SBIR/STTR Award attributes
NASArsquo;s Urban Air Mobility (UAM) and Uncrewed Aircraft System (UAS) Traffic Management (UTM) concepts envision increasing autonomy, artificial intelligence, and machine learning to maintain operational efficiency while ensuring safety. Increasing autonomy while maintaining or improving efficiency and safety will require effective teaming between humans and automation in routine and contingency operations. Concepts for highly automated future air transportation, like UAM and UTM, describe procedures for addressing contingencies, implicitly assuming automated services will be able to coordinate well enough to address contingencies, with little or no human input, if procedures are pre-defined. However, if traditional air traffic operations are to be a guide, humans will need to be involved in coordinated contingency planning for UAM/UTM operations.To address the need for coordinated contingency planning in UAM/UTM, we propose a Contingency Planning Toolkit for Advanced Air Mobility (CPT AAMO), whose architecture appropriately distributes work among system organizations and agents (human and automated). Its design is based on a systematic analysis of potential allocations of contingency planning functions. The analysis is not just about allocating functions between humans and automation, but also the allocation of responsibilities across organizations in the system. Metrics include function allocation coherency, operational tempo, and coordination load. The analysis enables us to assess each candidate architecture according to system properties like safety, resilience, equity, integration, and resistance to cyber-attack. Our approach allows NASA to move beyond function allocation to task design, providing a systematic assessment of what will and will not work as a procedure/task. This effort fills a gap in AAM concept development, providing appropriate architectures and function allocations for contingency planning in a highly automated system.
