Sampled trajectories from a Bayesian model trained using anonymized flight operational quality assurance (FOQA) data from a Boston metropolitan helicopter air ambulance company.
Comma Separated Value (CSV)
The dataset contains trajectories sampled from the helicopter air ambulance (HAA) encounter model. Each sampled trajectory is approximately 120 seconds long. These trajectories are only representative of HAA operations; they may not be representative of different types of helicopter operations. The encounters are uncorrelated in the sense that it is assumed that air traffic control services are not being provided during the encounter.
MIT LLTEM V1.0
The MIT LL Terminal Encounter Model (LLTEM) was developed to generate statistically representative encounters between unmanned aircraft and manned aircraft in terminal airspace. The model presently addresses unmanned aircraft on straight-in approach to a Class D airport encountering a second aircraft either landing or taking off. The dataset here includes one million encounters sampled from the model for use in terminal area safety analyses.