Human-Machine Interactions in Very-Low-Level UAS Operations and Traffic Management

Abstract

With the proliferation of Unmanned Aircraft Systems (UAS) in low-altitude airspace and a growing interest in new Urban Air Mobility (UAM) solutions, the Air Traffic Controller (ATCo)'s responsibility to ensure safety and efficiency of operations can no longer be fulfilled with the conventional air traffic control paradigm. Hence, a new increasingly autonomous Decision Support System (DSS) specifically designed for integrated manned/UAS Traffic Management (UTM) is of paramount importance. This DSS makes 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 analysed in depth and reflected in the design of suitable Human-Machine Interfaces and Interactions (HMI <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ). The task analysis presented in this paper assessed the interdependencies between the human and the machine following the Observe-Orient-Decide-Act (OODA) framework. The paper focuses on the management of urban airspace, which is partitioned based on navigation performance. The human-machine workflow is presented and discussed, highlighting the proposed interactions in each subtask. To support closed-loop interactions and enhance system integrity, the UTM DSS makes use of the Cognitive HMI <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> concept, which is also briefly outlined in this paper.