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Sample Application of Matlab Data
Structures
Dr. Antonio A. Trani
Associate Professor of Civil and Environmental Engineering
Virginia Tech
CEE 5944
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A Typical Flight
In order to consider study the National Airspace System (NAS) we
consider aircraft flight plans (fp) over the entire continental US . A
sample flight explaining the requirements of the data stucture used
in Matlab is explained in the sequel. All parameters of this flight
have been derived from the Enhanced Traffic Management System
(ETMS).
% The following example illustrates the ETMS data base
AAL1________00_0 YYY B767 YYY YYY
AAL1________00_0 JFK LAX
1
40.640 73.779 866 33.943 118.408 1152 14:26 286 0 C 50
IZYYYYYY 40.633 73.783 0 866.000
123 123
YYYYYYYY 40.417 74.143 112 871.885
330 304
YYYYYYYY 40.200 74.500 208 875.749
386 345
YYYYYYYY 40.285 74.988 282 879.526
441 386
.....
LZYYYYYY 33.950 118.400 0 1168.621
219 225
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Flight Information
•
Boeing 767-200
•
Origin = JFK (New York)
•
Destination - LAX (Los Angeles)
•
Flight departure time = 866 UTC (minutes)
•
50 waypoints along the route are filed by the pilot in this case
indicating a full trajectory from JFK to LAX
•
The entire trip crosses 5-6 ARTCC centers in NAS and involves
2 terminal area crossings (at origin and destination airports)
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Data Structure of Flight Plan Information
•
In order to understand the communication loads required with
advanced ATM applications for each one of the areas of interest
we prototype a sample flight plan message as shown below:
fname: 'AAL1________00_0'
fmodel: 'B767'
origin: 'JFK'
dest: 'LAX'
n: 50
wp: [50x3 double]
twp: [50x1 double]
omodule: 222
start_point: [-73.7830 40.6330 0]
start_time: 866
start_seg: 1
start_lam: 0
path: [ 1x5 struct]
main_path: [ 1x4 struct]
Aircraft ID
Aircraft Model
Origin-Destination Info
Waypoint Information
Starting Leg
Information
n+4 Waypoint/Sector Info
Total Data Set = 3708 bytes (using double precision for all numeric data)
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Some Details About the Typical Flight Plan
•
The previous flight plan structure follows the same guidelines
used by the FAA in ETMS with a few additions
•
The average flight plan from an observation of random sets of
6000 IFR plans crossing ZTL is 34.3 waypoints. This still
represents an average of 3,350 bytes of information per flight
•
The modeling assumption is that in the future NAS most of the
flights will operate under some equivalent IFR flight plan for
safety reasons (today about 60% of the operations are IFR)
•
In the tactical domain (n+4 waypoint information could be used
to probe and schedule detours)
•
In the near-strategic domain we assume n+10 waypoints used in
the elaboration of surrogate flight plans
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Pictorial Representation of the Flight
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Aircraft Trajectory (Speed and Altitude Profile)
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Another Look at the ETMS Flight Plan Data
Flight Time (minutes)
Flight Time (minutes)
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Air Traffic Control Domains
Control activities in Air Traffic Control (ATC) are usually
segregated into the following domains:
•
Airport Air Traffic Control Tower (ATCT)
•
Terminal Radar Approach and Departure Control Areas
(TRACON)
•
Enroute Air Traffic Control Centers (ARTCC)
•
Air Traffic Control Systems Command Center (central flow
control) - ATCSCC
An information component of ATC also includes a multitude of
Flight Service Stations to provide weather and flight plan
approvals:
•
Flight Service Stations (FSS)
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Schematic of ATC ARTCC Representation
Sectors at FL400
36
Washington
Enroute Center
35
Atlanta
Enroute Center
Latitude (deg.)
34
33
113
91
131
126
129
32
31
87
61
62
30
23
24
29
93
51
115
86
Jacksonville
Enroute
Center
89
49
77
40
119
121
Sector
143
55
75
84
28
Miami
Enroute Center
27
26
-88
-86
-84
-82
-80
-78
-76
Longitude (deg.)
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Representation of ATCT and TRACON
Top View
Side View
5,200 ft.
Class C Airspace
3,800 ft.
3,400 ft.
2,132 ft.
Virginia Tech Airport
1,176 ft.
Roanoke Airport
22 nm
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Importance of ATC Domain Areas in
Communications
Each ATC domain area has specific aviation data requirements
•
The exchanges of information (including weather) vary across
NAS according to the ATC domain area in question
•
The resolution of aviation weather services improves as each
flight transitions from ARTCC to the airport area due to the
physical resolution of the weather sensors (i.e., Doppler radar,
Low Level Wind Shear, etc.) installed near or at the airports.
•
It is expected that as new advances in weather technology take
place the resolution of the minimum cell of weather information
will improve. However, it is likely that the density of services
would probably remain unevenly distributed across NAS ATC
services.
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Flight and Traffic
Information Services
(2020)
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Traffic Information System Strategy
Current state-of-the-art TIS systems use either one of two systems:
•
TCAS - Traffic Collision Avoidance System
- Uses secondary radar and dedicated antennas on-board the aircraft
to detect others
- Issues alerts and conflict resolution advisories to conflicting aircraft
- High cost and high resolution of aircraft position and conflict
maneuvers
•
ADS-B - Automated Dependence Surveillance system based on
Air-to-Ground VHF data link
- Derives aircraft position from air data computers
- Uses either satellite or land VHF (or L-band) data link
- Sampling rate varies from 5 min (oceanic) to 1-10 s (land)
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Traffic Analysis (Collaborative Routing)
Future Air Traffic Management systems will implement advanced
forms of Collaborative Routing (CR)
•
Under CR the premise is for flights to take both tactical and
strategic actions in flight to minimize conflicts with others
•
Flights have primary flight plans filed before departure
•
As each flight progresses a number of NAS conflicts and events
can change the character of the best strategy for each flight
•
Tactically: Each flight will alter their course to avoid other
aircraft (tactical boundary - TCAS type service)
•
Strategically: Each flight will probe near-strategic and strategic
events (included possible conflicts and sector capacity
boundaries) to plan a system optimal detour strategy
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Sample Collaborative Routing (SUA induced)
SUA
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Several detour
strategies need to be
studied while
performing
system optimal
collaborative
routing
strategies. Here
we show detours
around Special
Use Airspace
(SUA)
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Collaborative Routing (Weather Induced)
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Air Traffic Management Concept of Operations
(Circa 2020)
•
ADS-B surveillance information is widely available to all
airspace users
•
LEO communications are used in two ways:
- Backup system for ADS-B (critical element of ground surveillance)
- Provides traffic information services - collaborative routing and selfseparation information - to aircraft in the airspace (in all phases of
flight)
•
Aircraft communications messages can be catalogued into three
distinct groups:
- Tactical decision making information (typically flight critical)
- Near Strategic information (aircraft to AOC for example)
- Far strategic information (for long-range strategic planning)
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Tactical Air Traffic Information
Principal goal: collision avoidance and short-range route planning
•
Limited role for AOC
•
Interactions with ARTCC and Terminal Area sector controllers
Constraints:
•
Weather (close in + high accuracy)
•
Positions of other aircraft
•
SUA restrictions
Types of Messages: real-time position information, real-time
conflict detour strategies considering n flights and m possible flight
plan alternatives.
Enroute/terminal ATM sectors are modeled in great detail.
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Near Strategic Air Traffic Management
Information
Principal goal: overall airspace efficiency
•
Strong AOC role (for airline flights)
•
Strong interaction with FAA ATC services (for all flights)
-
Interaction with FAA Systems Command Center (ATCSCC)
-
Modest interaction with Flight Service (FS) stations and
ARTCC
System Constraints:
•
Enroute capacity (e.g., sector capacities)
•
Weather patterns and SUAs
•
Airport capacity constraints
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Near Strategic Air Traffic Management
Information
Types of messages:
•
Plan-ahead traffic information solution in the near strategic
boundary
•
The character of the messages is also real-time but of have less
priority that previous case
Enroute/terminal ATM sectors are modeled in moderate detail (a
single lumped queueing model is enough).
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Airborne-Ground TIS/FIS Network
•
Aircraft form a distributed computing network
•
Distributed control algorithms devise aircraft maneuvers
(advanced real-time tactical and strategic flight plan
functionality)
•
Other services exist (TCAS) for last-minute conflict resolution
strategies)
•
Other services exist (ADS-B) to complement the tactical and
near-strategic pilot situational awareness
•
For initial conceptualization we assume that most of the ATM
system wide-optimization computations occur at a ground
facility (called ATM Center - part of ARTCC or TRACON)
where faster CPUs exist.
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Airborne Network Information
Satellite
Satellite
To ATM
To ATM
Other Air-Air
(TCAS, ADS-B)
From ATM
Air-Air
Air-Ground
ATM Service
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Estimating Conflicts in the Airspace (Necessary to
Assess Future CNS Concept of Operations)
•
First order approximation using previous studies
•
A study by Trani, Sherali, Smith and Srinivas using 6000 random
flights in ZMA and ZJX (NEXTOR Report RR-98-12)
•
Under current ATC and NAS system conditions about 4.7% of
the flights in the enroute airspace are in conflict (9.26 km. shell)
- Rigid airway structure (most flight plans use standard fixes)
- Use of the National Route Program (NRP) for 7-10% of the flights
•
Under Reduced Vertical Separation Mode (RVSM) conditions
the number of blind conflicts is expected to decrease to 3.1%
•
The geometries of the conflicts will change moderately
•
Several studies confirm that random airspace conflicts grow
quadratically with the number of flights.
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Geometry of ZMA and ZJX
34
114
90
131
33
126
129
Latitude (deg.)
32
94
87
31
86
61
119
62
30
23
24
29
50
117
89
142 11248
77
40
54
84
154
75
W497B
158
28
326
324
177
27
152
302
210
26
121
178
25
172
273
277
171
299
275
276 274
24
-88
-86
-84
-82
-80
300
-78
307
305
-76
Longitude (deg.)
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Sample Conflict Results (ZMA and ZJX)
Baseline Scenario Statistics
Conflict Type
Vertical Transition Conflicts
Enroute Conflicts
Severity 1
127
28
Severity 2
91
19
Severity 3
13
9
Total
231
56
Conflict Type
Vertical Transition Conflicts
Enroute Conflicts
Severity 1
104
8
Severity 2
66
6
Severity 3
4
2
Total
174
16
RVSM System Statistics
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Other Interesting Facts About Airspace Conflict
Studies Used in Our Analysis
•
The same study (refer to Train, Sherali, Smith and Srinivas,
1998) concluded that:
•
The activation of a large SUA off the coast of Florida (W-497B)
results in sector traffic loads increasing by up to 200% if no
strategic action is taken by ATC personnel in distributing
affected flights.
-
•
This is the result of detours for traffic that normally uses
airways AR-1, AR-3, AR-7 and A699 off the coast.
These facts are important in trying to understand the possible
interactions among aircraft in Free Flight mode in a
distributed ATC/ATM system.
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Conflict Time Statistics
Conflict times (vertical transition conflicts)
ARTCC
Baseline
Mean (standard dev.)
(min)
RVSM
Mean (standard dev.)
(min)
Cruise Climb
Mean (standard dev.)
(min)
ZMA/ZJX
4.56 (11.52)
2.85 (9.91)
2.86 (9.89)
ZID/ZTL
3.04 (2.40)
2.40 (5.47)
2.27 (5.18)
ARTCC
Baseline
Mean (stand. dev.)
(min)
RVSM
Mean (stand. dev.)
(min)
Cruise Climb
Mean (stand. dev.)
(min.)
ZMA/ZJX
5.37 (9.04)
9.18 (11.84)
5.15 (9.42)
ZID/ZTL
6.31 (10.86)
6.21 (10.94)
4.48 (10.30)
Conflict times (enroute conflicts)
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Latitude (deg)
Flight Plans (Baseline in ZID)
Longitude (deg)
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Latitude (deg)
Flight Plans (Free Flight RVSM
Longitude (deg)
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Flight Tracks of Aircraft Affected by SUA Closure
1997 Data
30.6
119
121
30.4
30.2
48
Latitude (deg)
30
29.8
29.6
Aircraft Tracks
(ZJX SAR Data)
29.4
29.2
154
29
28.8
28.6
-79.5
-79
-78.5
Longitude (deg)
-78
-77.5
158
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Example of SUA (KSC Warning Areas)
Scale (nm)
Touchdown
205 KTAS
50
0
Northern Track
Reentry Profile
Ascent Profiles
East Track
50,000 ft.
Mach 1.0
90,000 ft.
Mach 1.6
167,000 ft.
Mach 3.5
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Southern Track
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RLV Operation Impacts
GA Operations
FAA
ATC Infrastructure
ATC Workload
DOC Cost per flight
Travel time cost
Commercial Ops.
Non-airspace
users
DOC Cost per flight
Travel time cost
Service costs/benefits
Launch delay
penalties
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