the information in this document is proprietary to, and the property of sensis corporation. it may...

The information in this document is proprietary to, and the property of Sensis Corporation. It may not be duplicated, used, or disclosed in whole or in part for any purpose without express written consent.

Probabilistic NAS Platform

George Hunter, Diego Escala

Sensis Corporation

January 27, 2010

2 Sensis Corporation Proprietary Data – See title page

Outline

PNP design overview and philosophy

Probabilistic modeling (George)

PNP software architecture (Diego)


Outline





PNP Design Overview and Philosophy Requirements

•NextGen performance and benefits assessment Incorporate key aspects of NAS from the ground up

– Uncertainty, weather

•Design environment, including real-time evaluation

•1 hour run time (nominally), easy to use

Design•Don’t try to solve every problem

NAS has significant dynamic range

•Select modeling fidelity: 15 minute/sector discretization

Spatially: ~10s nmi

Temporally: 15 min

Tactical: CDR, etc. Strategic: TFM, DAC, FP, etc.

Implicit / nodal modeling Explicit modeling


PNP Design Overview and PhilosophyDecouple simulation and decision making

Build a little – test a little•Continuous improvement

•Expandable architecture

Emphasis on testing, validation and process


Real-time

Fast-time

Airport weather impact models

Airspace weather impact models

Weather-integrated decision making

Probabilistic modeling / decision making

Traffic flow management

Dynamic airspace configuration

Surface traffic modeling

Terminal area modeling

Super density operations

Fuel burn modeling

Emissions modeling

Trajectory-based operations

Separation assurance

Plug-n-play

Fast run-time

Capabilities SummaryExisting Can Support

√√√√√√√√

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Outline





Probabilistic Modeling

Example uncertainties•System capacity and loading forecasts

•Airports and sectors


Forecasted Airport CapacityIllustration of our approach

Step 1 TAF

Step 2Mean and Sigma

for Ceiling, Visibility and Wind

Speed

Step 3

Mean and sigma:

Ceiling

Visibility

Wind Speed

Forecasts:

Ceiling

Visibility

Wind Speed

Forecasts for Ceiling, Visibility and Wind Speed

Distributions for Ceiling, Visibility and Wind Speed


Forecasted Airport Capacity

Step 4

Model

Step 5

Step 6

Arrivals / hour

Dep

artu

res

/ hou

r

VFR

IFR

VFR Cap Dist

IFR Cap Dist


Forecasted Airport Capacity

Airport capacity distribution that takes into account ceiling, visibility and wind speed forecasts

Step 7


Outline





PNP Software Overview

Client-server architecture

Predictive modeling

Two runtime modes•Fast-time (simulation)

•Real-time (live)


Fast-time Mode

Archived Wx/Tx DataPNP

Client 1

Client 2

Client n

Local Network

Static NAS Data


Live (Real-time) Mode

Client 1

Client 2

Client n

Local Network Internet

Wx/TxData Server

PNP

Static NAS Data


Probabilistic NAS Platform (PNP)

Weather Data

Reports

Network

MATLAB®

ScriptingInterface

NASDatabase

MATLAB® Client

External Client(Any Language)

ClientAs Middleware

Java Client

Decis

ion

makin

gN

AS

Sim

ula

tion

Performance Data

Flight Data

Graphical User InterfacePlan View Display

PNP Architecture


Probabilistic NAS Platform (PNP)

Weather Data

Reports

Network

MATLAB®

ScriptingInterface

NASDatabase

Decis

ion

makin

gN

AS

Sim

ula

tion

Performance Data

Flight Data

Graphical User InterfacePlan View Display

PNP Architecture


PNP Communications Basics

Subscription model•Clients can specify which messages they need, and at what

interval they need each

Serialized Java objects sent over TCP/IP

Compression supported


Advance simulation

time

Send messages for

interval

Send heartbeat to

clients

Wait for client responses

PNP Communications Cycle


Step 1: Register with

PNP

Step 2: Request Data

Updates

Step 3: Handle Data

Updates

Client-Server Communications


Registering with PNP

public MyPnpClient(){

// Connect to the PNP server on the local computer.// buildReceiveRequests() specifies message

subscriptionsm_Client = new ObjectClientMessageManager(“localhost”,buildReceiveRequests());

}


Subscribing to Messagesprivate ArrayList<MessageReceiveRequest> buildReceiveRequests(){

ArrayList<MessageReceiveRequest> requests = newArrayList<MessageReceiveRequests>();

// Add a request to receive PnpFlightDetails every 15 minutesrequests.add(new MessageReceiveRequest(PnpFlightDetails.class,

15));

// Add a request to receive AirportLoading every 15 minutesrequests.add(new MessageReceiveRequest(AirportConditions.class,

15));

// Add a request to receive SectorLoading every 15 minutesrequests.add(new MessageReceiveRequest(TerminalConditions.class,

15));

return requests;}


Responding to PNP

BatchResponse response = newBatchResponse(1,

aoc.getDelayMap(), aoc.getRerouteMap(),

aoc.getInflightRerouteMap());

m_Client.send(response);

[AOC Example]


Data TranslationNAS Data

• Wx radar• Winds/temps• METAR/TAF• Turbulence• Icing• Flight plans• Flight positions• Sector def’ns• Airport capacities

Client-usable data

• Wx-degraded sector capacities

• Sector capacity forecasts

• Sector loading• Sector loading

forecasts• Airport capacity

distribution based on wx

• Airport conditions• Flight trajectories


Data Available from PNP Server

Flight Data• Flight Trajectory (1-

min)

• Current Position

• Sector Schedule

NAS Data• Airport Congestion

• Airport Loading

• Operations per airport

Airspace Data• Sector Boundaries

• Sector Congestion

Weather Data• Forecasts

• Weather-related Congestion


Programmable Client Functionality

Flight Plan Amendments•Delay flights

•Reroute flights While at gate or in-flight

Airspace Modification / Definition•Number of sectors

•Sector boundaries

•Sector capacities

•Airport capacities


Uncertainty Modeling Process in ProbTFM

PNP

Implement reroutes and delays

ProbTFM

Compute sector capacity distributions

Compute congestion costs for current departures based on sector loading, capacity

Compute delays and reroutes for flights that

exceed congestion thresholdSend delays to PNP

PNP

Send sector loading for a/c enroute

Send expected sector loading for a/c at gate

Send wx-degraded sector capacities

Send airport capacity distributions

Send departures for current interval


1. George Hunter, "Meta Simulation Results for Simultaneous Dynamic Resectorization and Traffic Flow Management," AIAA Digital Avionics Systems Conference (DASC), Orlando, FL, October, 2009.

2. George Hunter, Robert A. Vivona, Carlos Garcia-Avello, "Preliminary Evaluation of Trajectory Prediction Impact on Decision Support Automation," AIAA Digital Avionics Systems Conference (DASC), Orlando, FL, October, 2009.

3. Huina Gao, George Hunter, "Future NAS-Wide User Gaming Preliminary Investigation," AIAA Digital Avionics Systems Conference (DASC), Orlando, FL, October, 2009.

4. George Hunter, "Testing and Validation of NextGen Simulators," AIAA Modeling and Simulation Conference, Chicago, IL, August 2009.5. George Hunter, "Preliminary Assessment of Interactions Between Traffic Flow Management and Dynamic Airspace Configuration Capabilities," AIAA

Digital Avionics Systems Conference (DASC), St. Paul, MN, October, 2008.6. George Hunter, et. al., "Toward an Economic Model to Incentivize Voluntary Optimization of NAS Traffic Flow," AIAA ATIO Conference, Anchorage,

AK, September, 2008.7. George Hunter, "Sensitivity of the National Airspace System Performance to Weather Forecast Accuracy," Integrated Communications, Navigation and

Surveillance Conference (ICNS), Herndon, VA, May, 2008.8. George Hunter, Kris Ramamoorthy, "Integration of terminal area probabilistic meteorological forecasts in NAS-wide traffic flow management decision

making," 13th Conference on Aviation, Range and Aerospace Meteorology, New Orleans, LA, January, 2008.9. Kris Ramamoorthy, George Hunter, "The Integration of Meteorological Data in Air Traffic Management: Requirements and Sensitivities," 46th AIAA

Aerospace Sciences Meeting and Exhibit, Reno, NV, January, 2008.10. George Hunter, Ben Boisvert, Kris Ramamoorthy, "Advanced Traffic Flow Management Experiments for National Airspace Performance

Improvement," 2007 Winter Simulation Conference, Washington, DC, December, 2007.11. Kris Ramamoorthy, George Hunter, "Evaluation of National Airspace System Performance Improvement With Four Dimensional Trajectories," AIAA

Digital Avionics Systems Conference (DASC), Dallas, TX, October, 2007.12. Kris Ramamoorthy, Ben Boisvert, George Hunter, "Sensitivity of Advanced Traffic Flow Management to Different Weather Scenarios," Integrated

Communications, Navigation and Surveillance Conference (ICNS), Herndon, VA, May, 2007.13. George Hunter, Ben Boisvert, Kris Ramamoorthy, "Use of automated aviation weather forecasts in future NAS," The 87th American Meteorological

Society Annual Meeting, San Antonio, TX, January, 2007.14. Kris Ramamoorthy, George Hunter, "Probabilistic Traffic Flow Management in the Presence of Inclement Weather and Other System Uncertainties,"

INFORMS Annual Meeting, Pittsburgh, PA, November, 2006.15. Kris Ramamoorthy, Ben Boisvert, George Hunter, "A Real-Time Probabilistic TFM Evaluation Tool," AIAA Digital Avionics Systems Conference

(DASC), Portland, OR, October, 2006.16. George Hunter, Kris Ramamoorthy, Alexander Klein "Modeling and Performance of NAS in Inclement Weather," AIAA Aviation Technology,

Integration and Operations (ATIO) Forum, Wichita, KS, September 2006.17. Kris Ramamoorthy, George Hunter, "A Trajectory-Based Probabilistic TFM Evaluation Tool and Experiment," Integrated Communications, Navigation

and Surveillance Conference (ICNS), Baltimore, MD, May, 2006.18. Kris Ramamoorthy, George Hunter, "Avionics and National Airspace Architecture Strategies for Future Demand Scenarios in Inclement Weather," AIAA

Digital Avionics Systems Conference (DASC), Crystal City, VA, October, 2005.19. George Hunter, Kris Ramamoorthy, Joe Post, "Evaluation of the Future National Airspace System in Heavy Weather," AIAA Aviation Technology,

Integration and Operations (ATIO) Forum, Arlington, VA, September 2005.20. James D. Phillips, “An Accurate and Flexible Trajectory Analysis,” World Aviation Congress (SAE Paper 975599), Anaheim, CA, October 13-16, 1997.

Publications


Questions?

Thank You

George HunterDiego Escala

the information in this document is proprietary to, and the property of sensis corporation. it may...

Documents

wind speed slide

wind speed step

property of sensis corporation

title page pnp design

wind speed distributions

modeling fidelity

process slide

approach step