Data Driven Methods for
Airspace Performance Analysis
Lance Sherry
John Shortle
Students
Center for Air Transportation Systems Research (CATSR) at George Mason University
1
Research and Business Opportunities
Complexity of Interactions
in Network of Distributed
Agents
Optimized
Networked
Operations
Point-to-Point
Scheduled
Operations
Barnstorming
Operations
Aircraft
•Basic Aero
•Propulsion
Air Transportation
• Air Transportation Mail
Air Traffic Control
• Basic Airport Traffic
Control
1920
Air Transportation
• National Air Carriers
• Point-to-Point Service
• Inter-modal
Air Traffic Control
• En-route Air Traffic
Control
• Terminal Area Traffic
Control
Networked
Scheduled
Operation
Air Transportation
• National/International
Network airlines
•Civil Aviation Board
Air Traffic Control
• Radar
• Precision Approach
•
Air Transportation
• Deregulation
• Hub monopolies
•Schedule/Network
optimization
•Overscheduling
•Yield Management
• Fuel Management
airlines
Air Traffic Control
• Radar
• Precision Approach
Optimized
Stochastic,
Capacity-limited
Networked
Operations
Air Transportation
• Flexible Airline Business
Models
• Low Cost
Carriers/Regional Jet
Airlines
• Network configurations
(Hub, point-to-point)
Air Traffic Control
• Collaborative Decision
Making
• Revenue/Cost
Synchronization
• Aircraft Self-separation
• Facility Resizing
• Safety/Capacity Tradeoff
2000
1940
1960
1980
Center for Air Transportation Systems Research (CATSR) at George Mason University
Years
2
Big Data Analytics in Air Transportation
Latitude/Longitude
Surveillance
Data
Flight Data
Aircraft Performance
Altitude and
(Derived) True Airspeed
Procedures
Weather Data
Model-based
Engineering &
Big Data
Analysis
Aircraft Performance
Models
Automation
Behavior
Models
Insights &
Understanding for
Operators, Planners, &
Investors
Automation Behavior Models
Center for Air Transportation Systems Research (CATSR) at George Mason University
Validation
3
Emission Inventory
Center for Air Transportation Systems Research (CATSR) at George Mason University
4
Context
Maximum Emissions generated
Reduction Altitude
during Takeoff Phase Thrust
(Takeoff Thrust to Climb
• Airport Management is required
to report Emissions Inventory for
aircraft Landing and Takeoff
Operations (LTO):
1.
2.
3.
Sustainability planning
Climate Change Registries
Environmental Impact Studies
Fuel
Thrust)
Gear-Up
1500 ft AGL
100 ft AGL
Accelerate to VR
V2
Hold V2 + 10 knots at Constant Rate-of-Climb
Air
CnHm+ S + N + O →
CO + H O + N + O + NOx + CO + SOx + Soot + UHC
Products of Ideal
Products
of Non-Ideal
Combustion
Center Combustion
for Air Transportation Systems Research (CATSR)
at George
Mason University
5
Context
• Monitoring by sensors inaccurate due to
dispersion effects/prohibitively expensive
• Inventory Models
– Mass of pollutants generated
– ICAO Reference Model
Pollutant mass per flight =
Number of Engines x
Time in Phase of Flight (T) x
Fuel Flow Rate (FFR) x
Emissions Index (EI)
• T, FFR, EI averages from ICAO data-base
Center for Air Transportation Systems Research (CATSR) at George Mason University
6
Problem
• “Static” Inventory Models over-estimate
Emissions Inventory
• Two assumptions:
1. Average Time-in-Phase (assumed 2.9 mins
takeoff)
2. Thrust Setting for Takeoff (assumed 100%)
Pollutant mass per flight =
Number of Engines * Time in Phase of Flight * Fuel Flow Rate * Emissions Index
Center for Air Transportation Systems Research (CATSR) at George Mason University
7
Solution
• Improve accuracy in Emissions Inventory
Estimate using
1. High-fidelity track surveillance data
2. Procedure data (i.e. navigation data-base)
3. Aircraft performance model
• Validated by Flight Data
4. Weather data
Center for Air Transportation Systems Research (CATSR) at George Mason University
8
Flight
Schedule
Aircraft Type
•Aircraft Type
•Aircraft
Trajectory
Big Data Analytics
Surveillance
Track Data
Weather Data
Aircraft
Performance
Model
Estimate
Takeoff
Thrust
Setting
Emissions
Data Bank
Avg.
Fuel
Burn
Rate
Avg
TimeinPhase
No. Engines
Emissions Index
Fuel Burn Rate
Time in Phase
Fuel Burn
Rate for
each flight
Trajectory
Analysis
(AEDT/NIRS)
Time in
Phase for
each flight
Takeoff Thrust
Setting
Calculate
Emissions
Inventory
(Reference
Model)
Emissions
Inventory
Emissions Inventory (tons) =
# Engines ∙
Emissions Index ·
Fuel Burn Rate ·
Time in Phase
Estimated
Takeoff Thrust
Assume 100%
Takeoff Thrust
Estimated
Takeoff Thrust
Standalone Takeoff
Models
Center for Air TransportationThrust
Systems
Research (CATSR) at George Mason University
(ACRP-04-02)
9
Surveillance Track Data
Latitude/Longitude
Alternate filtering
techniques developed
VTAS=
(𝑽𝑽𝑮𝑮 ∙ 𝑺𝑺𝑺𝑺𝑺𝑺 𝜽𝜽 ) −
𝑽𝑽𝑮𝑮 ∙ 𝑪𝑪𝑪𝑪𝑪𝑪 𝜽𝜽 −
(𝑽𝑽𝑾𝑾 ∙ 𝑺𝑺𝑺𝑺𝑺𝑺 𝝓𝝓 )
(𝑽𝑽𝑾𝑾 ∙ 𝑺𝑺𝑺𝑺𝑺𝑺 𝝓𝝓 )
Altitude and
(Derived) True Airspeed
Center for Air Transportation Systems Research (CATSR) at George Mason University
10
Aircraft Performance Equations
Total-Energy model: rate of work done by forces acting on the
aircraft = rate of change of potential and kinetic energy
Rearranging for Thrust
Center for Air TransportationSurveillance
Systems Research
University
Aircraft performance
track(CATSR)
data at George Mason
Weather
(i.e. wind)
11
Results
Thrust Settings for 1200 departures at ORD
µ = 86% Max Takeoff Thrust, σ = 11%
Frequency
50%
40%
30%
20%
10%
0%
0
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
1
Thrust
% Max Takeoff Weight
Validation:
• Airline supplied takeoff thrust settings.
• Range in thrust reduction
from 0% to 24 %
Center for Air Transportation Systems Research (CATSR) at George Mason University
• An average thrust reduction of 13%, standard deviation of 8%.
12
Sensitivity Analysis – TOW and Headwind
(Marginal)
Sensitivity to
Headwind
(~5%)
MD-83 (Super MD-80)
Sensitivity to
Takeoff
Weight (~30%)
Center for Air Transportation Systems Research (CATSR) at George Mason University
13
Modernization Cost/Benefits
Analysis: Metroplex Flow Deconfliction Using
RNP Procedures at Midway Airport
Akshay Belle
Center for Air Transportation Systems Research (CATSR) at George Mason University
14
Metroplex Examples
Top 10 Metroplexes in the US
Sl.no
Metroplex
1
2
5
3
New york
Chicago
Los Angeles
Atlanta
District of
Columbia
Dallas
San Francisco
Miami
Denver
Charlotte
4
6
7
8
9
10
Chicago Metroplex
Ops per day # Airports
(Year 2012) within 30NM
3257
4
3055
2
2797
4
2542
1
2434
3
2236
1903
1734
1697
1498
2
3
2
1
1
Total of 21 Metroplexes in the U.S serving
metropolitan area that account for:
• 35% of the nation’s population (314 M)
(United States Census Bureau, 2012)
• 44% of the gross domestic product ($15.68
trillion) (U.S. Department of Commerce,
2012)
14NM
New York Metroplex
9NM
10 NM
8.5NM
17NM
Center for Air Transportation Systems Research (CATSR) at George Mason University
15
Metroplex De-confliction – Terminal Airspace
Redesign (Spatial Strategy)
Before
After
N
ORD
ORD
22L
Departures
N
22L
Departures
Airspace
Conflict
13C ILS
MDW
No Airspace
Conflict
13C RNP
Wind Direction
Center for Air Transportation Systems Research (CATSR) at George Mason University
MDW
Wind vector
16
Chicago Metroplex De-confliction
MDW - RNP0.3 w/RF Leg approach on to 13C
•
Chicago Metroplex Deconfliction
–
–
RNP0.3 w/RF Leg approach on
to 13C at MDW
Safe Vertical Separation
Metroplex De-confliction – Vertical Profile
Center for Air Transportation Systems Research (CATSR) at George Mason University
17
MDW Flows from East and West
Flows From East
Flows and their respective Track count
Sl.no
1
2
Direction
Runway
13C
3
4
5
6
7
Abeam
Flows From West
Abeam
E
31C
8
9
10
11
31R
4L
4R
12
13
14
15
16
17
18
19
20
21
22
23
24
13L
22L
22R
13C
W
13L
22L
22R
31C
31R
4L
4R
Approach
ILS
RNP
Count
798
87
Visual
1026
Visual
Visual
Visual
8
840
70
ILS
1467
Visual
Visual
Visual
ILS
345
5
48
390
Visual
1181
ILS
RNP
Visual
Visual
Visual
Visual
ILS
Visual
Visual
Visual
ILS
Visual
568
151
857
9
650
56
387
987
2
50
729
564
Center for Air Transportation Systems Research (CATSR) at George Mason University
18
TRACON Flow Track Distance & Time
Performance
Flows From East
Track distance and time, lower the better
Ranking of flow from the East
Abeam Final
waypoint on
STAR
Flows From West
Ranking of flow from the West
Center for Air Transportation Systems Research (CATSR) at George Mason University
19
Benefits RNP Approaches for MDW (all Runways)
RNP 31 C from West
RNP 4R from the East
ILS available
Chicago Heights (CGT)
Joliet (JOL)
Center for Air Transportation Systems Research (CATSR) at George Mason University
20
Source of variance in RNP flows
MDW- Flows to runway 13C from the east
ILS Approach
RNP Approach
“Vectors" up to the Start of the RNP
approach (base leg) introduce as much
variation in track distance/time as the ILS
approaches.
Center for Air Transportation Systems Research (CATSR) at George Mason University
21
Airport Surface Operations
Analysis
Anvardh Nanduri, Kevin Lai
Center for Air Transportation Systems Research (CATSR) at George Mason University
22
ATL 2012 Jan Excess Surface Count (10 Min Periods)
2500
2000
1500
1000
500
0
-500
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Day of Month
Arr
Dep
Avg
1 Sigma
2 Sigma
Center for Air Transportation Systems Research (CATSR) at George Mason University
23
Annual Surface Ops
2500
3 Sigma
2 Sigma
2000
Excess number of flights
Daily Cumulative 10 Minute Surface Counts
3000
1 Sigma
1500
Average
1000
Departures
500
0
Arrivals
-500
Dates
Day of Year
2012
Excess Cum Arrivals
Excess Cum Departures
Avg
1 Sigma
2 Sigma
3 Sigma
Center for Air Transportation Systems Research (CATSR) at George Mason University
24
Daily Cumulative Surface Count
ATL 2012
60
100.00%
90.00%
Frequency
50
80.00%
70.00%
40
60.00%
30
50.00%
40.00%
20
30.00%
20.00%
10
10.00%
0.00%
0
200
400
600
800
1000
1200
1400
1600
1800
2000
2200
2400
2600
2800
3000
0
Daily Cumulatve Surface Count
Frequency
Cumulative %
Normal Distribution
Center for Air Transportation Systems Research (CATSR) at George Mason University
25
35
30
00:00-00:59
00:00-00:59
01:00-01:59
01:00-01:59
02:00-02:59
02:00-02:59
03:00-03:59
03:00-03:59
04:00-04:59
04:00-04:59
05:00-05:59
05:00-05:59
06:00-06:59
06:00-06:59
07:00-07:59
07:00-07:59
08:00-08:59
08:00-08:59
09:00-09:59
09:00-09:59
10:00-10:59
10:00-10:59
11:00-11:59
11:00-11:59
12:00-12:59
12:00-12:59
13:00-13:59
13:00-13:59
14:00-14:59
14:00-14:59
15:00-15:59
15:00-15:59
16:00-16:59
16:00-16:59
17:00-17:59
17:00-17:59
18:00-18:59
18:00-18:59
19:00-19:59
19:00-19:59
20:00-20:59
20:00-20:59
21:00-21:59
21:00-21:59
22:00-22:59
22:00-22:59
23:00-23:59
23:00-23:59
Causal Analysis- Reduced Departure Rate - Mar 13, 2012 (ATL)
Runway Config Change
8L, 9R, 10 | 8R, 9L (35 ops/10
mins )
Airport Departure Rate
Runway Config
26R, 27L, 28 | 26L, 27R (34 ops/10 mins)
25
20
15
10
5
0
Airport Acceptance Rate
Visibility
Ceiling/1000
Wind Direction/10
Center for Air Transportation Systems Research (CATSR) at George Mason University
Wind Speed
26
Cumulative Surface Counts - Reduced Departure Rate -
Mar
13, 2012 (ATL)
4000
3500
2500
2000
1500
1000
Runway Config Change
8L, 9R, 10 | 8R, 9L (35
ops/10 mins )
Runway Config
26R, 27L, 28 | 26L, 27R (34 ops/10 mins)
500
0
TW1
TW4
TW7
TW10
TW13
TW16
TW19
TW22
TW25
TW28
TW31
TW34
TW37
TW40
TW43
TW46
TW49
TW52
TW55
TW58
TW61
TW64
TW67
TW70
TW73
TW76
TW79
TW82
TW85
TW88
TW91
TW94
TW97
TW100
TW103
TW106
TW109
TW112
TW115
TW118
TW121
TW124
TW127
TW130
TW133
TW136
TW139
TW142
TW145
Number of flights
3000
TW
Cumulative Actual Arr Surface Count
Cumulative Actual Dep Surface Count
Cumulative Sched Arr Surface Count
Cumulative Sched Dep Surface Count
Center for Air Transportation Systems Research (CATSR) at George Mason University
27
00:00-00:59
00:00-00:59
01:00-01:59
01:00-01:59
02:00-02:59
02:00-02:59
03:00-03:59
03:00-03:59
04:00-04:59
04:00-04:59
05:00-05:59
05:00-05:59
06:00-06:59
06:00-06:59
07:00-07:59
07:00-07:59
08:00-08:59
08:00-08:59
09:00-09:59
09:00-09:59
10:00-10:59
10:00-10:59
11:00-11:59
11:00-11:59
12:00-12:59
12:00-12:59
13:00-13:59
13:00-13:59
14:00-14:59
14:00-14:59
15:00-15:59
15:00-15:59
16:00-16:59
16:00-16:59
17:00-17:59
17:00-17:59
18:00-18:59
18:00-18:59
19:00-19:59
19:00-19:59
20:00-20:59
20:00-20:59
21:00-21:59
21:00-21:59
22:00-22:59
22:00-22:59
23:00-23:59
23:00-23:59
Causal Analysis- “Blue Sky” - May 18, 2012 (ATL)
35
30
No Runway Configuration Change
8L, 9R, 10 | 8R, 9L (36 ops /10 mins)
25
20
15
10
5
0
Airport Departure Rate
Airport Acceptance Rate
Wind Speed
Visibility
Ceiling/1000
Center for Air Transportation Systems Research (CATSR) at George Mason University
Wind Direction/10
28
Cumulative Surface Counts – Blue Sky - May 18, 2012
(ATL)
3000
2500
1500
Runway Configuration did not change
8L, 9R, 10 | 8R, 9L (36 ops /10 mins)
1000
500
0
TW1
TW4
TW7
TW10
TW13
TW16
TW19
TW22
TW25
TW28
TW31
TW34
TW37
TW40
TW43
TW46
TW49
TW52
TW55
TW58
TW61
TW64
TW67
TW70
TW73
TW76
TW79
TW82
TW85
TW88
TW91
TW94
TW97
TW100
TW103
TW106
TW109
TW112
TW115
TW118
TW121
TW124
TW127
TW130
TW133
TW136
TW139
TW142
TW145
Number of flights
2000
TW
Cumulative Actual Arr Surface Count
Cumulative Actual Dep Surface Count
Cumulative Sched Arr Surface Count
Cumulative Sched Dep Surface Count
Center for Air Transportation Systems Research (CATSR) at George Mason University
29
Airspace Risk Management
- Go Around
Stabilized Approaches
Zhenming Wang, Houda Kerkoub
Center for Air Transportation Systems Research (CATSR) at George Mason University
30
Risk Management Metrics
Risk Events Metric
Definitions
Risk Management Metrics
Risk Events and Factors
Risk Events Definitions
Calculate Risk Events and Factors
Derived data
Calculate Derived data
Processed Observed Data
Process Observed Data
Navigation Data-base
Aircraft Performance
Raw Surveillance Track
(Procedures)
Models
Data
Center for Air Transportation Systems Research (CATSR) at George Mason University
Weather Data
31
•
Missed Approach – 20%
Go Arounds
•
Go Arounds are not
measured/reported.
Track data used to
count and analyze
Fit
Normal (0.007, 0.005)
Likelihood of a Go Around
Mean = 7/1000
Std Dev = 5/1000
Range = [0 22/1000]
Aborted Approach – 80%
local time
18:00-18:59 18:00-18:59 19:00-19:59
quarter hour
3
4
1
arrival runway configuration
9R, 22L, 28
9R, 22L, 28 9R, 22L, 28
airport acceptance rate
15
15
15
arrival demand
72
72
73
ceiling (ft)
1200
1200
1000
wind direction
180° - S
180° - S
190° - S
wind speed (kts)
14
14
10
visability (miles)
3
3
3
temperature (°F)
32
32
32
on-time arrival %
16.67%
26.32%
16.67%
avg.
arrival delay
(min)
77
122
Center for Air Transportation Systems
Research
(CATSR)
at George Mason 134
University
32
Go-arounds
• 19 out of 3548
• About 5.4 per 1000 flights
Center for Air Transportation Systems Research (CATSR) at George Mason University
33
Go Arounds - ASRS Taxonomy
Factor
Airplane Issues
Separation Violation
Weather
Flight/TAC Interaction
Runway Issues
No Reason provided
% ASRS Reports
54%
21%
17%
8%
5%
6%
Center for Air Transportation Systems Research (CATSR) at George Mason University
34
Go Arounds - ASRS Taxonomy
1. Airplane Issue
1.1 Unstable Approach
1.1.1.High and Fast
1.1.2 Other Approach
Issue
1.2 Alerts
1.3 Onboard failures
Center for Air Transportation Systems Research (CATSR) at George Mason University
53.74%
9.52%
6.12%
3.40%
4.08%
40.14%
35
Go Arounds – ATSAP Taxonomy
ATSAP Data, Bayesian Network Model
Firdu Bati (Dissertation)
Center for Air Transportation Systems Research (CATSR) at George Mason University
36
Stabilized Approach
• 1000’ AGL
– On Runway Center-line
– On Glidepath
– At Landing Speed (VRef)
– At Rate of Descent for Glide-path (< 1000fpm)
Center for Air Transportation Systems Research (CATSR) at George Mason University
37
Stabilized Approaches
Frequency of risk events from 1000 ft. AGL to runway threshold
Fast
Center for Air Transportation Systems Research (CATSR) at George Mason University
38
Stabilized Approaches
Frequency of risk events from 750 ft. AGL to runway threshold
Center for Air Transportation Systems Research (CATSR) at George Mason University
39
Stabilized Approaches
Frequency of risk events from 500 ft. AGL to runway threshold
Summary table 500 ft. AGL
Center for Air Transportation Systems Research (CATSR) at George Mason University
40
1000’ AGL
13C
ILS available
31C
4R
Chicago Heights (CGT
Joliet (JOL)
Groundspeed
Change
Rate of
Descent
Within limits
No change
Excessive
Within limits
Greater than
10 knots
Excessive
Position with
Glidepath
On Glidepath
Above Glidepath
On Glidepath
Above Glidepath
On Glidepath
Above Glidepath
On Glidepath
Above Glidepath
04R
13C
31C
Position with Runway
Centerline
#
%
#
%
#
%
On Runway Centerline
721 74.56% 411 29.19% 987 84.22%
Not On Runway Centerline 35 3.62% 492 34.94% 52 4.44%
On Runway Centerline
3
0.31%
0
0.00% 38 3.24%
Not On Runway Centerline
2
0.21% 96 6.82%
0
0.00%
On Runway Centerline
2
0.21%
1
0.07%
1
0.09%
Not On Runway Centerline
0
0.00%
2
0.14%
0
0.00%
On Runway Centerline
0
0.00%
0
0.00%
1
0.09%
Not On Runway Centerline
0
0.00% 24 1.70%
0
0.00%
On Runway Centerline
177 18.30% 14 0.99% 82 7.00%
Not On Runway Centerline 18 1.86% 233 16.55% 3 0.26%
On Runway Centerline
1
0.10%
0
0.00%
5
0.43%
Not On Runway Centerline
0
0.00% 102 7.24%
0
0.00%
On Runway Centerline
4
0.41%
0
0.00%
3
0.26%
Not On Runway Centerline
3
0.31%
2
0.14%
0
0.00%
On Runway Centerline
2
0.21%
0
0.00%
0
0.00%
Not On Runway Centerline
0
0.00% 31 2.20%
0
0.00%
20%
Center for Air Transportation Systems Research (CATSR) at George Mason University
26%
8%
41
Stabilized Approaches - Factors
Weight % Flights
Class
750 ft.
AGL –
Change in
Speed
Heavy
20.9%
B757
15.1%
Large
12.0%
Small
47.0%
Average Groundspeed at the
Runway Threshold
134.5 knots
129 knots
132 knots
122.5 knots
Every approach/runway is different
Procedure % dv>10kts from 1000' to THR
ILS
5.97%
RNP
4.23%
VFR
50.15%
% dv>10kts from 750' to THR
1.19%
0.00%
12.35%
% dv>10kts from 500' to THR
0.17%
0.00%
0.59%
Center for Air Transportation Systems Research (CATSR) at George Mason University
42
Big Data Analytics in Air Transportation
Latitude/Longitude
Surveillance
Data
Flight Data
Aircraft Performance
Altitude and
(Derived) True Airspeed
Procedures
Weather Data
Model-based
Engineering &
Big Data
Analysis
Aircraft Performance
Models
Automation
Behavior
Models
Insights &
Understanding for
Operators, Planners, &
Investors
Automation Behavior Models
Center for Air Transportation Systems Research (CATSR) at George Mason University
Validation
43