Modeling Low Level Flight Patterns of Manned Aircraft from Actual Flight Tracking Data

With the increasing number of unmanned aircraft flying beyond visual line-of-sight missions, it becomes more and more important to consider and the safety and efficient use of airspace shared between unmanned and manned aircraft. To enable fast-time simulations for the evaluation of safety and efficiency in several future scenarios, representative models of manned aircraft operations at low altitude are needed. In this paper we introduce the main missions flown at low altitudes by manned aircraft and show how we modeled media helicopter operations from big data. We describe the algorithm we developed to automatically extract the model parameters from actual flight tracking data in detail and present the resulting stochastic distributions of the model parameters. We also clarify the assumptions and limitations of our current analysis and show directions for further development.