Interpretable Human-Machine Interactions for UAS Traffic Management

Nichakorn Pongsakornsathien, Alessandro Gardi, Roberto Sabatini, Trevor Kistan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

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.

Original languageBritish English
Title of host publicationAIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021
DOIs
StatePublished - 2021
EventAIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021 - Virtual, Online
Duration: 2 Aug 20216 Aug 2021

Publication series

NameAIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021

Conference

ConferenceAIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021
CityVirtual, Online
Period2/08/216/08/21

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