Helicopter Air Ambulance (HAA) Trajectories

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.

Encounter Models Overview
For many aviation safety studies, aircraft behavior is represented using encounter models, which are statistical models of how aircraft behave during close encounters. The models are used to provide a realistic representation of the range of encounter flight dynamics where an aircraft collision avoidance system would be likely to alert. These models represent aircraft behavior (rates) during the course of the encounter with other aircraft. Encounter models have been developed for many different manned operational contexts. For more details on encounter models, please refer to overview on the Airspace Encounter Models GitHub organization: https://github.com/Airspace-Encounter-Models/em-overview.

Helicopter Air Ambulance Encounter Model
As noted in the source, the HAA encounter model was trained using flight operational quality assurance (FOQA) data provided through NDAs by a Massachusetts-based HAA operator. This is the first modern encounter model to solely represent helicopter operations and also the first to train using FOQA data.

This generative Bayesian model was trained from an estimated 2,526,000 observations across 758 flight hours. Approximately 50% of the training data had a reported altitude of 1200 feet mean sea level (MSL) or less and about 50% of the FOQA tracks were 19 minutes or less in duration. The training data were obtained in 2014 through a series of nondisclosure agreements between MIT Lincoln Laboratory and Panoptes and between Panoptes with a Boston metropolitan HAA company. Panoptes was a spin-off from Aurora Flight Sciences.

There are nine variables in the HAA encounter model. Similar to all the other encounter models, the airspace is divided in altitude layers. Because of the low operating altitudes and lack of modeled weather (e.g., wind speed is ignored), it is assumed ground speed is equivalent to airspeed. Units are in feet mean sea level (MSL). Similar to the unconventional model, the HAA encounter model does not include an airspace class or a geographical location variable; and similar to the due regard encounter mode, aircraft heading is modeled for the regular structure of HAA operations.

In order to use a discrete Bayesian network, it is necessary to quantize the features by defining a sequence of cut points c₁ … cn. Values less than c₁ 1 are the first bin, values greater than cn are in the (n + 1) bin, and values in the half-open intervals [c_i-1,c_i) are in the ith bin. None of the variables have a uniform quantization, nor are the bins a constant size. The bounds and cut points are listed in Table 1. Figure 1 on the More Information page illustrates the independent frequency distribution of some variables in the model and Figure 2 illustrates the empirical CDF for the same variables.