NASA SBIR 2020-I Solicitation

Proposal Summary

 20-1- A3.02-5159
 Increasing Autonomy in the National Airspace System (NAS)
 An Autonomous Severe Weather Trend Monitor for Improved System-Wide TFM Execution
SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
AvMet Applications
1800 Alexander Bell Drive
Reston, VA 20191
(571) 335-7079

Principal Investigator (Name, E-mail, Mail Address, City/State/Zip, Phone)

Alexander Klein
AvMet Applications Incorporated Reston, VA 20191 - 2019
(703) 801-8381

Business Official (Name, E-mail, Mail Address, City/State/Zip, Phone)

Mark Klopfenstein
AvMet Applications Incorporated Reston, VA 20191 - 2019
(703) 453-9192
Estimated Technology Readiness Level (TRL) :
Begin: 2
End: 4
Technical Abstract (Limit 2000 characters, approximately 200 words)

Severe weather remains the main disruptor to airspace operations and traffic managers’ actions. An autonomous airspace system will need to automatically ingest the latest weather forecast(s), reason about its impact, and provide actionable guidance to human operators (in the transition) and/or other service-based airspace automation systems. Our proposed Innovation lays the foundation for such automated weather reasoning and focuses on a specific aspect of autonomous operation with clearly stated practical needs—TMI impact reduction—to demonstrate its capabilities.

Today’s manually executed TMIs are often overly restrictive, and once activated are not routinely reviewed for possible reduction in scope or duration resulting in excess delays & costs. We propose an autonomous system which will monitor the latest weather, traffic, implemented TMIs, and look for opportunities to reduce their impact on the NAS. The application will:

  • Continuously ingest latest NOAA weather forecasts, air traffic, and TMI information from FAA SWIM feed
  • Perform automated Forecast Trend Analysis to compare the latest information to previous forecast(s) and NAS status, and identify when an in-depth search for TMI reduction is warranted, e.g., when forecasts evolve toward less-severe
  • If warranted, run a set of parallel fast-time simulations starting from current NAS status and extending up to 6-8 hours ahead, combining two “what-if” series of experiments:
    1. Meteorologically sound range of alternative weather scenario outcomes representing the underlying forecast uncertainty
    2. Parameterized TMI reductions in scope and end times
  • Evaluate results (including comparison with the outcomes of previous cycles) to establish, with a required degree of confidence, if a non-trivial and specific TMI reduction opportunity exists
  • Alert relevant traffic managers for review and action
  • Continue autonomously monitoring and looking for additional TMI reduction opportunities throughout the operational day
Potential NASA Applications (Limit 1500 characters, approximately 150 words)

This autonomous severe weather trend reasoning application supports and could be part of NASA’s goal to enable successful transition to an autonomously operating airspace system. Additionally, this initial application could plug into various NASA simulations needing automated weather and/or TMI monitoring. The underlying technology can provide the framework for other autonomous weather impact reasoning systems that support future airspace uses by new entrants including UAM and UTM.

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words)

A direct application of the system to be built is for the FAA ATCSCC who plans and executes NAS-level TMIs. By using this technology, thousands of delay minutes could be saved. A modified version of the technology is applicable to airline operations to help them more readily adapt to changes in weather and TMIs. Other potential applications include UAS, UAM, and international ANSP operators.

Duration: 6

Form Generated on 06/29/2020 21:08:02