Statistical Decision Support Tools for System-Oriented Runway Management

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NNX11CB70C
Agency Tracking Number: 095863
Amount: $600,000.00
Phase: Phase II
Program: SBIR
Awards Year: 2011
Solicitation Year: 2009
Solicitation Topic Code: A3.01
Solicitation Number: N/A
Small Business Information
Optimal Synthesis, Inc.
CA, Los Altos, CA, 94022-2777
DUNS: 829385509
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 P. K. Menon
 Principal Investigator
 (650) 650-8585
 menon@optisyn.com
Business Contact
 P. Menon
Title: Business Official
Phone: (650) 650-8585
Email: menon@optisyn.com
Research Institution
 Stub
Abstract
The feasibility of developing a statistical decision support system for traffic flow management in the terminal area and runway load balancing was demonstrated in the Phase I research. The methodology employed an advanced estimation algorithm based on a queuing network model of the runway and the terminal area, and statistical decision theory to formulate traffic flow decisions. Radar data from the San Francisco terminal area was used in the feasibility demonstration. Component technologies developed in Phase I work can be used for synthesizing real-time statistical decision support tools for runway configuration management and arrival/departure scheduling.Phase II work will use the Phase I algorithms for developing decision support tools for NASA's System-Oriented Runway Management program elements. Queuing networks of runways, taxiways, gates, and terminal airspace will form the foundation of the decision support tool. Predicted demand, historic traffic data and real-time measurements will be combined in an estimator to generate the statistical distributions of the queuing network parameters. These will then be used in conjunction with methods from Statistical Decision Theory to generate actionable decisions. Phase II research will develop a software package implementing these algorithms, which can be evaluated in human-in-the-loop and operational settings during the Phase III work.

* information listed above is at the time of submission.

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