© 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 
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© 2015 The MITRE Corporation. All rights reserved. 

NPRM Reference 
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© 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 
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© 2015 The MITRE Corporation. All rights reserved. 

NPRM Reference 
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© 2015 The MITRE Corporation. All rights reserved. 

Target Performance Goals By Airport (Modeled)
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© 2015 The MITRE Corporation. All rights reserved. 

NPRM Reference 
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© 2015 The MITRE Corporation. All rights reserved. 

Capacity Input: 

Adjusted Capacities at JFK (Arrivals Plus Departures)

J A S O N D J F M A M J J A S O N D J F M A M J J 

2005 2006 2007 

74.6 

79.2 

81.2 

77.1 
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© 2015 The MITRE Corporation. All rights reserved. 

NPRM Reference 
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© 2015 The MITRE Corporation. All rights reserved. 

Mean Departure Delay by Hour 

(Modeled: JFK) 
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© 2015 The MITRE Corporation. All rights reserved. 

NPRM Reference 
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© 2015 The MITRE Corporation. All rights reserved. 

JFK 2008 Negotiated Schedule 
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© 2015 The MITRE Corporation. All rights reserved. 

NPRM Reference 
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© 2015 The MITRE Corporation. All rights reserved. 

EWR Average Adjusted Total Capacities 

88 

84 

S O N D J F M A M J J A S O N D J F M A M J J 

2005 2006 2007 

A 

Focus of this analysis. 

87* 

83* 

*Modified AAR in visual conditions when Runway 11 used with 22s or 4s 
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© 2015 The MITRE Corporation. All rights reserved. 

NPRM Reference 
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© 2015 The MITRE Corporation. All rights reserved. 
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© 2015 The MITRE Corporation. All rights reserved. 

NPRM Reference 
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© 2015 The MITRE Corporation. All rights reserved. 

Performance Summary: 

2007 Versus 2008 
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© 2015 The MITRE Corporation. All rights reserved. 

Performance Summary: 

2007 Versus 2009
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© 2015 The MITRE Corporation. All rights reserved. 

Performance Summary: 

2007 Versus 2010
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© 2015 The MITRE Corporation. All rights reserved. 

Performance Summary: 

2007 Versus 2011 
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© 2015 The MITRE Corporation. All rights reserved. 

Performance Summary: 

2007 Versus 2012
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© 2015 The MITRE Corporation. All rights reserved. 

NPRM Reference 
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© 2015 The MITRE Corporation. All rights reserved. 

JFK Adjusted Rates 
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© 2015 The MITRE Corporation. All rights reserved. 

EWR Adjusted Rates 
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© 2015 The MITRE Corporation. All rights reserved. 

LGA Adjusted Rates 
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© 2015 The MITRE Corporation. All rights reserved. 

NPRM Reference 
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© 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
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© 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
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© 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
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© 2015 The MITRE Corporation. All rights reserved. 

NPRM Reference 
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© 2015 The MITRE Corporation. All rights reserved. 

EWR Unscheduled Arrivals 

(January – October 2008) 
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© 2015 The MITRE Corporation. All rights reserved. 

EWR Unscheduled Departures 

 (January – October 2008) 
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© 2015 The MITRE Corporation. All rights reserved. 

JFK Unscheduled Arrivals 

 (January – October 2008) 
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© 2015 The MITRE Corporation. All rights reserved. 

JFK Unscheduled Departures 

 (January – October 2008) 
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© 2015 The MITRE Corporation. All rights reserved. 

LGA Unscheduled Arrivals 

 (January – October 2008) 
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© 2015 The MITRE Corporation. All rights reserved. 

LGA Unscheduled Departures 

 (January – October 2008) 
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© 2015 The MITRE Corporation. All rights reserved. 

EWR Unscheduled Arrivals 

Summer 2009 (May – August) 
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© 2015 The MITRE Corporation. All rights reserved. 

EWR Unscheduled Departures 

Summer 2009 (May – August) 
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© 2015 The MITRE Corporation. All rights reserved. 

JFK Unscheduled Arrivals 

Summer 2009 (May – August) 
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© 2015 The MITRE Corporation. All rights reserved. 

JFK Unscheduled Departures 

Summer 2009 (May – August) 
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© 2015 The MITRE Corporation. All rights reserved. 

LGA Unscheduled Arrivals 

Summer 2009 (May – August) 
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© 2015 The MITRE Corporation. All rights reserved. 

LGA Unscheduled Departures 

Summer 2009 (May – August) 
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© 2015 The MITRE Corporation. All rights reserved. 

EWR Unscheduled Operations 

Summer 2010 (May – August) 
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© 2015 The MITRE Corporation. All rights reserved. 

JFK Unscheduled Operations 

Summer 2010 (May – August) 
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LGA Unscheduled Operations 

Summer 2010 (May – August) 
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© 2015 The MITRE Corporation. All rights reserved. 

NPRM Reference 
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© 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 23

Mean	Delay	(Minutes)

Local	Hour

2008	proposed	...

...	built	to	81

2007	schedule
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© 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 23

Mean	Delay	(Minutes)

Local	Hour

2008	proposed	...

...	built	to	81

2007	schedule
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© 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 23

Mean	Delay	(Minutes)

Local	Hour

2008	proposed	...

...	built	to	81

2007	schedule
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© 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.”