AvMet Applications, Inc. — National Aeronautics and Space Administration SBIR Phase I: A3

Description

To facilitate efficient, weather-resilient UAM operations, airspace capacity management rules and airspace rationing algorithms will need to be developed and tested under a variety of inclement weather impacts, urban airspace layouts, and traffic demand scenarios. We are therefore proposing to design and build an efficient, modular, weather-aware UAM System Capacity Manager (USCM): a superfast-time, adaptable UAM system simulator with a path to a real-time Decision Support Tool (DST) capability.USCM will store UAM route network and vertiport data (ldquo;templatesrdquo;) including throughput under various weather conditions, buildings, and UAM vehicle information by vehicle class. It will also use as input the UAM operatorsrsquo; business rules as well as airspace rationing and vertiport landing slot allocation rulesets and, lastly, traffic demand as it evolves during the day. Weather forecast will be ingested and translated into operational impacts on UAM airspace objects (traffic corridors, vertiport approach zones); derived metrics such as ride quality may also be generated. All this information will be loaded into the superfast-time UAM simulation model, the Evaluator. A single UAM system simulation run will then be triggered or, if warranted, multiple runs will be launched in parallel in the cloud, accounting for weather forecast uncertainty range and exercising the respective range of operational outcomes such as UAM network delays and closures. Rule-driven UAM system response options will also be evaluated, for instance ground delay programs or pre-planned traffic reroutes. Results will be available near-instantly.As the standalone off-line simulation model is validated and evolves into a DST, it would contribute to maintaining efficient UAM, help coordinate operational responses between UAM vehicle operators, streamline weather-constrained urban airspace management and facilitate interaction with vertiport demand-vs-capacity management tools ndash; in real time.