A New Paradigm to Model Aircraft Operations at
Airports:The Virginia Tech Airport SIMulation Model
(VTASIM)
Dr. Antonio A. Trani
Dr. Hojong Baik
Transportation Engineering
Dr. Julio Martinez
Vineet Kamat
Construction Engineering
Department of Civil and Environmental Engineering
Virginia Tech
NEXTOR Research Symposium
November 13, 2000
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Outline of this Presentation
•
Virginia Tech efforts in airport simulation and modeling
future NAS operations
•
Components of VTASIM
•
•
•
Algorithms
•
Sample results
Dynamic Construction Visualizer
•
Model description
•
Visualization post-processor
Final Remarks
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The Virginia Tech Airport Simulation Model
•
Hybrid simulation model
•
Microscopic in nature (second-by-second output if
required)
•
Models aircraft operations around the airport terminal area
(includes sequencing)
•
Models ATC-pilot interactions explicitly (voice and
datalink)
•
Dynamic taxiing plans (true dynamic traffic assignment)
•
Developed under the auspices of the FAA NEXTOR basic
research funding (ATM agenda)
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Framework for VTASIM
Nominal Schedule
for Arrivals
Separation
Rule
Nominal Schedule
for Departures
Aircraft Sequencing Problem
(ASP)
Optimal sequence and schedule
Time-dependent O-D
(between gates and runways)
Taxiing Network
Configuration
Network Assignment Problem
(NAP)
Simulation
(VTASM)
Optimal taxiing routes
for arrivals and departures
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Development of a Simulation Model: VTASIM
•
•
Existing microscopic simulation models for airport studies:
•
SIMMOD, TAAM (airfield and airspace analyses)
•
Airport Machine (airfield analysis)
•
RAMS (airspace analysis)
These models are:
•
discrete-event simulation models,
•
less accurate in describing the aircraft movement,
•
do not describe communication process (ATC-pilot).
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VTASIM is a Hybrid-type Simulation Model
•
A discrete-event simulation model
•
•
A discrete-time simulation model
•
•
Represents a system by changing the system status at the
moments when an event occurs
Represents a system checking and changing the system status
at every step size (dt).
VTASIM is a hybrid-type simulation model
•
Movement: represented by discrete-time simulation model
•
Communication: represented by discrete-event simulation
model
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Entities and State Variables in VTASIM
Entities:
•
Two types of controllers (i.e., local and ground controllers),
•
Two types of flights (i.e., departing and arriving flights), and
•
Facilities including gates, taxiways, runways, etc.
State Variables:
•
Controllers: controlling state, next communication time,
•
Flights: communication state, next communication time,
movement state, next movement time, speed, acceleration,
position, etc.,
•
Gates, taxiways, runways: current flight(s).
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State Diagram for Arriving Aircraft Movement
On Final
Communication
Recieved Landing
Clearance
Flare
Free
Rolling
Braking
Coasting
Exiting
R/W
No
Parked
(at gate)
Taxiing
Area
Holding
Recieved Taxiing
Clearance
Communication
No
Waiting
in Line
(Gate Arrival Queue)
Waiting to
Taxi
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Ground Control Model Features
•
Communication interactions between ATC controllers/data
link and each aircraft is explicitly modeled
•
Delay analysis. There are two types of delay:
•
Traffic delay due to the traffic congestion on taxiway/runway
•
Communication delay due to the controller/data link
communications
•
Dynamic aircraft-following logic
•
Static and dynamic route guidance for taxing
•
By applying dynamic guidance logic, more realistic and
efficient routing is possible.
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State Diagram for Communication (Voice Channel)
Start Communication
Put this flight strip to
progressing box.
Is controller busy?
No
Sending
Request
(t1)
Waiting
Command
(t2)
Receiving
Command
(t3)
Sendin
Confirm
(t4)
Yes
WaitNext
Comm.
(t0)
End Communication
Ready to
comm.
Sendin g
Confirm.
(t4)
Receiving
Command
(t3)
Wait
Contact
from
Controller
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Received clea
No
(i.e., Delayed)
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State Diagram for Controller’s Flight Data Strips
Completed
Flight Strips
Completed
Flight Strips
Processing
Flight Strips
Processing
Flight Strips
Pending
Flight Strips
Pending
Flight Strips
Ground controller’s
flight strip organization
Local controller’s
flight strip organization
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Algorithm: Dynamic Taxiing Route Plan
n=1
Considers time-dependent
network loading
Employs an incremental
time-dependent
network assignment strategy
Based on time-dependent
shortest path algorithm
Find TDSP
for the n th aircraft
(by using
TDSP algorithm)
Assign the nth
aircraft on the
links involved in
the TDSP over
time intervals
Update
link travel times
n = last vehicle?
No
n = n+1
Yes
End
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Algorithm: Dynamic Taxiing Route Plan
1006
1006
1008
1007
1008
1007
2005
2005
21
2006
1010
1009
1013
1011
2
21
1009
1
1
2009
1012
1012
3
2007
1015
4
2011
5
1017
2010
1018
7
2012
1021
2013
2014
11
1026
33
9
11
2016
1028
2020
3
33
1026
1029
1025
1027
2016
1030
1031
2017
2018
2014
10
1031
1033
2015
1023
1024
1027
2012
1021
2013
12
1025
1030
1029
1032
1020
8
10
1024
1028
7
2015
1023
9
1019
6
8
12
2010
1018
1019
1020
2007
1015
1016
4
2011
1017
6
2008
1014
1016
5
1013
2009
2
2008
1014
3
2006
1010
1011
2017
1032
2019
2021
01
Statically assigned path
2018
1033
2020
3
2019
2021
01
Time-dependent assigned path
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Aircraft Following Model
Ht
vt+dt
Basic equations of motion to characterize the aircraft taxiing
following model
vtd+ ∆t = v f (1 −
Hj
Ht
)
ant ++∆1 t = (vtd+1 − vt ) / ∆t
Speed equation of motion
Acceleration equation of motion
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Conflict Detection and Resolution Model
Second or later flights on this link
(do follow the leading flight
by car-following logic)
First flight on this link
(Need to check
the potential collision)
Conflicting flights coming
toward thecommon intersection
15.6(sec)
20.8(sec)
F1
Current position
of flight
Start point
of Intersection
F3
Legend :
30.7(sec)
F2
the current operation direction
Expected arrival time to
the common intersction
(ET i)
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Four Phases of the Landing Procedure
Exit point
Touchdown Point
Air Speed
Altitude
Disatance
Runway
CO
Exit
Taxi
BR
FR
FL
FL : Flare
FR: Free-rolling
BR: Braking
CO: Coasting
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Example of Output File (1): Log File
Second-by-second statistics can be obtained in VTASIM
Time = 320.000
DEP_1 (4.27860, 7.23847)
readyToCommunicate
clearToTakeOff rolling
228.557 5.65931 2006 -> 2005
347.582 322.875 8907.85
Aircraft ID and Position
Acft. COMM State
Acft. Permission
Acft. speed, accel. and
link information
DEP_2 (3.44770, 3.71363)
readyToCommunicate
clearToTaxi
taxiingToDepQue
27.3409 0.000000 1031 -> 2018
782.058 727.237 3832.22
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Example of Output File (2): Summary File
------------------------------- SUMMARY -------------------------------
Flight (Departure DEP_1, B727-100, Gate 1, Runway 36)
Enters into the simulation at
: 1 sec.
Taxiing Duration
: 73 - 217
Taxiing Delay
: 2.22827
Nominal Takeoff Time (= NTOT)
: 186
Sequenced Takeoff Time (= STOT)
: 268
Actual Takeoff Time (= ATOT)
: 289
Runway Occupancy Time (= ROT)
: 289 - 328
Sequenced Delay
(= ATOT - STOT) : 21
Runway Delay
(= ATOT - NTOT) : 103
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Example of Output: Departure Profiles
12000
ROT
10000
Distance (ft)
8000
Takeoff
Distance
6000
4000
Taxing
Distance
2000
Minimum
Separation
0
0
50
100
150
200
250
300
350
400
450
500
550
600
Time (second)
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Local Controller “Workload” Metric
Local controller’s workload (2)
(Utilization factor = 0.607)
10
Aircraft Under Control
No. of aircraft contacting controller
9
8
7
6
5
4
3
2
1
0
0
200
400
600
800
1000
1200
1400
1600
1800
1800
(second)
TimeTime
(seconds)
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Delay Curves for Mixed Runway Operations
Average Delay per Aircraft (seconds)
Average Aircraft Delay (seconds)
900
800
Simulation +
Average
o
700
600
500
400
300
TextEnd
200
100
0
10
15
20
25
30
35
40
Number of Operations
45
50
55
60
Aircraft Operations per Hour
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Sample Aircraft Delays Curves
Voice channel - three assignment techniques studied
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Sample Delay Curves (datalink analysis)
Datalink active - three assignment techniques studied
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Dynamic Construction Visualizer (DCV)
•
General-purpose tool for 3D visualization of discrete-event
and continuous simulation models
•
Developed by Dr. J. Martinez and V. Kamat (Virginia
Tech)
•
Independent of simulation tools
•
Processes log (trace) files to depict motion
•
Uses 3D CAD models of simulation entities
•
Language that merges together modeling and CAD tools to
achieve dynamic visualization
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The DCV Language
TIME 0;
CLASS Airfield Airfield.wrl;
CREATE TheAirfield Airfield;
PLACE TheAirfield AT (0,0,0);
TIME 6;
CLASS B747 B747.wrl;
CREATE NW56 B747;
PLACE NW56 ON TaxiToRunway;
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Building DCV Files
•
Files for actual modeled operations can be very long
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Not meant to be typed by humans
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Meant to be generated by simulation models as they run
•
Practically any simulation model can produce DCV
compatible trace files
•
VTASIM
•
SIMMOD
•
TAAM
•
RAMS, etc.
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Tools and Implementation
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Microsoft Windows™ (98, NT, 2000)
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Visual C++ 6.0
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SGI Computer Graphics APIs (Libraries)
•
Cosmo3D
•
OpenGL Optimizer
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Sample DCV Graphic User Interface
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Sample DCV Graphic User Interface
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Sample DCV Graphic User Interface
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Sample DCV Graphic User Interface
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Acknowledgements
•
The support of the Federal Aviation Administration (FAA)
in the development of Air Traffic Management (ATM
Agenda) models is gratefully acknowledged.
•
The support of the National Science Foundation (NSF) in
the development of the Dynamic Construction Visualizer is
gratefully acknowledged.
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Remarks about VTASIM
•
The model characterizes aircraft movement at the
microscopic level
•
Provides better insight of traffic dynamics around the airport
taxiway-apron network
•
Provides better interaction between aircraft operating on
runway and taxiway networks
•
ATC-pilot voice or datalink exchanges are modelled
explicitly
•
With proper adaptations and calibration VTASIM could be
employed as an ATC advisory system with aircraft
predictive capabilities (sequencing is explicitly modeled)
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Remarks about DCV
•
The model serves as a good visualization complement to
any discrete-event or discrete-time simulation model
•
Provides powerful visualization tool could be adapted for
real-time use if desired
•
Excellent 3D graphics with open standards (OPEN GL API)
•
•
Portable
•
Easy to use
A good example on how small projects at NEXTOR
universities provide synergy to work being sponsored by
FAA and other agencies
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Final Remarks
•
Fast-time model requirements are changing to keep up with
changes in NAS procedures and automation
•
Challenging ATC-pilot modeling requirements expected of
future ATM concepts
•
Planned ATC/ATM changing strategies associated with
Free-Flight and automated ground control operations at
airports would require radical changes into the logic of
existing NAS simulation models in the long term
•
The research models presented is a low level effort in the
development of a new generation of tools to understand a
critical part of NAS.
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