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View Video Presentation: https://doi.org/10.2514/6.2021-2337.vid The proliferation of Unmanned Aircraft Systems (UAS) in low-altitude airspace and a growing interest in new Advanced Air Mobility (AAM) solutions, are eliciting the development of new and increasingly autonomous Decision Support Systems (DSS) specifically designed for integrated manned/UAS Traffic Management (UTM). These UTM DSS make use of advanced traffic flow and airspace management concepts, but to ensure effective teaming between the human and the system in challenging situations, the nature of their roles and responsibilities is to be analyzed in depth and reflected in the design of suitable Human-Machine Interfaces and Interactions (HMI2). The paper focuses on the detail UTM operator’s supervisory role in the envisioned semi-autonomous air traffic flow management paradigm. The key HMI2 formats and functions are prototyped for airspace demand-capacity visualization and traffic clustering, supporting more interpretable human-machine interactions. The Cognitive HMI2 framework is also embedded in the proposed prototype to support closed-loop interactions and improve system integrity.
Pongsakornsathien et al. (Wed,) studied this question.