Artificial Intelligence for Refining Multi-Aircraft Testbed Environments

Award Information
Agency:
National Aeronautics and Space Administration
Branch
n/a
Amount:
$100,000.00
Award Year:
2011
Program:
SBIR
Phase:
Phase I
Contract:
NNX11CD11P
Agency Tracking Number:
105908
Solicitation Year:
2010
Solicitation Topic Code:
A3.01
Solicitation Number:
n/a
Small Business Information
Aptima, Inc.
12 Gill Street, Suite 1400, Woburn, MA, -
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
967259946
Principal Investigator:
Nathan Schurr
Principal Investigator
(781) 496-2453
nschurr@aptima.com
Business Contact:
Thomas McKenna
Business Official
(781) 496-2443
mckenna@aptima.com
Research Institution:
Stub




Abstract
NASA is researching various concepts, procedures, standards, and technologies intended for NextGen Airspace. Complex, distributed airspace simulations that utilize experimental testbeds (e.g., Multi Aircraft Control System, or MACS) are vital research tools for these projects. However, managing the various complexities and coordination of agent-supported separation assurance can be challenging. This often creates undesired staffing and training requirements, workload, and susceptibility to human error that can disrupt planned scenario events. To address this issue, we propose to develop Artificial Intelligence for Refining Multi-Aircraft Testbed Environments (AIR-MATE). This proposed innovation will provide a MACS-interoperable software module that coordinates the behaviors of human-automation pairs in simulated NextGen airspace. This effort will leverage recent advancements in distributed constraints optimization and adjustable autonomy to analyze airspace simulations in a decentralized, parallel manner and solve problems locally for enhanced efficiency. This technology will reduce the workload and staffing requirements in current NextGen simulations, while ensuring the desired scenario events and separation assurance is properly executed. The results of the AIR-MATE effort will be a more controlled and high-fidelity testbed environment that will aid researchers, increase the quality of NextGen research, and ultimately benefit the development of NextGen concepts.

* information listed above is at the time of submission.

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