NASA/TM–2015–218928 Real-Time Monitoring and Prediction of Airspace Safety Indranil Roychoudhury SGT, Inc., NASA Ames Research Center, Moffett Field, CA Lilly Spirkovska NASA Ames Research Center, Moffett Field, CA Matthew Daigle NASA Ames Research Center, Moffett Field, CA Edward Balaban NASA Ames Research Center, Moffett Field, CA Shankar Sankararaman SGT, Inc., NASA Ames Research Center, Moffett Field, CA Chetan Kulkarni SGT, Inc., NASA Ames Research Center, Moffett Field, CA Scott Poll NASA Ames Research Center, Moffett Field, CA Kai Goebel NASA Ames Research Center, Moffett Field, CA December 2015 NASA STI Program . in Profile Since its founding, NASA has been dedicated to • CONFERENCE PUBLICATION. the advancement of aeronautics and space Collected papers from scientific and technical science. 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NASA/TM–2015–218928 Real-Time Monitoring and Prediction of Airspace Safety Indranil Roychoudhury SGT, Inc., NASA Ames Research Center, Moffett Field, CA Lilly Spirkovska NASA Ames Research Center, Moffett Field, CA Matthew Daigle NASA Ames Research Center, Moffett Field, CA Edward Balaban NASA Ames Research Center, Moffett Field, CA Shankar Sankararaman SGT, Inc., NASA Ames Research Center, Moffett Field, CA Chetan Kulkarni SGT, Inc., NASA Ames Research Center, Moffett Field, CA Scott Poll NASA Ames Research Center, Moffett Field, CA Kai Goebel NASA Ames Research Center, Moffett Field, CA National Aeronautics and Space Administration Ames Research Center Moffett Field, California 94035 December 2015 Acknowledgments This work was supported by the SMART-NAS project under the Airspace Operations and Safety (AOSP) program within the NASA Aeronautics Research Mission Directorate (ARMD). The use of trademarks or names of manufacturers in this report is for accurate reporting and does not constitute an offical endorsement, either expressed or implied, of such products or manufacturers by the National Aeronautics and Space Administration. Available from: NASA Center for AeroSpace Information National Technical Information Service 7121 Standard Drive 5285 Port Royal Road Hanover, MD 21076-1320 Springfield, VA 22161 (301) 621-0390 (703) 487-4650 Abstract The U.S. National Airspace System (NAS) has reached an extremely high level of safety in recent years. However, it will become more difficult to maintain the current level of safety with the forecasted increase in operations. Consequently, the Federal Aviation Adminis- tration (FAA) has been making revolutionary changes to the NAS to both expand capacity and ensure safety. Our work complements these efforts by developing a novel model-based framework for real-time monitoring and prediction of the safety of the NAS. Our framework is divided into two parts: (offline) safety analysis and modeling, and real-time (online) mon- itoring and prediction of safety. The goal of the safety analysis task is to identify hazards to flight (distilled from several national databases) and to codify these hazards within our framework such that we can monitor and predict them. From these we define safety metrics that can be monitored and predicted using dynamic models of airspace operations, aircraft, and weather, along with a rigorous, mathematical treatment of uncertainty. We demon- strate our overall approach and highlight the advantages of this approach over the current state-of-the-art through simulated scenarios. 1 Executive Summary The U.S. National Airspace System (NAS) has reached an unprecedented, extremely high level of safety due to the efforts of a plethora of national and international organizations conducting regular risk assessments, establishing standards, enacting rules and regulations, auditing for compliance, providing education, and improving technology for aircraft, avion- ics, and air traffic control. However, NAS operations are forecast to increase, due both to increases in commercial flying and the integration of Unmanned Aerial Systems (UAS) into the NAS. Because the same accident rate will result in an increased number of accidents and incidents – an unacceptable eventuality – the Federal Aviation Administration (FAA) has been making revolutionary changes to the NAS to both expand capacity and ensure safety. Our work complements these efforts. We utilize the improved technologies of the FAA’s Next Generation Air Transportation System (NextGen); however, we do not depend on them. We can use even current NAS technology to potentially improve safety through increased shared situational awareness, leading to more informed flight planning and pre- emptive diversions. NAS safety is the goal of every stakeholder involved in the aviation domain. The state- of-the-practice for assessing the safety of the airspace relies on anticipating hazards prior to flight using an acceptable-minimums checklist such as those advocated by the FAA’s Flight Risk Assessment Tool (FRAT) or the hazard analysis promoted by the FAA’s Safety Management System (SMS). If the risk is acceptable, the pilot then updates the assessment during flight using available information. Unfortunately, very little information is available in flight. This is projected to change with NextGen. Even then, the pilot would need to divide attention away from the flying tasks to retrieve and decipher the data, evaluate it in the context of her flight, and decide whether to alter the current plan. The decision must consider multiple factors simultaneously. For example, if the pilot decides to deviate to avoid weather, she must consider the restrictions due to fuel reserves, required arrival times, and restricted airspaces, among others. Moreover, the lack of information is also prevalent in Air Traffic Control (ATC) facilities. Each ATC controller has a limited set of data available and little time to devote to planning very far ahead. To address the challenges of assessing safety with the current state-of-the-practice, in this report, we present a novel framework for real-time monitoring and prediction of the safety of the NAS. Our framework is general enough to include any hazard that can be modeled quantitatively. Another contribution of our work to improving NAS safety is our approach to handling uncertainty. Rather than ignoring uncertainty (of the weather forecast or expected traffic, for example) or just adding a “fudge factor” to account for uncertainty (separating aircraft by a little extra, for example, to account for uncertainty in when a pilot will slow on final approach to landing), we present a systematic, integrated framework for the rigorous, mathematical treatment of uncertainty. Based on principles of probability and Bayesian analysis, the proposed methodology can compute the entire probability distribu- tion of NAS-related quantities of interest without making significant assumptions regarding their distribution type and/or parameters. Our framework is divided into two parts, an (offline) safety analysis and modeling part, 2 followed by an (online) real-time monitoring and prediction of safety part. The goal of the safety analysis task is to identify hazards to flight – conditions that can contribute to incidents or accidents, and to codify these hazards within