Metroplex Operations
NASA NRA NNH06ZEA001N-AS
Airspace Subtopic 20
NASA Airspace Systems Program
Technical Interchange Meeting
March 18-20, 2008
CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH
The NAS is a Network of Networks
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Key Nodes in these Networks are Predicted to be Saturated
– Even with New Runways and Technology!
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2007
New York
2015
New York
Los Angeles
Philadelphia
San
Francisco
Predicted Congested
Metropolitan Regions
with all NEXTGEN
Technology and Runway
Improvements
FAA FACT 2 Report May 2007
3
2025
New York
Los Angeles
Philadelphia
San
Francisco
Atlanta
Las Vegas
Phoenix
San Diego
Why this Research Problem is Important
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• National Air Transportation Capacity
Growth & Congestion Management is a
Complex Adaptive System
Stochastic Network Control Problem
• NYC Metroplex is a Current Example of a
Major Problem that will Illustrate a
General Solution Approach
4
Domestic Markets served by NYC Major
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Airport Networks: 104
DOT/FAA response to
NYC Congestion Problem
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•Cap Operations at LGA, JFK & EWR
•Loss of Market Competition & Efficiency
•Offer Airports the Option to Charge
Congestion Pricing Landing Fees
•PANYNJ rejecting offer
•Considering using Slot Auctions to find
Market Clearing Prices
•Congressional Authorization may be
Required
PANYNJ Response to Problem
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• 90 Yr. Lease of Stewart International
Airport
•
•
•
•
$79 million + $17 million Improvements
2 Parallel Runways
November 1, 2007 assumed control
Skybus Airline will connect to Columbus and
N.C. Piedmont Triad International Airports
• Other Airlines offer service to Atlanta, Florida,
Detroit and Philadelphia
Some Outstanding Issues
with these Solutions
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•What are the Airport/Airline/DOT Property Rights?
•What is the Best Equity Metric?
•How should Max. Capacity be Determined?
•What Fraction of Max. Capacity should be Allocated?
•How Should these Airport Operations be Coordinated?
•How should Small and Medium sized Communities be
Served?
•How will Market Allocation affect Service?
•Desired Market Service Redundancy?
•Desired Market Service Frequency?
•Desired Aircraft Gauge Distribution?
GMU-Purdue Research Approach
In-depth study of a Metroplex
•
•
•
Analyze dynamic properties of
NY/NJ metroplex
Develop solutions based on variable
metroplex components
Generate hypotheses and parameters
governing metroplex properties
Network Effects
•
•
•
Derive and analyze generic
metroplex properties and
dependencies
Understand network effects on
metroplex
Create models with NY/NJ
metroplex as a test-bed and refine
hypotheses
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Purdue Study of Dependencies
& Network Effects
• Characterize underlying
dependencies in metroplex
Metroplex Dependency Dimensions
Resources
Operations
Policy
Economics
Air/Ground
Terminal Area
Rules & Regs
$$ Drivers
• Categorize and mathematically
represent dependencies within and
across: Resource – Operations –
Policy – Economic Dimensions
An Airport
in Metroplex
Airport
in Metroplex
• Understand network effects
• Metroplex and rest of NAS network
are mutually influential
• Competing interests in network
evolution
• Performance impacts from altering
network topology (add/delete links
and weights on links)
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• Airspace Structure
• ATC facilities
• Runways
• Aircraft
• Arrival/Depart. Stream
• Ground Ops
• Capacity sharing
• Airline ops
• TRACON coordination
• Interaction w/ Center
• Required Nav perf.
• Reduced Separation
• Traffic Demand
• Airline strategies
• Regional A/P author.
• ATM business model
GMU NYC Case Study:
Number of Major Domestic Markets Served
Airport Code
Newark(EWR)
Kennedy(JFK)
LaGuardia(LGA)
11
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# of Airports Served
81
62
68
Airports Served by Multiple NYC Airports
# of airports served by
# of NYC airports
1
2
3
29
37
38
% of airports served by
27.9%
•What Property Rights?
•What Equity Metric?
•What Frequency?
•What Aircraft Gauge?
•What Load Factor?
•What Competition?
12
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•What Profitability?
35.6% 36.5%
Airports Served by Multiple NYC Airports
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# of airports served by
# of NYC airports
1
2
3
29
37
38
% of airports served by
27.9%
35.6% 36.5%
•What Property Rights?
•What Equity Metric?
•What Frequency?
•What Aircraft Gauge?
•What Load Factor?
•What Competition?
13
•What Profitability?
Proper Combination
can solve X 3 PAX
and Cargo Growth
for a METROPLEX?
Frequency? Histogram of the Average Number
of Arrival Flights per Day (Summer 2007 T100)
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Top 3 routes
•BOS-LGA(32)
•DCA-LGA(31)
•ORD-LGA(30)
14
Average Number of Flight Arrivals/16 Hr Day from
Top Metroplex Airports to NYC (Summer 07 T100) CATSR
Metroplex
Boston
Washington DC
Chicago
Miami
Los Angeles
San Francisco
15
Airport Name
Boston Logan MA
Manchester NH
Providence RI
Baltimore MD
Ronal Reagan National
DC
Dulles VA
Chicago Midway IL
Chicago O'Hare IL
Miami FL
Fort Lauderdale FL
West Palm beach FL
Los Angeles CA
Ontario CA
Burbank CA
John Wayne Orange
Co CA
Long Beach CA
San Francisco CA
San Jose CA
Oakland CA
EWR
# of arrivals/day
JFK LGA
NYC
BOS
MHT
PVD
BWI
DCA
10
4
4
4
7
21
3
4
4
8
32
6
4
5
31
63
13
12
13
46
IAD
MDW
ORD
MIA
FLL
PBI
LAX
ONT
BUR
SNA
10
2
20
8
12
6
10
12
6
12
30
11
14
4
28
14
61
25
39
18
32
1
5
3
Code
LGB
SFO
SJC
OAK
11
6
13
8
22
1
5
3
10
1
6
20
2
4
6
30
3
4
Total
88
87
75
82
47
37
Competition? Number of Airlines Serving
the Markets Histogram(T100)
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•LGA is Most
Competitive
•EWR is Least
Competitive
16
Profitability?
One-way Airfares Histogram (DB1B)
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•EWR has the Highest
average airfare
•JFK the Lowest
17
Profitability?
Unit Revenue vs. Load Factor
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•Unit revenue decreases with
•increasing load factor.
•MVY (Martha’s Vineyard,
MA) to NYC has the largest
unit revenue (0.83$/mile).
•TUS (Tucson, AZ) to NYC
has the smallest
unit revenue (0.08$/mile).
18
Efficiency? Load Factor vs. Seat Size
Classified by Load Factor
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•Load factor has
a positive
relationship
with A/C Gauge
Efficiency?
19
Efficiency? LGA has Lowest
Load Factor Histogram (T100)
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•LGA has Lowest
average load factor (0.71)
•EWR and JFK have
load factors greater than 0.6
on 90% of routes
•LWB-LGA has Lowest
load factor among
all routes (0.26)
•DCA-EWR (0.48),
DCA-JFK (0.8),
DCA-LGA (0.51)
20
Efficiency ? Frequency vs. Seat Size
Classified by Load Factor
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• High frequency, Small A/C
routes are good
candidates for up-gauging
21
Efficiency vs. Profitability?
Frequency vs. Seat Size & Unit Revenue
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•High Unit Revenues
For Small A/C &
High Frequency
22
Interim Observations
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• Airlines are filling planes
• Flights with low load capacity are mostly to
small profitable airports or BOS and DCA
• Airlines made money in Summer of 2007
So, what's the problem?
- Delays!
23
NYC airports Quarter Hour Over-scheduling
Percentage (6:00am-10:00pm) in 2007 summer
n
O = ∑ I Demand >max Capacity / n
i =1
24
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JFK Scheduled Gate-In/Gate-Out Demand
Distribution (Count - Summer 07 ASPM)
Gross OverScheduling
25
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JFK Scheduled Wheels-On/Wheels-Off Demand
Distribution (Count - Summer 07 ASPM)
Schedule Padding for
Expected Taxi Delays
26
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JFK Actual Wheels-On/Wheels-Off Demand
Distribution (Count - Summer 07 ASPM)
FAA ATC
Effect
DOT CAP
27
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Result of this Schedule on Network Delay:
AVG Wheels-Off Delays At JFK (ASPM)
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95 Minutes!
28
Effect of LGA Slot Control Program:
Still Unacceptably High Network Delays!
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60 Minutes!
29
Economic Optimum Slot Allocation is at
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80 - 90% Max Capacity
$40
$35
Some Costs Approximated
Other Costs Not Included
Slot Reductions Imposed
at Top 35 Airports
Sum of Both Costs ($B)
$30
Costs Resulting From Reducing
Airport Landing Slots
$25
$ B/Yr
$20
$15
Data Scaled to
Reflect CY2025
Costs Resulting from Passenge
Delays and Flight Cancellations
$10
$5
$0
0.0%
2.5%
5.0%
7.5%
10.0%
12.5%
15.0%
17.5%
Percent of Slots Withheld at Top 35 Airport
Donohue and Shaver, forthcoming spring 2008
20.0%
Work Completed
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• Identified Primary Markets being Served
by NYC Metroplex
• Estimated Price Elasticity for these
Markets
• Estimated Fixed and Variable A/C Ops
costs
• Identified Market Service Redundancies
• Identified Inter-Airport Ground and Helo
routes and transit times
Work to be Done Next Quarter
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• Compute Optimum Fleet Gauge and Schedule for each
individual A/P using Le Formulation
• Vary fuel cost from $3.5 to $5.0/gal
• Add International Airports at EWR and JFK
• Continue development of an Optimum Metroplex Model
formulation
• Simulate Stochastic Low Level flight Operations for
Helicopters to establish Max. Runway Independent air
transport capacity (5 A/P)
• Does Business Case Exist?
• Compare to Ground transportation times/Capacity
Major Research Issues still
to be Addressed in this Research
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• How should the National Airspace
Networks be Configured to efficiently Serve
Major Metropolitan Regions?
• What National Control Mechanisms will be
both Adequate, Equitable and Efficient?
• How will we Define Adequacy, Equity and
Efficiency?
• Can we Design and Enforce an N tiered
Network system?
33
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• BACKUP
Progress to Date
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•
•
•
•
35
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Data Analysis Software Complete (Oct-Nov 2007)
NASA project report (Dec. 2007)
TRB Conference Papers (Jan. 2008)
104 Market Data-base complete (Feb. 2008)
5 ICRAT ‘08 papers relevant to this study in review process:
– Analysis of Air Transportation for the New York Metroplex:
Summer 2007 (Wang, Donohue, Hoffman, Sherry and OsegueraLohr)
– Impact of GDP Rationing Rules on Passenger & Airline Equity
(Manley and Sherry)
– Decision Support Tool for Predicting Aircraft Arrival Rates, GDPs
and Airport Delays from Weather (Smith, Sherry and Donohue)
– Passenger Trip Delays in the US Airline Transportation System in
2007 (Calderon-Meza, Sherry and Donohue)
– Network Restructuring Models for Improved ATS Forecasts
(DeLaurentis, Kotegawa, and Sengstacken)
LGA Up-gauging studies Show
Both Promise and Problems
Aircraft Up-Gaugi
Current Fleet Allocation - 1010 Flts
90 % Optimum Fleet Allocation - 806 Flts
GRA upgauged schedule's Fleet Allocation - 1194 Flts
300
250
200
150
100
50
0
19 to 3744 to 5069 to 77 88 to
110
111 to 117 to 134 to 138 to 166 to 182 to 194 to 226 to
116
133
137
158
181
193
225
285
Aircraft Seating Capac
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Aircraft Info (P52)
37
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JFK Actual Gate-In/Gate-Out Demand
Distribution(ASPM)
38
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Wheels-Off Delays At EWR (ASPM)
39
Wheels-off delays=max{0, actual wheels-off
time -scheduled wheels-off time}
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