© 2015 The MITRE Corporation. All rights reserved. 

# George Solomos David Hechtman

Nina Mohleji Bill Swedish

Jennifer Gentry Peter Kuzminski

Keith Baldwin Diane Boone

Mark Huberdeau Nazanin Bonds

Erin Catlett Mike Callaham 

# Reference Material for JFK, LGA, and

EWR Analyses Center for Advanced Aviation System Development



# 3 March 2015| 2 |

© 2015 The MITRE Corporation. All rights reserved. 

# NPRM Reference| 3 |

© 2015 The MITRE Corporation. All rights reserved. 

# § Use Called Rates

– Sum of Called Rates for Total Ops



# § Use Actual Rates

– Sum of Actual Rates for Total Ops



# § Actual Rate if Above Called



# § Use Max of Total Called rate or total actual rate for Total Ops



# § Use [Total Ops – Actual Rate Above Called] to set final rate



# § Note: assumes 1 for 1 tradeoff 

# Derivation of Adjusted Capacities

When Both Actual Rates Below Called Rate

When Both Actual Rates Above Called Rate

When One Rate Above and One Below Called Rate| 4 |

© 2015 The MITRE Corporation. All rights reserved. 

# NPRM Reference| 5 |

© 2015 The MITRE Corporation. All rights reserved. 

# Target Performance Goals By Airport (Modeled)| 6 |

© 2015 The MITRE Corporation. All rights reserved. 

# NPRM Reference| 7 |

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# Capacity Input:

Adjusted Capacities at JFK (Arrivals Plus Departures)

J A S O N D J F M A J J A S O N D M J F M A J J M 2005 2006 2007 74.6 79.2 81.2

77.1| 8 |

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# NPRM Reference| 9 |

© 2015 The MITRE Corporation. All rights reserved. 

# Mean Departure Delay by Hour (Modeled: JFK)| 10 |

© 2015 The MITRE Corporation. All rights reserved. 

# NPRM Reference| 11 |

© 2015 The MITRE Corporation. All rights reserved. 

# JFK 2008 Negotiated Schedule| 12 |

© 2015 The MITRE Corporation. All rights reserved. 

# NPRM Reference| 13 |

© 2015 The MITRE Corporation. All rights reserved. 

# EWR Average Adjusted Total Capacities

88

84

S O N D J F M A J J A S O N D M J F M A J J M 2005 2006 2007

A Focus of this analysis. 87*

83*

*Modified AAR in visual conditions when Runway 11 used with 22s or 4s| 14 |

© 2015 The MITRE Corporation. All rights reserved. 

# NPRM Reference| 15 |

© 2015 The MITRE Corporation. All rights reserved.| 16 |

© 2015 The MITRE Corporation. All rights reserved. 

# NPRM Reference| 17 |

© 2015 The MITRE Corporation. All rights reserved. 

# Performance Summary: 2007 Versus 2008| 18 |

© 2015 The MITRE Corporation. All rights reserved. 

# Performance Summary: 2007 Versus 2009| 19 |

© 2015 The MITRE Corporation. All rights reserved. 

# Performance Summary: 2007 Versus 2010| 20 |

© 2015 The MITRE Corporation. All rights reserved. 

# Performance Summary: 2007 Versus 2011| 21 |

© 2015 The MITRE Corporation. All rights reserved. 

# Performance Summary: 2007 Versus 2012| 22 |

© 2015 The MITRE Corporation. All rights reserved. 

# NPRM Reference| 23 |

© 2015 The MITRE Corporation. All rights reserved. 

# JFK Adjusted Rates| 24 |

© 2015 The MITRE Corporation. All rights reserved. 

# EWR Adjusted Rates| 25 |

© 2015 The MITRE Corporation. All rights reserved. 

# LGA Adjusted Rates| 26 |

© 2015 The MITRE Corporation. All rights reserved. 

# NPRM Reference| 27 |

© 2015 The MITRE Corporation. All rights reserved. 

# EWR Unscheduled Traffic CY2007

arr local hr Total Weekday
Average

06 89 0.34

07 347 1.34

08 247 0.95

09 279 1.08

10 267 1.03

11 297 1.15

12 261 1.01

13 248 0.96

14 273 1.05

15 297 1.15

16 380 1.47

17 333 1.29

18 259 1.00

19 220 0.85

20 385 1.49

21 565 2.18

22 289 1.12

Grand Total 5036 19.44 Overall Avg/Hour 1.14 dep local hr Total Weekday
Average

06 144 0.56

07 158 0.61

08 576 2.22

09 217 0.84

10 260 1.00

11 244 0.94

12 284 1.10

13 312 1.20

14 310 1.20

15 376 1.45

16 406 1.57

17 441 1.70

18 260 1.00

19 231 0.89

20 240 0.93

21 236 0.91

22 250 0.97

Grand Total 4945 19.09 Overall Avg/Hour 1.12| 28 |

© 2015 The MITRE Corporation. All rights reserved. 

# JFK Unscheduled Traffic CY2007

arr local hr Total Weekday
Average

06 177 0.69

07 166 0.64

08 132 0.51

09 194 0.75

10 187 0.72

11 189 0.73

12 257 1.00

13 331 1.28

14 369 1.43

15 293 1.14

16 401 1.55

17 363 1.41

18 352 1.36

19 338 1.31

20 326 1.26

21 261 1.01

22 229 0.89

Grand Total 4565 17.69 Overall Avg/Hour 1.04 dep local hr Total Weekday
Average

06 144 0.56

07 198 0.77

08 196 0.76

09 290 1.12

10 352 1.36

11 200 0.78

12 209 0.81

13 276 1.07

14 261 1.01

15 333 1.29

16 301 1.17

17 335 1.30

18 329 1.28

19 382 1.48

20 334 1.29

21 287 1.11

22 316 1.22

Grand Total 4743 18.38 Overall Avg/Hour 1.08| 29 |

© 2015 The MITRE Corporation. All rights reserved. 

# LGA Unscheduled Traffic CY2007

arr local hr Total Weekday
Average

06 97 0.38

07 185 0.72

08 333 1.29

09 385 1.49

10 367 1.42

11 403 1.56

12 343 1.33

13 335 1.30

14 325 1.26

15 346 1.34

16 316 1.22

17 331 1.28

18 298 1.16

19 227 0.88

20 203 0.79

21 168 0.65

22 142 0.55

Grand Total 4804 18.62 Overall Avg/Hour 1.10 dep local hr Total Weekday
Average

06 59 0.23

07 159 0.62

08 189 0.73

09 237 0.92

10 300 1.16

11 310 1.20

12 350 1.36

13 341 1.32

14 402 1.56

15 407 1.58

16 398 1.54

17 428 1.66

18 346 1.34

19 275 1.07

20 210 0.81

21 228 0.88

22 190 0.74

Grand Total 4829 18.72

Overall Avg/Hour 1.10| 30 |

© 2015 The MITRE Corporation. All rights reserved. 

# NPRM Reference| 31 |

© 2015 The MITRE Corporation. All rights reserved. 

# EWR Unscheduled Arrivals (January – October 2008)| 32 |

© 2015 The MITRE Corporation. All rights reserved. 

# EWR Unscheduled Departures (January – October 2008)| 33 |

© 2015 The MITRE Corporation. All rights reserved. 

# JFK Unscheduled Arrivals (January – October 2008)| 34 |

© 2015 The MITRE Corporation. All rights reserved. 

# JFK Unscheduled Departures (January – October 2008)| 35 |

© 2015 The MITRE Corporation. All rights reserved. 

# LGA Unscheduled Arrivals (January – October 2008)| 36 |

© 2015 The MITRE Corporation. All rights reserved. 

# LGA Unscheduled Departures (January – October 2008)| 37 |

© 2015 The MITRE Corporation. All rights reserved. 

# EWR Unscheduled Arrivals Summer 2009 (May – August)| 38 |

© 2015 The MITRE Corporation. All rights reserved. 

# EWR Unscheduled Departures

Summer 2009 (May – August)| 39 |

© 2015 The MITRE Corporation. All rights reserved. 

# JFK Unscheduled Arrivals Summer 2009 (May – August)| 40 |

© 2015 The MITRE Corporation. All rights reserved. 

# JFK Unscheduled Departures Summer 2009 (May – August)| 41 |

© 2015 The MITRE Corporation. All rights reserved. 

# LGA Unscheduled Arrivals Summer 2009 (May – August)| 42 |

© 2015 The MITRE Corporation. All rights reserved. 

# LGA Unscheduled Departures Summer 2009 (May – August)| 43 |

© 2015 The MITRE Corporation. All rights reserved. 

# EWR Unscheduled Operations

Summer 2010 (May – August)| 44 |

© 2015 The MITRE Corporation. All rights reserved. 

# JFK Unscheduled Operations Summer 2010 (May – August)| 45 |

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# LGA Unscheduled Operations Summer 2010 (May – August)| 46 |

© 2015 The MITRE Corporation. All rights reserved. 

# NPRM Reference| 47 |

© 2015 The MITRE Corporation. All rights reserved. 

# JFK Modeled Departure Delay: Hourly

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23Mean	Delay	(Minutes)



### Local	Hour 2008	proposed	...

...	built	to	81

2007	schedule| 48 |

© 2015 The MITRE Corporation. All rights reserved. 

# EWR Modeled Arrival Delay: Hourly

0 5 10 15 20 25 30 35 40 45 50 55 60 65

6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23Mean	Delay	(Minutes)



### Local	Hour 2008	proposed	...

...	built	to	81

2007	schedule| 49 |

© 2015 The MITRE Corporation. All rights reserved. 

# EWR Modeled Departure Delay by Hour

0 5 10 15 20 25 30 35 40 45 50 55 60 65

6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23Mean	Delay	(Minutes)



### Local	Hour 2008	proposed	...

...	built	to	81

2007	schedule| 50 |

© 2015 The MITRE Corporation. All rights reserved. 

# Modeling Approach (1 of 2)

Approach to Measuring Performance at Congested Airports MITRE has developed for the FAA a performance modeling and analysis approach for estimating airport performance given various levels of demand, capacity, and potential scheduling limits. In the past this process has been used to estimate performance and evaluate scheduling limits at several airports, including: ORD, JFK, EWR, and LGA, airports. See Figure 1 for a depiction of this approach.

Figure 1: Performance Modeling and Analysis Approach

To evaluate the performance impact of various schedules and other factors on an airport of interest, an airport queuing simulation model is utilized. Modeling the performance impact involves a multi-step process. The first step is to determine the appropriate level of capacity to model. This is done by evaluating airport arrival and departure rates called by the facility, as well as actual throughput experienced. Modeled or facility estimated capacity is utilized in cases where future capacity changes need to be accounted for (e.g., during runway rehabilitation, significant procedural changes, etc.). Capacity is constantly changing and is subject to many factors, including weather, fleet mix, and many others. Because of this, it is important to evaluate the airport’s capacity over a period of time.| 51 |

© 2015 The MITRE Corporation. All rights reserved. 

# Modeling Approach (2 of 2)

The second step involves developing a demand profile for the airport. This needs to include both scheduled and nonscheduled operations. Information about scheduled operations are typically obtained from published schedules ( Innovata or the Official Airline Guide (OAG)), but may also be obtained through a scheduling conference, from airline submittals, or other sources as well. To accurately account for nonscheduled operations, an analysis of an individual airport needs to be performed in order to determine the appropriate level of nonscheduled operations to analyze. Data from the Traffic Flow Management System (TFMS) or Aggregate Demand List (ADL) are used to

collect information on nonscheduled traffic.

The third step includes modeling the representative demand profile (that includes scheduled and nonscheduled operations), along with the historical capacity levels, day by day, and hour by hour, to baseline performance. This is done before any schedule limits are applied to the modeling. Modeled results are compared to actual recorded performance as measured by the FAA’s ASPM system. Past analyses have shown the trends observed from the model results follow the theory of queuing delay and are consistent with the trends from observed delay data, and thus were found to be indicative of actual performance.

The fourth step involves developing constraints that can be applied to the representative demand profile in order to achieve target levels of performance. Many different approaches can be analyzed and include tradeoffs such as impacting scheduled operations only, or scheduled and nonscheduled operations. Implementation of basic single-hour and half-hour constraints can be analyzed, along with multi-hour constraints that allow more peaking in the demand profile but also consist of a recovery period. As the various types of constraints are applied by a scheduling algorithm, operations are moved or removed from the baseline demand profile as necessary to meet the constraints. If possible, operations are moved to times where capacity is available. If operations cannot be accommodated close to their original scheduled time, they are removed from the model (past analyses have used a two-hour window).

The fifth step involves remodeling the airport’s performance using constrained schedules from the scheduling algorithm, along with nonscheduled operations and the collected capacity data. Performance metrics are analyzed to understand if the target levels of performance have been satisfied. If not, the constraints are adjusted to alternative levels, the scheduling algorithm is rerun, and the model’s output is again analyzed until the targets are reached.

Performance estimates from this model are accumulated for each minute of delay, not just delays greater than 15 minutes. The resulting performance measures are sensitive to a number of factors; therefore, the model is run hundreds of times randomizing various elements to account for stochastic variations that may exist. This may include randomizing when scheduled or nonscheduled operations take place, depending on the information available at the time of the analysis.

Differences between actual and modeled delays can be expected due to factors such as airport and en route weather, airport fix loading, airline response to delays and other factors, and traffic flow management actions. Nonetheless, the model results can be used to evaluate the trends and relative differences of performance impacts of constrained schedules at individual airports.| 52 |

© 2015 The MITRE Corporation. All rights reserved. 

### This is the copyright work of The MITRE Corporation and was produced for the U.S. Government under Contract Number DTFAWA-10-C-00080 and is subject to Federal Aviation Administration Acquisition Management System Clause 3.5-13, Rights in Data-General, Alt. III and Alt. IV (Oct. 1996). No other use other than that granted to the U.S. Government, or to those acting on behalf of the U.S. Government, under that Clause is authorized without the express written permission of The MITRE Corporation. For further information, please contact The MITRE Corporation, Contract Office, 7515 Colshire Drive, McLean, VA 22102, (703) 983-6000.

The contents of this material reflect the views of the author and/or the Director of the Center for Advanced Aviation System Development, and do not necessarily reflect the views of the Federal Aviation Administration (FAA) or Department of Transportation (DOT). Neither the FAA nor the DOT makes any warranty or guarantee, or promise, expressed or implied, concerning the content or accuracy of the views expressed herein.

© 2015 The MITRE Corporation. The Government retains a nonexclusive, royalty-free right to publish or reproduce this document, or to allow others to do so, for “Government Purposes Only.”