ACES-Based Testbed and Bayesian Game-Theoretic Framework for Dynamic Airspace Configuration

Period of Performance: 01/01/2010 - 12/31/2010

$600K

Phase 2 SBIR

Recipient Firm

Intelligent Automation, Inc.
15400 Calhoun Dr, Suite 190
Rockville, MD 20855
Firm POC
Principal Investigator

Abstract

This SBIR effort is focused on developing a Dynamic Airspace Configuration (DAC) concept where-in ARTCCs can benefit from re-configuring airspaces based on Traffic Flow Management (TFM) restrictions, and the development of a preliminary Airspace Concept Evaluation System (ACES)-framework and initial algorithms to demonstrate that ARTCCs need to engage in a coordination framework of exchanging TFM restriction until they determine mutually-agreeable optimal airspace configuration. The development of algorithms that leverage and recognize the interactions and interdependencies between DAC and TFM is the key innovation of this effort. Some examples of expected operational improvements include 1) reduction in congestion and delays when sector capacities (Monitoring Alert Parameter or Dynamic Density) are violated, 2) reduction in controller workload and improved safety, 3) ability to accommodate user preferred routes and weather uncertainty and 4) achieve a balance between airborne delay and grounding holding delay. The SBIR Phase-I effort demonstrated how a combined DAC-TFM algorithm determines an optimal airspace configuration different from a DAC-only algorithm and could result in minimization of peak count and dwell time variance. The effort also included the design and preliminary implementation of a TFM model that uses ARTCC sector configuration to determine the delays that is generated, absorbed and propagated. The Phase II effort includes development of DAC-TFM framework as an enhancement to NASA's ACES- DADS (Dynamic Airspace Design Service) work and interaction of NASA's airspace partitioning DAC algorithms such as MxDAC, DAU slicing and Sector Combination algorithms with the TFM models using the same framework.