Automated Airspace Management: Concept, Development, and Testing
For many decades, researchers at NASA Ames Research Center have worked to make the air-transportation system more efficient, predictable, and effective. Since about 2005 one important aspect of this research has been the development of an autonomous system for air-traffic control. This system, known as the Autoresolver, is designed to perform most of the roles that air-traffic controllers perform including ensuring separation between aircraft, creating routes around weather and other avoidance volumes, and sequencing and scheduling aircraft across points in space. The recent, rapid expansion of new aircraft operations and types, including urban air mobility aircraft and small unmanned aerial systems, have only increased the need for highly automated systems to control the predicted traffic demand. This talk will focus on the development of the Autoresolver - from concept to testing. It will also discuss the National Airspace (NAS) Digital Twin simulation platform, created to facilitate rapid testing and improvement of the algorithm and with the hope of proving the automation in a high-fidelity environment. An open question that will be discussed is how to ensure that the system-level emergent behavior of independently developed autonomous algorithms is what is desired.