80NSSC21C0566

Small Business Innovation Research Program (SBIR) Phase II

An Autonomous Severe Weather Trend Monitor for Improved System-Wide TFM Execution

Severe weather remains the main disruptor to airspace operations and traffic managersrsquo; actions. An autonomous airspace system will need to automatically ingest the latest weather forecast, reason about its impact, and provide actionable guidance to human operators and/or other service-based airspace automation systems. Our Phase I prototype has laid the foundation for such automated weather reasoning, focusing on a specific aspect of autonomous operation with clearly stated practical needsmdash;TMI impact reductionmdash;to demonstrate its capabilities.Todayrsquo;s manually executed TMIs are often overly restrictive and are not routinely reviewed for possible reduction in scope or duration, resulting in excess delays amp; costs. To address this, we are developing an autonomous system which will continuously ingest latest weather forecasts, air traffic amp; TMI information, perform automated Forecast Trend Analysis to compare this latest information with previous forecast(s), identify when forecast trends toward less-severe, and if warranted, launch a search for TMI reduction opportunities. A ldquo;what-ifrdquo; series of parallel fast-time NAS simulations, projecting current situation up to 8 hours ahead, combines meteorologically sound range of potential weather outcomes (given the forecast uncertainty) and parameterized TMI reductions in scope and end times. The application will evaluate results (including those from prior cycles) to establish, with a required degree of confidence, if a non-trivial TMI reduction opportunity exists. If so, it will alert relevant traffic managers and then continue autonomous monitoring, looking for additional TMI reduction opportunities during the operational day.In Phase II, we will transition from emulated to live real-time operation, with input from the FAA ATC System Command Center, using ensemble forecasts, expanded TMI reduction search, and data mining techniques. We will also leverage this technology into other domains, e.g., UAM and UTM.

The goal of phase II is to continue the R&D efforts initiated in Phase I. Funding is based on the results achieved in Phase I and the scientific and technical merit and commercial potential of the project proposed in Phase II.

A3

205159

SBIR_20_P2

Mark Klopfenstein