A Queuing Model-Based System for Triggering Traffic Flow Management Algorithms

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NNX10CC14P
Agency Tracking Number: 095863
Amount: $99,996.00
Phase: Phase I
Program: SBIR
Awards Year: 2010
Solicitation Year: 2009
Solicitation Topic Code: A3.01
Solicitation Number: N/A
Small Business Information
95 First Street, Suite 240, 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) 559-8585
 menon@optisyn.com
Business Contact
 P. Menon
Title: Business Official
Phone: (650) 559-8585
Email: menon@optisyn.com
Research Institution
N/A
Abstract
Next generation air traffic management systems are expected use multiple software tools and quantitative methods for managing traffic flow in the National Airspace. NASA and other aerospace research centers are involved in developing advanced numerical algorithms for strategic traffic flow management. These algorithms can be invoked at fixed time intervals, or can be employed whenever adverse traffic flow conditions occur. In order to avoid spurious responses, the control algorithms should be used only when actual traffic flow problems are likely to arise, and not in response to normal flow variations. Queuing models describe the aggregate stochastic behavior of the national airspace, and can provide not only mean flow characteristics, but also the expected variations. This proposal advances the development of a queuing model-based methodology for triggering traffic flow management algorithms. The approach , based on the measured state of the national airspace system. The approach exploits recently-developed queuing models of the NAS, together with recent advances in estimation theory. Phase I research will demonstrate the feasibility of developing the traffic flow management triggering system using a simulation model of the national airspace system. Phase II research will integrate this methodology with NASA's traffic flow management algorithms, and assess the overall system performance n the ACES environment. Algorithms and software developed under the SBIR project will be delivered to NASA at the end of Phase II work.

* Information listed above is at the time of submission. *

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