The long-term goal of this A3 Airspace Operations and Safety work is facilitating the development of autonomy in the future National Airspace System (NAS) through the modeling of how human behavior influences the details of flight path selection. The short-term goal is to improve the current NAS by identifying flights deemed ?anomalous? by a suite of indicators designed to assess flight efficiency and safety. The transition path for NASA priorities begins with the Performance Data Analysis and Reporting System (PDARS) flight repository, the source of the forensic data for this project. ATAC has been the primary developer / integrator of PDARS, and Metron is developing joint business opportunities with ATAC to complement their domain and visualization expertise with Metron?s analytics. Part of ATAC?s responsibilities on PDARS is to consolidate, to cleanse, and to otherwise add value to NAS data?the indicators that we propose to develop for this project are designed to aid that mission. During the execution of the Phase II, we will work with ATAC to transition our short-term technology to an FAA NextGen program (e.g., Collaborative Air Traffic Management Technologies (CATMT)), and leverage these in-roads to begin transitioning our deeper human-behavior modeling effort.
For Non-NASA commercial applications, we plan to use the proposed work to extend our technology base of kinematic modeling and anomaly detection (which is focused on the land and sea domains) to include air operations. This will allow us to break into new areas within agencies such as the National Geospatial Intelligence Agency (NGA). NGA is already using our anomaly detection capabilities as part of a suite of tools that we have developed to support Activity Based Intelligence on land and maritime-based track data. In FY16, we will be moving some of these track analytics developed for NGA to a computing cloud environment, and the NASA Phase II development can provide a complementary set of techniques. Similarly for the Navy, much of our technology base for anomaly detection was developed as a kinematic component for Maritime Domain Awareness (MDA), where it is important to understand the behavior of commercial shipping. We would use the extension of this work into the air domain to develop a similar capability for the Air Force, providing capabilities for them to interact more safely and effectively within the context of civilian airspace.