed for the whole route.

5.3.3 Forecasting

As for Terminal Data Set - Type 1, the method of forecasting should be some form

of time compression, hence practically all comments on that data set apply. Some

additional comments regarding the growth rates used in the time compression method of

forecasting follow.

Even though this data set applies to en route centers, the growth rates at terminal

areas are of primary concern: the method of forecasting must utilize the growth rates

for the origin-destination pair associated with each recorded flight record on the peak

day tapes. Before applying growth rates to the peak day records, an attempt should be

made to combine the growth rates at the origin and destination of each pair of airports

into a composite rate for the pair.

Procedures for combining growth rates are already available in the transportation

literature. A crude example, labeled the proportional trip distribution model by Potts

and Oliver [15] , yields

\

35
where d^_. is the forecast demand between airports i and j,

and g_. the predicted growth rates for airports i and j respectively,

and X. . is the current demand between i and j.

Changes in route structures will not be reflected in such a procedure, nor will

changes in altitudes flown and departure time distributions. Such changes must be

forecast separately and imposed exogenously.

5.3.4 Potential Users

1. Analysis of the RNAV Concept

Studies comparing usage of the RNAV system to that of the present system will

require simulation of both systems with the traffic data set described above as an

input. It will be necessary to designate which flights will use RNAV routes rather

than the routes given in the data set. (This breakdown of traffic into RNAV and non- RNAV is external to the traffic data effort, as will be the assignment of RNAV traffic

to RNAV-routes. ) The primary traffic data required by this study will be the origin,

destination and (conventional) route flown. Aircraft type and user category may also

be relevant in choosing whether a conventional or RNAV route will be used, since the

fraction of aircraft having RNAV equipment may vary with type and user category.

Thus, the En Route Data Set - Type 1 will contain the basic traffic data required for

a study of the RNAV system.

2 . Analysis of IFF/ECM Interference

The traffic data available in En Route Data Set Type 1 can be used to study how

often jammed IFF response might occur, to investigate methods for detecting deliberate

jamming, £ind to study means of identifying intruders in spite of the various interferences.

The main geographical areas of interest are along the boundaries of North America.

Data are needed for all traffic, including VFR, since any intruder would appear on radar similar to a VFR flight. However, due to the IFF problem, VFR flights in boundary

areas must file with the appropriate authorities, hence pertinent data should be

available. Route flown, or at least the intended route, is available from this data

set, but actual track (which may deviate from the route filed) will not be included.

Perhaps some statistical simulation model can be used to generate realistic deviations

from filed routes.

The data set, as described above, covers only CONUS , not all of North America.

It is hoped that some phases of the problem can be studied by using a sample of areas

in CONUS as representative of those required for the study. In any case, since this

analysis is unique in its requirement for detailed data over such a large geographical

area, its accommodation is impractical within the general-usage thrust of the traffic

data effort described here; perhaps the military would wish to undertake the requisite

data collection and study. Some areas of interest, such as the Gulf Coast, would be

included in the data set, and an analysis could be performed on these to yield at

least partial results.

3 . Analysis of the Capacity of the En Route ATC System

As with many other prospective .studies, simulation is expected to be the main

to'ol for the analysis of en route capacity. The En Route Data Set will provide

realistic peak traffic levels, but aclditional data will be required to establish a relationship between controller communication activity and aircraft maneuvers and to

relate controller workload to traffic levels and characteristics of a particular

sector. Sector boundaries will also be required. Measurement of the airways' absolute

capacity does not require traffic dat.a, but if delay is to be taken into account,

various levels of traffic may be required and would be available from this data set.

5. 4 En Route Data Set - Type 2 5.4.1 Description

The data sets described above apply to individual aircraft either directly or statistically generated. However, not. all analyses require such detailed data. The

data set described in this section conisists of peak instantaneous airborne aircraft

counts (lAC) for en route ATC sectors. A number of analysts have expressed the need

36
for peak lAC for each sector in CONUS. It is hoped that some classification of sectors

by such items as number of airways, number of airway intersections, number of towers,

or aircraft handled, etc., may be possible, so that instantaneous counts need be

obtained only for representative classes, rather than for all sectors. Although a desire was expressed for all traffic, the analyses described below all relate to the

ATC system, hence IFR traffic would be sufficient. Background counts of the number of

VFR aircraft, or at least the number of "blips" on the radar screen coincident with

the peak IFR count, are also desired. In addition to the lAC, the distributions of

various sorts of communications activity as functions of traffic level and sector

characteristics are required.

5.4.2 Sources

The main requirement, that for peak instantaneous IFR traffic counts for en route

sectors, can be met from the NAS computer diagnostic tapes. (See the Appendix for a more detailed description of NAS computer operation. ) The NAS computers must keep

track of the number of active flight records for each sector and the status of each.

Thus a special post-processing program would be written (or may already be available)

to process the NAS output off-line and obtain peak instantaneous counts.

A measure of the number of false radar returns may be obtained either by examining

radar scope pictures or from diagnostic output of the NAS tracking system. (The

latter is in the preliminary stages of implementation; more complete and detailed

information on its operation is required to evaluate this source more fully. ) A

separate analysis of communication activity as a function of traffic level and sector

characteristics may be required, or, at least an examination of current communication

studies which might shed light on the relationships between traffic and communication

activity levels.

5.4.3 Forecasting

It should not be too difficult to obtain the present day data for this data set,

assuming that sampling by class is possible. Forecasting these items, may, however,

prove to be much more difficult. One approach might be to develop a functional relationship among the sector characteristics defining the sectors in the data set, the

expected traffic levels which are currently being forecast for some of those characteristics, and the current instantaneous airborne counts. Such a functional relationship

would permit forecasts of future lAC's. Using cross-sectional data as a basis for

obtaining time-dependent estimates must be done with great care but may be the only

technique available here.

Insofar as predictions of background noise level are concerned, the only comment

is that this will probably involve analysis of radar capabilities.

5.4.4 Potential Users

1. Estimating the Required Size of NAS Stage A Computers

Computer size requirements being greatly affected by the amount of data to be

processed, traffic levels must be projected over the major portion of the equipment's

life. Only IFR traffic would be stored in the computer's data bank, but VFR traffic

causes primary radar returns as a background "noise" level which affects the amount of

processing required to discriminate IFR returns from the noise. Some indication of

this background level of non-IFR returns is therefore needed. Other required information, not directly related to traffic, includes number of sectors and characteristics

of the airway structure in each ARTCC, and should be available from sources other than

the traffic data sets. It is expected that predictions of the lAC will be input to

analytical models or equations which calculate parameters relevant to computer size.

Again, the design of such models and equations is not part of the effort described

here.

2 . Assigning Voice Communication Frequencies to En Route Sectors

The main traffic data required to analyze frequency assignment to sectors are those sectors' peak lAC's. Since voice communication must be available independent of

the environment, a worst case analysis using peak data is desirable. Actual position

within a sector can affect the degree to which signals from different aircraft in the same or different sectors can interfere with one another, but in the absence of actual

position data the worst case assumption can be applied. Along with the output of the

traffic data effort, sector boundary specifications and a model of frequency interactions are also required for this analysis.

37
3 . Analyzing the Communications Requirements for the Upgraded Third Generation

(UTG) System

Assessing the communications requirements generated by future ATC systems will

necessitate having peak traffic counts, as well as the distribution of communications

activity. The traffic data effort will include communications activity rates for the

current system configuration, but it will not relate these rates to the UTG system

specifications.

5 . 5 Oceanic Data Set

5.5.1 Description

This data set will be made up of all North Atlantic traffic including air carrier,

foreign flags, supplementals , military, and non-air carrier as well as traffic which

neither originates nor terminates in the U.S. The data will consist of the number of

flights per day between all pairs of cities. For each origin/destination pair, the

fraction of traffic using each oceanic route, the fraction of flights of each aircraft

type, the daily (actual) departure time distribution, and the distribution of flight

duration will be provided. In addition, the avionics carried by each aircraft type

category will be specified.

A simplified version might allot all flights for a given city pair to a single

route; provide the fraction of flights of each aircraft type for only three categories:

jet, large (4-engine or more) piston, small piston; and develop an assumed flight

duration. This might be enhanced by developing a set of departure time distributions

which depend not on city pair directly, but rather on the flight duration, with an offset to take into account the origin time zone. Although this data set would contain only North Atlantic traffic, there is also a requirement for other oceanic traffic, particularly for the Pacific. If the cost were

reasonable, it would be of great value to obtain these additional data, particularly

for assessing the effectiveness of world-wide oceanic navigation systems.

5.5.2 Sources

The Oceanic Data Set will necessitate a special collection effort since data are currently lacking for non-air carrier trans-oceanic flights. If all international

departure points, or alternatively, all coastal sectors, kept data for each oceanic

flight on one day, the data set could be constructed. Such an effort would, of course,

have to be coordinated by an international group such as ICAO, in order to obtain data

on all oceanic flights, including those which neither land in nor depart from the U.S.

It would be desirable to record departure and arrival times to construct distributions

by pairs of cities. If these times cannot be recorded, a special study of departure

time distributions for city pairs at various separations might be conducted. Such a construction implies that departure time distribution is primarily a function of the

travel time between two cities and of the origin time zone. The break in surveillance of trans-oceanic flights precludes obtaining the actual

track flown. A special study [13] to estimate mean deviation from nominal track for

the North Atlantic has been accomplished with a radar-equipped ship in mid-ocean under

one of the heavily traveled routes to record aircraft position.

5.5.3 Forecasting

The required data are similar to those required for En Route Data Set Type 2,

although not as detailed. A similar forecasting procedure might be applied if international flight growth rates can be estimated. As traffic increases, a study of the

growth rates for all countries which affect trans-oceanic flights would certainly be

desirable. Changes in departure time distributions may be predicted as a function of

changes in aircraft mix which reduce time between cities and expansions of traffic

levels which tend to flatten out peaks.

38
5.5.4 Potential Users ,

1 . Study of Oceanic Navigation Systems, Especially OMEGA

In order to assess the benefits of OMEGA with regard to increased safety or a reduction in the present trans-oceanic separation standards, trans-oceanic air traffic

data are needed. A desire was expressed for data on actual tracks flown in order to

evaluate the deviations from planned tracks under use of current navigation systems.

However, the lack of surveillance of trans-oceanic flights makes such data unavailable.

The Oceanic Data Set, though lacking track deviation data, would provide information

on actual traffic levels handled by the current system; this could be combined in a special study (not within the province of the traffic models effort) of track deviations

and their propagation when inertial navigation systems are used. Future traffic levels

could be used to assess the demands on a new navigation system. Of course, those

demands could include overland air transportation and ships at sea as well as transoceanic air traffic.

2 . Sizing Oceanic Sectors for NAS Stage A

The Oceanic Data Set would provide the necessary data for analysis of East Coast

sector sizing. Some modeling by the user would be required to pass from the basic

numbers provided by the data set to the desired peak instantaneous airborne counts.

Pacific sectors would not be included in the data set unless, as mentioned above, the

data collection is economically feasible. In the absence of West Coast data, the

sizing of Western oceanic sectors would lack a satisfactory empirical basis, hence

the data set is not wholly adequate for this application.

3 . Reconfiguring the Flight Information Regions (FIR'S)

The Oceanic Data Set would provide a valuable input to an analysis of the recon- figuration of fir's. These data would enter a user-developed model designed to simulate

aircraft movements along specified routes in order to determine such relevant factors

as instantaneous airborne counts for each region and the number of boundary crossings.

Departure time distribution is critical since the lAC is affected greatly by bunched

departures.

4 . Assessing Satellite Navigation Power Requirements

The determination of power requirements for a satellite system interrogated by

aircraft will depend on the expected number of interrogations which, in turn, requires

traffic data of the type described. These data would probably be input to a simulation

model which describes the aircraft movements and satellite interrogation rates.

6.0 FINDINGS AND RECOMMENDATIONS

The FAA Models Committee Report [17] recommended that, to decrease duplication of

effort and to ensure more consistent analysis of air traffic problems, a centralized

data collection, assimilation, and processing effort should be initiated to provide

common air traffic data for all FAA analyses. An initial effort designed to test

collection and forecasting methods, as well as to stimulate further discussion of

Agency needs, was undertaken during the Fall of 1972. This resulted in the LAX Basin

Model Study and a subsequent survey aimed primarily at general aviation flights at the

Long Beach, California airport.

After preliminary results of the LAX Basin Study were available, and concurrent

with the Long Beach Survey, the present study was initiated to investigate the feasibility of identifying common traffic data requirements and format, to consider related

data processing techniques (i.e., mathematical models, simulations, forecasting

techniques etc. )

, and to recommend courses of implementation action.

During this study, approximately 24 different FAA analyses requiring traffic data

were considered and interviews were conducted with the responsible analysts to determine

data requirements. Simultaneously, existing FAA data collection efforts and sources

were examined to assess the adequacy of current data availability and to examine those

requirements not satisfied. The major data lacks appeared to be concerned with VFR

aircraft and with instantaneous airborne positions. Recommendations for obtaining

those data are included in this report.

The needs having been identified, common requirements were grouped into five

different data sets consisting of the following information:

39
1. Instantaneous position data from several large terminal areas.

2. Arrival and departure rates from several large, medium, and small terminals.

3. Origin/Destination (0/D) data for all IFR and certain VFR flights for the

coterminous United States.

4. Peak IFR counts for ATC en route sectors.

5. Oceanic 0/D data for the North Atlantic.

A single data collection effort similar to the LAX Basin study would obtain

present-day values for Data Sets 1 and 2 for large terminals, if departure or arrival

runway is specified for each flight. Special care is required in collecting VFR data,

but preliminary results from the Long Beach survey indicate that, with sufficient

manpower familiar with the local air traffic situation, such a collection effort can provide valuable data not now available elsewhere. Additional data collection efforts

will be required to obtain Data Set 2 at small and medium airports, but the effort

required is significantly less than that for large terminals.

The IFR 0/D data required by Data Set 3 is currently available from each FAA

facility for a peak day. Therefore a special effort aimed at a single day of the year

is feasible, requiring only that reports be filed for that day in addition to the peak

day. This puts an additional demand on field personnel that may be avoided by processing

NAS and ARTS computer output tapes. The VFR 0/D data may be obtained from filed

flight plans, but some actual flights may not be recorded by this procedure. The peak

sector counts required by En Route Data Set Type 2 should also be available from offline processing of NAS computer outputs.

Collection of oceanic data for certain tracks between San Francisco/Los Angeles

and Hawaii started in December, 1973. North Atlantic 0/D data have been collected;

additional data collection efforts, coordinated by an international body such as ICAO, are possible.

Further collection efforts and analyses relating navigation and communications

activity to traffic levels and ATC system characteristics are required by many of the users interviewed.

Most analyses currently under way or anticipated require traffic data for some future date, usually about 10 years hence. Further investigation of forecasting

methods and their applicability to the data forms described above should be undertaken.

Preliminary analysis accomplished during this study indicates that a modification of

the time compression technique used in the LAX Basin Study may be appropriate for

forecasting the forms in Data Sets 1, 3, and 5. The forecast data required by Type 2 may be directly available from present FAA forecasts with only a slight variation

representing distribution among runways. Data Set 4 may require an entirely different

technique and must be studied further.

Five data sets (two each for the terminal and en route areas and one for oceanic

areas) have been identified as candidates which would satisfy a substantial portion of

air traffic situation data requirements for analyses of anticipated NAS problems.

Suggestions have been made as to sources and means for collecting the specified data,

as well as possible methods for projecting these data to future time horizons. The

study indicates the feasibility of establishing common data and sources to satisfy the

air traffic situation data requirements for the majority of NAS analyses. Furthermore, the practicality of gathering the data and the resources required were addressed

at a general level.

Priorities among the different data collection efforts depend upon the priorities

of the various user programs. Since this is subject to FAA and DOT policy decisions,

our recommendations are governed primarily by our assessment of the criticality of

current data gaps, rather than program priorities.

Since the most critical element of the NAS is the terminal area where the interaction of VFR and IFR operations is most visible, it is recommended that initial

efforts be directed toward collecting the data specified in Terminal Data Sets Types 1 and 2. The sample terminal areas for this pilot effort should be selected to provide

information required by some on-going studies. Additional objectives would be to

develop effective data collection and validation procedures and improved methodology

for forecasting air traffic information.

A collection effort has been considered in the Chicago area including not only

the O'Hare terminal area, but also the Chicago Center. The characteristics of Chicago

-- a high percentage of IFR operations and the large number of overflights, as contrasted

with Los Angeles or Miami -- make it a desirable area in which to perform such a

40
survey. Care should be taken to obtain the runway data from O'Hare for all departures

and arrivals so that the data may be used for both Terminal Data Sets. Other areas might be candidates for future surveys, such as New York with its 3 major airports,

Cleveland ARTCC with a large number of overflights, or Denver or Atlanta which have

been used for previous studies. The principal criteria should be that characteristics

be relatively distinctive and applicable to the analyses being performed.

Considerable emphasis has been placed here on the present lack of information on VFR operations and the need to correct this deficiency. The implementation of a pilot

program for the collection of Terminal Data Sets, Types 1 & 2, could provide more

information on VFR operations if the selected sample terminal areas contain satellite

general aviation airports. However, the patterns and habits of VFR operations conducted

in such environments probably differ from those at the smaller non-tower general

aviation airports, which are more isolated from the main streams of air traffic. As

has been pointed out, the latter VFR operations may represent a substantial portion of

total VFR activity which is not included in present FAA traffic counts. It is therefore

recommended that a representative sample of small airports be surveyed in several

areas of the CONUS using a modified Long Beach technique. The information thus

collected would be a significant input for improved general aviation forecasts.

41
APPENDIX A

POTENTIAL OF THE TRAFFIC DATA IN NAS STAGE A & ARTS III COMPUTERS

The recently installed NAS Stage A and ARTS III Systems change the nation's air

traffic control system from a manual operation to a semi-automated one. This is only

the first step toward a more complete automation of the ATC System.

There are actually many models and versions of NAS Stage A and ARTS III systems.

Basically, however, each system consists of the three following major sub-systems:

• Data Acquisition Subsystem: Digitizes the radar and beacon data and transmits

them to the central computer

• Data Processing Subsystem: The central computer complex which controls the

peripheral equipment as well as the data processing.

• Display Subsystem: Processes and controls the data for display.

Individual installations of each of the above subsystems differ in both hardware

and software aspects. In fact, equipment modification at the various centers and

terminals has been a continuous effort, and no one individual, at this stage of

implementation, is familiar with all of the detailed changes among the various models

and versions of NAS Stage A and ARTS III systems.

The amount of data processed by the en route or terminal computers is immense,

containing information for computer command, radar beacon signals, weather maps,

flight plans, etc. However, the data of major interest to this effort are those

related to air traffic.

The air traffic data available in the en route and terminal computers are especially useful in two respects: (1) the computer data contain real time air

traffic information, rather than monthly or yearly average data; and (2) they provide

precise track information for each aircraft.

The following sections will briefly outline the data flow (traffic data only)

in the NAS Stage A and ARTS III Systems.

NAS Stage A

Figure A.l shows the data flows in the NAS Stage A System. The NAS Stage A

System has the option of transferring the data from the core storage of the Central

Computer Complex (an IBM 9020 computer) to the System Analysis Recording (SAR)

tape. The resulting SAR tape is processed off-line by programs in the NAS Operational

Support System (NOSS) , a large utility system consisting of many parts. Those of

interest to this effort are the Data Reduction & Analysis (DR&A) programs. The DR&A

programs as currently constituted deal not only with traffic information, but also

certain monitoring functions.

The functions of the various programs in the DR&A are summarized below:

Station Log Program: Analyzes the messages which have been recorded on the SAR tape

file and determines the message type, station, aircraft identification, time,

device, etc.

Flight Plan Data Base Analysis Program: Prints information concerning dynamic data

pertaining to a given aircraft whenever any external controller's actions are entered into the computer for that aircraft.

Input/Output Message Summary Program: Summarizes all I/O data for all operational

positions, sectors, and devices.

Track Data Base Analysis Program: Displays and calculates selected information from

the track data base approximately every 5 seconds.

Track Data Base Analysis Summary: Summarizes and provides statistics on the data

selected by the Chronological Log Program. > Radar Track History Program: Provides a history of a subset of the total number of

tracks in the system. All of the radar data pertaining to a given selected

track are listed once every second. Other listed data include time the data were

received, plus the track, radar, and computer identifications.

42
f INPUT OUTPUT

Flight Plans

from FSS, Tower,

Other ARTCC,

Pref iled Controller

Displays

Radar and

Beacon Returns

Controller

Entered Data

IBM

9020

Computer

Printed

pFlight

Strips

Flight Plans to

Other ARTCC and

• Tower

Meteorological

Data

SAR

Tape

)

FIGURE A.l: DATA FLOWS IN THE NAS STAGE A SYSTEM

43
ARTS III

The terminal computer system has parts corresponding to those in the en route

system. The data flows in the ARTS III system are similar to those in NAS Stage A. The

output tape of the Data Extractor Routine corresponds to the SAR tape in the en route

system, and has several options to extract data depending on user needs.

The extraction tape can be processed further off-line by the Data Reduction

Program which corresponds to the DR & A programs in the en route system, but is less

extensive. The output items and their functions are shown below:

Sector Time: Provides the current time and the types of beacon subsystem.

DAS Reports: Contains types of beacon subsystems, azimuth, ranges, beacon code and

beacon mode.

DAS Replies: Contains types of beacon subsystem reply condition, azimuth, beacon

code and range.

Tracking Message: Contains current time, aircraft identification, altitude, assigned

and reported beacon code, azimuth, range, X and Y coordinates, and velocity.

Keyboard Input: Provides current time, aircraft, identification, altitude and the

message.

Auto Functions: Provides aircraft identification, altitude, mode of auto functions

(e.g., auto acquire, auto assign code, etc.)

Arrival Flight Plan Message from ARTCC to ARTS III: Consists of current time, ARTCC

identification, message number, flight plan, aircraft identification, arrival

coordination fix, arrival coordination time at coordination fix, altitude and

airport of intended landing.

Departure Flight Plan Message from ARTCC to ARTS III: Consists of current time, ARTCC

identification, message number, flight plan, aircraft identification, departure

point, assigned beacon code, departure coordination fix, proposed departure

coordination time and altitude.

Beacon Identification: Consists of current time, trial track, assigned beacon code,

azimuth range, X and Y coordinates, and velocity.

Trial Track: Consists of current time, trial track, assigned beacon code, azimuth,

range, X and Y coordinates and velocity.

Discussion

The NAS Stage A and ARTS III Systems will certainly change the availability and

composition of traffic data. Currently 20 ARTCC 's and 61 of the nation's busiest

airport terminals are equipped with either the NAS Stage A or ARTS III Systems. These

61 airports serve about 70% of the total domestically enplaned passengers and 38% of

all itinerant operations at FAA-operated airport traffic control towers [6] . By 1980

there will be 200 ARTS III Systems installed nationwide [2] . The NAS Stage A, model 3D

system will have both beacon tracking and radar tracking capability [10] , and is

currently being installed in place of the original version of the en route system. The

current ARTS III Systems have only a beacon tracking capability and can thus track only

those aircraft equipped with transponders. It is estimated that about 60% of the

aircraft in GA fleet are presently equipped with transponders, and this number is

expected to increase in the future. However, an add-on primary radar tracking subsystem

has been developed for the ARTS III System [5] . Test and evaluation [4] of this subsystem

show that the radar-only tracking feature is satisfactory, and that the radar tracking

reliability for large aircraft is comparable to that for beacon tracking. All of these

improvements tend gradually to narrow down the VFR data gap. However, this gap may

never be completely closed because about 80% of airports in this country do not have

any kind of FAA control facility and neither primary radar tracking nor beacon tracking

is 100% reliable.

Analyzing the NAS Stage A and ARTS III traffic data may be costly and difficult,

primarily because of the immense volume of traffic information recorded by the computers.

For example, on a typical day at the Cleveland ARTCC, in a 13-hour span (from 1420

44
Aug. 10, 73 to 0330 Aug. 11, 73), nine reels of SAR tapes were generated.* The average

time span covered by each tape was 1 hour and 28 minutes, the exact time span depending

on traffic conditions. The situation is similar for the terminal system. The ARTS III can record on one extraction tape (2400 ft., 200 bpi) about 2 hours of traffic** dependi

upon the traffic condition and the kind of information being recorded. To merge and

combine the data tapes recorded at different centers and terminals increases the cost

and difficulty by an order of magnitude, particularly since output tapes from different

ATC facilities may not be compatible.

The volume of air traffic data generated by the NAS Stage A and ARTS III systems

creates a requirement for great care and effort in selecting only those data which are necessary for analytical purposes.

* Dr. Jan Shannon, ARD 110, FAA, private communication.

**Joseph Kowalewski, NAFEC, private communication.
REFERENCES

[1] Airport Activity Statistics for the Certified Route Air Carriers, prepared jointly

by the Civil Aeronautics Board and the Federal Aviation Administration.

[2] Air Traffic Control, Part 1, Sperry Rand Engineer Review (1971).

[3] Air Traffic Patterns for IFR and VFR Aviation - Calendar Year 1971, Department

of Transportation, Federal Aviation Administration (June 1972)

.

[4] Augmented Radar Beacon Tracking Level, Test and Evaluation Report, UNIVAC (April,

1973)

.

[5] Augmented Radar Beacon Tracking Level System Design Data, UNIVAC (Nov. 72)

.

[6] Automated Terminal Radar System III (ARTS III) Benefits, Technical Analysis Division,

National Bureau of Standards (May, 1971)

.

[7] S. Cohen and F. Maginnis, Extrapolation Methodology Used in the Los Angeles Basin

Standard Traffic Model, MITRE Technical Report Number 6386, (April, 1973).

[8] S. Cohen and F. Maginnis, Statistical Summary for Los Angeles Basin Standard

Traffic Model, MITRE Technical Report 6387, (April, 1973).

[9] S. Cohen and F. Maginnis, User's Manual for the Los Angeles Basin Standard

Traffic Model, MITRE Technical Report Number 6377, (April 1973).

[10] Concepts, Design and Description for the Upgraded Third Generation Air Traffic

Control System, CONUS ATC System, (Jan. 1972)

,

[11] FAA Air Traffic Activity - Calendar Year 1971, Department of Transportation,

Federal Aviation Administration (February 1972)

.

[12] FAA Statistical Handbook of Aviation, Department of Transportation, Federal

Aviation Administration, (1970).

[13] Oceanic ATC Surveillance Systems Study, by Systems Control, Inc., 260 Sheridan

Ave., Palo Alto, Cal. (February 1973).

[14] Official Airline Guide, Reuben H. Donnelley Corporation, 2000 Clearwater Drive,

Oak Brook, 111. 60521.

[15] Renfrey B. Potts and Robert M. Oliver, Flows in Transportation Networks , Academic

Press, (1972), pp. 123-130.

[16] Report of the Department of Transportation Air Traffic Control Advisory Committee,

U. S. Government Printing Office, Washington, D. C. 20402 (December 1969)

.

[17] Report of the Traffic Models Committee for the Office of Systems Engineering

Management, Federal Aviation Administration.

[18] Terminal Area Forecast 1974-1984, Department of Transportation, Federal Aviation

Administration (October 1972)

.

46
GLOSSARY

AC Air Carrier I/O Input/output

a/

c

Aircraft JFK John F. Kennedy International

ARTCC Air Route Traffic Control Center Airport

ARTS III Automated Radar Terminal kHz Kilohertz

System LAX Los Angeles International Airport

ATC Air Traffic Control LGA LaGuardia International Airport

ATCAC Air Traffic Control Advisory LlOll Lockheed Tristar Aircraft

Committee MI Military

B747 Boeing 747 Aircraft MITRE the MITRE Corporation

CAB Civil Aeronautics Board MLS Microwave Landing System

CAP Civil Air Patrol NAFEC National Aviation Facilities

CAS Collision Avoidance System Experimental Center

CATER Collection and Analysis of NAS National Airspace System

Terminal Record NAS

CONUb Continental United States Stage A Enroute Automation Program

CSC Computer Sciences Corporation NOAA National Oceanic and Atmospheric

CS/T Combined Station/Tower Administration

DAS Data Acquisition System 0/D Origin/Destination

DCA Washington National Airport OMEGA Long range navigation system

DCIO Douglas 10 Aircraft ORD O'Hare International Airport

DME Distance Measuring Equipment RNAV Area Navigation

DOT Department of Transportation RSM Requirements Source Matrix

DR&A Data Reduction and Analysis SAR System Analysis and Recording

DSF Digital Simulation Facility SID Standard Instrument Departure

ECAC Electromagnetic Compatibility SMSA Standard Metropolitan Statistical

Analysis Center Area

ECM Electromagnetic Countermeasure STAR Standard Terminal Arrival Route

Newark Airport STOL Short Takeoff and Landing

r AA Federal Aviation Administration TACAN Tactical Air Navigation

Flight Information Region TCA Terminal Control Area

FSS Flight Service Station uhf Ultrahigh Frequency

FY Fiscal Year UTG Upgraded Third Generation

GA General Aviation VFR Visual Flight Rules

GMT Greenwich Mean Time vhf Very High Frequency

lAC Instantaneous Airborne Count vlf Very Low Frequency

TP AO J.n uernauionax t-ivxx Aviation VOR veiry riign r jreguency L'ruriiira.ngc

Organization Station

IFF Identification - Friend or Foe VORTAC Co-located VOR and TACAN

IFR Instrument Flight Rules

IFSS International Flight Service

Station

ILS Instrument Landing System

47

N3S-1 I4A (rt£v. /-vjl

U.S. DIPT. OF COMM.

BIBLIOGRAPHIC DATA

SHEHT

1. PUPiLK ;A I"I0N ok Klil'UK 1 N't). NBS IR 73-4222. Cmv't Aftfssinn

No.

3. Kc c ij)U 111 's Ac cession .\o.

4. titl'l: .a.M) Si n riTi.i;

A Gtudy of Air Traffic Data RequirsKier.ts and Sources tor

FAA Analyses

5. 1 'uhl K it ion Date May, 1974

6. I'l'rforniins; Organization Codo

vvij-xiani r . urucKenjDrou / juaitn r . vjixsxnn,

'Rirhard H. . .Tack-soa,—Lambert "a.—Joel , —lao K. Slinn— . ... . ...

8. Perforniirif; Organ. Report No. MBS IR 73-422

9. PERHORMl.NG ORGANIZATION NAME AND ADDRESS

NATIONAL BUREAU OF STANDARDS

DEPARTMENT OF COMMERCE

WASHINGTON, D.C. 20234

10. Project /Ta.sk/Work Unit No.

11. Contract. Grant No.

12. Sponsoring Organization Namt- and Complete Address (Street, City, State, ZIP)

Federal Aviation Administration

800 Independence Avenue

Washington, D. C. 20003

13. Type of Report & Period

Covirred FINAL

14. Sponsoring Agcncv Code

15. SUPPLH.MtNTARY NOTtS

16. ABSTRACT (A 200-word or less tactual summary ol most si^ilicant information. If document includes a significant

bibliography or literature survey, mention it here.)

This report describes activities undertaken to assess the practicability of establishing

a single file or a set of files of standard reference air traffic data samples. These

files would serve as a common data base for ongoing and anticipated future forecast

and analytical investigations relevant to the accommodation of air traffic in the

National Airspace System.

The study entailed surveys of past and present air traffic data collection activities,

of existing data files, and of all identifiable users of air traffic data within the

FAA, as well as FAA contractors whose work requires air traffic data.

The information resulting from these surveys has been evaluated and aggregated to

identify data which will satisfy most of the requirements expressed by the data users.

T'vo data sets are specified for terminal area requirements, two sets for en route

requirements, and one set for oceanic requirements. These data sets will satisfy

most input requirements for all anticipated analysis efforts. However, depending

on the type of study, supplemental information, which is identified in various parts

of this report, will be required in some cases.

17. KEY WORDS (six to twelve entries; alphabetical order; capitalize only the first letter of the first key tvord unless a proper nams; separated by semicolons)

Air traffic analyses; air traffic data; standard reference air traffic data; users

of air traffic data.

13. AVAILABILITY Unlimited

I For f).fficial Distribution. Do Not Release to NTIS

Order Fro.n Sup. of Doc, U.S. Government Printing Office Washington, D.C. 20 102, SD r^t. \ >. C • ^

!

' Order I- rom National 'I cchnical Information Service (N I IS) Springfield, Virginia 2215!

19. SECURITY CLA.SS (THIS REPORT)

UNCLASSIFIED

20. SEC;UR1TV CLASS

n iliS PAGE)

UNCLASSIFIED

21. NO. OF PAGES

47

22. Price


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