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HIGHLIGHTS ARCHIVE
ATM-X Extensible Traffic Management (xTM) team presents three papers at the 2022 AIAA SciTech Forum
January 11, 2022

The ATM-X Extensible Traffic Management (xTM) team presented three papers at the 2022 AIAA SciTech Forum that was held from January 3-7. The first paper, titled “Overview of NASA’s Extensible Traffic Management (xTM) Research” with Dr. Jaewoo Jung as the first author, described the evolution of NASA's Unmanned Aircraft Systems (UAS) Traffic Management (UTM) to xTM, where the foundational UTM requirements and core properties are generalized to become xTM requirements supporting operations of new entrants beyond small UAS. The paper also described NASA’s approach for developing an xTM system for operations in high altitudes over 60,000 feet, designated as upper Class E airspace in the United States, and the planned research to examine the potential xTM-Air Traffic Control (ATC) interactions across multiple xTM systems, such as UTM, upper Class E traffic Management, ETM, and Advanced/Urban Air Mobility, AAM/UAM. The second paper, titled “Identifying Common Use Cases Across Extensible Traffic Management (xTM) for Interactions with Air Traffic Controllers” with Dr. Paul Lee as the first author, presented a set of use cases that have been identified in UTM, AAM/UAM, and ETM operations that are related to ATC interactions. In the paper, use cases across xTM systems were categorized based on common trigger events, to be used for discovering common procedures and data requirements across xTM systems that could help ease the controller’s cognitive task load and allow them to manage these interactions more safely. The third paper, titled “Intent Modeling and Conflict Probability Calculation for Operations in Upper Class E Airspace” with Dr. Min Xue as the first author, presented a probabilistic operational intent model for vehicles operating in upper Class E airspace. This model leverages and extends past works on probabilistic conflict computation in a hybrid form. Simulation results showed that this hybrid model captures the intent conflict probability with better accuracy, especially for a larger look-ahead horizon compared to the earlier works. The paper presented an example to illustrate the use of this model in strategic planning in ETM. The xTM team plans further publications for xTM-ATC interactions and ETM in the future.


POC: Jaewoo Jung



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