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Motivation

With projected increases in national air traffic, advanced tools will be needed to maintain the current level of safety of the National Airspace System (NAS) and to aid in decision-making by the various NAS stakeholders, such as pilots, airline dispatchers, controllers, NAS command center managers, unmanned aircraft systems (UAS) operators, etc. Awareness of both the current and future state of safety of the NAS is critical in making prudent decisions regarding avoidance of potential airspace hazards. Typically, each operator must consolidate operations-relevant information from disparate sources -- which are often imprecise, inconsistent, and incomplete -- and apply extensive domain knowledge to correctly interpret the current state of the NAS and forecast its (combined) evolution over the duration of the NAS operation(s). This time- and workload-intensive primarily manual process is periodically repeated throughout the operation so that changes can be managed in a timely manner.

To facilitate informed decision making on the part of NAS stakeholders, we are developing a model-based methodology for the automated real-time monitoring and prediction of safety of the NAS. This methodology should be able to, for example, help with the following scenario shown in the figure: If we have two aircraft, A1 and A2, and a region of convective weather moving north, situated as shown below, we want to predict which regions of the NAS will be unsafe for A2 within say the next 20 minutes because of a conflict with aircraft A1 or because of an encounter with convective weather.

motivation

Predicting threats to safety.


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