Mixed Equipage Estimates in NAS 

Performance

Joseph Post, Systems Engineering and Integration

August 13, 2015
Outline

• Background

• MITRE Avionics Equipage Initiative

• FAA System-Wide Modeling

• NextGen Business Case

2
Background – FAA Planning

• NextGen Organization Responsibilities

 Early lifecycle cost-benefit analysis

 Portfolio trade studies

 Enterprise modeling and analysis

 Enterprise risk analysis

• Program Management Office (PMO)

Responsibilities

 Detailed program cost-benefit analysis

 Program trade studies

 Program modeling and Analysis

 Program risk analysis

3
MITRE Avionics Equipage Initiative

• Primary source of fleet equipage data for NextGen analyses

• Data on current levels of Part 121 fleet equipage by capability

• Ad hoc assessments of current and forecast equipage by 

specific capability, location, or sub-fleet

• Cost estimating capability

 Estimates of the cost to bring the existing Part 121 fleet up to X% equipped 

for any combination of capabilities 

4
MITRE’s Equipage Database

• MITRE CAASD has developed a detailed database of equipage by airframe

• By working with individual air carriers, MITRE estimates exactly what 

avionics are on each aircraft

 This level of detail is important. The specific equipment that an aircraft 

has on board determines the cost and feasibility of upgrading

• FAA’s Systems Analysis & Modeling Division uses this information for 

modeling the benefits of those operational improvements which depend on 

equipage, e.g.,

 RNAV and RNP procedures

 Lower RVR minima

 Clearance delivery via Data Comm 

 GBAS approaches
FAR Part 121 Avionics Enablers: 

Current Status of Equipage and Approvals

Note: “OpSpec Approved” based on issuance of Operations Specification

“NSOA” (No Specific Ops Approval Available) indicates capability not covered by a specific Operations Specification

“NOR” (No Ops Approval Required) indicates capability does not require ops approval for utilization

U.S. FAR Part 121 Fleet

6494 airplanes

82 operators

6
MITRE’s avionicsCoster

• MITRE CAASD has leveraged it’s in house database to create a tool for 

NextGen Systems Analysis that can be used to generate the estimated 

forward-fit and retro-fit costs to reach a specified level of equipage

• This capability is particularly useful to ANG, as it does not double-count 

the cost of duplicate equipment

• For example, if a particular aircraft would require the same FMS 

upgrade for both RNP and Advanced Interval Management, the cost of 

this upgrade would only be counted once for such a bundle

• This will be the first year that we will utilize the avionicsCoster for our 

NextGen Business Case, and it is going to make our cost estimates 

more realistic, and lower than in the past
System-Wide Analysis Capability

• FAA's fast-time NAS-wide model

 Builds upon and replaces National Airspace System Performance 

Analysis Capability (NASPAC)

 Discrete-event queuing model

 Can be stopped and restarted, allowing dynamic responses

• Re-routing

• Traffic Flow Management (TFM)

• Improved demand and trajectory generation approach

• Aircraft equipage aware

• Completely new software

 Fortran, C, Pascal, SIMSCRIPT II.5 → Java

 Sun Solaris → Linux

• Platform independence

 Multi-processing architecture

8
SWAC Functional Diagram

9

Trajectory

Model

Aircraft Performance

Future

Schedule

Generator

ORD Forecast Operations

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

200720082009201020112012201320142015201620172018

Fiscal Year

Total Annual Operations

Operations Forecast

Fleet Forecast

ETMS Data

 

0

10

20

30

40

50

60

70

80

4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Local Hour

Operations (/15 min. epoch)

2007 Baseline Cap 2015_Baseline 2015-Trimmed

Unconstrained

Schedules

0

20

40

60

80

100

120

140

0 20 40 60 80 100 120

Departures (/hr)

Arrlivals (/hr)

VMC

MMC

IMC

Airport Capacities

 

0

10

20

30

40

50

60

70

80

4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Local Hour

Operations (/15 min. epoch)

Industry/ 2007 Baseline Cap 2015_Baseline 2015-Trimmed

Regulator

Response

Constrained

Schedules

Queuing

Model

Sector Capacities

0

500

1,000

1,500

2,000

2,500

3,000

3,500

20082009201020112012201320142015201620172018

Number of Aircraft

Delay Fuel

Weather
NAS Resources Represented by SWAC

Domestic Airspace Airports (including Surface)

Oceanic Airspace Arrival/Departure Fixes

& Restrictions

10
Aircraft Trajectory Representation

• Waypoints / cruise alt. 

 Traffic Flow Management System (TFMS) flight plan

• Arrival/departure procedures

 SIDs/STARs appended to trajectories

for specified airports

 Approach Procedures also appended

 Includes altitude restrictions

 Aircraft type/equipage can be used

• Weather data 

 NCEP/NCAR Global Reanalysis Model

 METAR surface weather observations

• Aircraft performance 

 Eurocontrol BADA 3.11+

 4D trajectory computed at 1 min. intervals

11
• Produced using MITRE’s 

runwaySimulator model for 

58 airports

• Represent maximum 

sustainable arrivaldeparture combinations

• Adjusted for:

 Anticipated NextGen 

improvements

 Anticipated runway extensions 

and additions

 Meteorological conditions

• Curves created for all years 

out to FY25 and beyond

• An additional 252 airport 

capacities included without 

NextGen improvements

Airport Capacity Pareto Curves

12
SWAC Airports

13

• All IFR operations are modeled

• Currently 310 airports are represented with capacity curves

Guam
Oceanic Modeling

SWAC represents two oceanic effects: in trail spacing and step climb blocking

• In trail (i.e., longitudinal) spacing is imposed at entry to oceanic airspace

 Restrictions are 60 nmi in length, 1,000 ft. in height

 Restrictions are sensitive to aircraft equipage (spacing can vary)

 Approx. 31,000 restrictions are currently being used

• Step climbs requested in oceanic airspace as demanded by flight 

performance model

 A probabilistic model is used to determine if climb is conflict free

• Probability determined by traffic density and separation standard

 A blocked flight is forced to fly at suboptimal altitude until that flight can “try again” 

to request a climb

14
Surface Modeling

Surface operations are represented 

by a sequence of queues and 

transits:

 Taxi-In queues

• Airport-specific congestion-based taxi-in times

• Ramp queues (coming soon)

 At Gate queues

• Airport, aircraft type, and airline-specific 

turnaround times

• Queues to check adherence to scheduled times 

and EDCT

• Gate holding queue for Departure Flow 

Management

 Taxi-Out queues

• Ramp queues (coming soon)

• Airport-specific congestion-based taxi-in times

• Queue to check adherence to EDCT

• Queue at runway for take-off

15
16

Rerouting

• Two-dimensional re-routing to avoid weather polygons, Special Activity Airspace 

(SAA), or regions of system outages

• User specifies

 Polygons

 Active times

 Look-ahead times
17

Monte Carlo Capability

• System-wide models traditionally have produced point estimates

• SWAC now allows randomization of select input parameters

• Select output variables can be aggregated across an arbitrary 

number of model replications, yielding interval estimates
18

Terminal Congestion Management

• Traffic now metered to 

TRACON based on 

arrival queue length

• User specifies queue 

length to start and stop 

metering
19

• Module imposes GDPs and assigns expected departure clearance 

times 

 Weather dependent airport capacities

 Ration By Schedule (RBS)

• Distance-based exemptions

• International exemptions

• Airport specific GDP triggers 

 Max flight delay

 Max queue length

• Dynamic framework

 GDP slot assignments revised based on

simulation state

 User-specified update interval

Ground Delay Program (GDP)

Generator
Passenger Flow Model

• Passenger Origin/Destination demand taken from 

DoT DB1B data

• Passengers fit onto SWAC flights to satisfy O/D 

demand

 Direct flights preferred

 Itineraries with one transfer possible

• Based on flight leg delay, passengers may miss 

connections

 Re-booked to final destination if possible; if not, 

counted as “stranded”

• Passenger delay calculated relative to arrival time 

of original passenger itinerary

 Not just delay of individual flight legs
21

• Comm/NAV/Surveillance capabilities can be 

assigned to specific aircraft, e.g.,

 DataComm 

 ADS-B In and Out

 PBN: RNAV and RNP

 Category II/III ILS

 EVS/SVS

• Future fleet equipage may be scheduled 

 User-specified forecast

• Various simulation elements may be varied 

based on equipage

 Airport capacities

 Sector capacities

 Flight paths

 Cruise altitudes

 Airspace restriction intervals

Avionics Equipage Sensitivity

0%

20%

40%

60%

80%

100%

2009

201020112012201320142015

2016201720182019202020212022202320242025202620272028

20292030203120322033

20342035

Aircraft with Equipped 

Capability (%)

Calendar Year

Major Airlines Forecast Scenarios

PBN Equipped Capability

RNAV - 1, RNAV - 2

RNP - 0.3

RNP - 0.3 with RF

RNP AR

Notional PBN Forecast

Air Transport 

ADS-B Equipage

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

200920102011201220132014201520162017201820192020

202120222023202420252026202720282029

203020312032203320342035

Year End

Scen A: ADS-B Out&In

Scen B: ADS-B Out

Scen B: ADS-B In

Notional ADS-B Forecast
NextGen Business Case

SWAC Experiment Design

22

Two scenarios examined:

1. "Runways" Scenario

– New runways, runway extensions, and airport 

configurations included as they are projected to occur

2. “NextGen” ≡ Runways + ATM Improvements

– New runways, runway extensions, and airport 

configurations included as they are projected to occur

– NextGen technologies and procedures also included

The difference between these two scenarios represents the "benefit" of NextGen
Sample Day Selection

• 16 sample days selected by the Office of Performance Analysis to 

represent the year for fast-time modeling purposes

• Optimization technique (mixed integer program) used to select days 

in order to minimize the weighted difference for defined metrics 

between the true population and the sample

 Metrics include total delay, IMC delay, and operations counts at Core 30 

airports; operations counts and flight durations at 20 ARTCCs.

• Updated annually

23
Traffic Growth

• Future traffic assumptions based on FAA Terminal Area Forecast 

(TAF) and international traffic forecast

• Fratar algorithm used to convert airport-level operations forecasts 

(from TAF) to origin-destination forecasts

• Flight plans from 16 sample days randomly chosen to create specific 

flight itineraries

 Departure times varied randomly (within specified limits)

• Attributes of flight objects representing avionics then assigned 

according to forecast details

24
Operational Improvements Modeled in SWAC

25

Automation Support for Separation Management Performance-Based Navigation

A: Implement TMA at Additional Airports (104115-12) A: RNAV SIDs/STARs (107103-13)

A: Extended Metering (104120-11) A: OAPM (108209-12)

A: Use RNAV Data to Calculate Trajectories (104123-11) A: Transition to PBN Routing for Cruise Operations (108209-14)

A: Ground-Based Interval Management (104123-12) B: Speed Advisory Support for Merging Aircraft on RNAV Procedures (108209-15)

B: Interval Management – Cruise (102118-21) B: Improved Arrival and Departure Management: Airspace Enhancements (104122-23)

B: Meet TBFM Constraints Using RTA Capability (104120-22) Separation Management

B: Time-Based Metering in the Terminal Environment (104128-24) A: Wake Re-Categorization Phase I (102154-11)

Improved Multiple Runway Operations A: ADS-B Separation (102123)

A: Wake Turbulence Mitigation for Departures (102140) B: Initial Conflict Resolution Advisories (102114)

A: 7110.308 Procedure (102141-11) B: Automation Support for Separation Management (102137)

A: Wake Turbulence Mitigation for Arrivals - Procedure (102144-11) B: Space-Based ADS-B (102137-33)

A: Independent Runway Separation Standards (102141-13) B: Expanded Use of 3 nmi Separation in Transition Airspace (104122-21)

A: Dependent Runway Separation Standards (102141-14) B: Wake Re-Categorization Phase II (102154-21)

B: Paired Approaches for Runways Spaced Less Than 2,500 ft. CAT I (102141-21) B: Interval Management – Defined Interval (102148-01)

B: Paired Approaches for Runways Spaced Less Than 2,500 ft. CAT II (102141-25) Surface

B: Wake Turbulence Mitigation for Arrivals – System (102144-21) A: Initial Surface Management System (104209-17)

Improved Approaches and Low-Visibility Ops B: Remote Operations at Non-Towered Airports (102153-02)

A: Initial Tailored Arrivals (104124-11) CATM

A: Optimized Profile Descents (104124-12) B: Flexible Airspace Management (108206)

A: GBAS Category I (107107-11) NAS Infrastructure

A: EFVS to 100 ft. (107117-11) B: Initial En Route DataComm Services

A: EFVS to Touchdown (107118-11)

Note that not all increments of the indicated operational improvements have been modeled, and in some cases like operational improvements have been combined for 

modeling purposes.
SWAC Test Matrix

26

18 Years

16 Days

576 Cases!

10/1/2011

10/30/2011

11/17/2011

12/19/2011

2/4/2012

2/28/2012

3/16/2012

3/20/2012

4/30/2012

5/4/2012

5/13/2012

6/11/2012

7/14/2012

7/25/2012

7/30/2012

9/5/2012

201320142015201620172018201920202021202220232024202520262027202820292030
Output Metrics

27

All IFR operations in U.S. Flight Information Regions (FIR)

Total delay includes push-back, taxi out, 

airborne, and taxi-in delay

SWAC output metrics include total IFR flights, flight segment delay 

(gate, surface, airborne), cancellations, fuel burn (entire flight, U.S. 

airspace), passenger delay

Annual Total Flight Segment Delay
28

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Questions?

nextgen@faa.gov