Unmanned Aircraft Terminal Area Encounters D
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 currently 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.
The incorporation of unmanned aircraft terminal operations into the scope of detect and avoid systems necessitates analysis of the safety performance of those systems—principally, an assessment of how well those systems prevent loss of "well clear from" and avoid collision with other aircraft. This type of analysis has typically been conducted by Monte Carlo simulation with synthetic, statistically representative encounters between aircraft drawn from an appropriate encounter model. While existing encounter models include terminal airspace classes, none explicitly represents the structure expected while engaged in terminal operations, e.g., aircraft in a traffic pattern.
An initial model of such operations, scoped specifically for assessment of unmanned aircraft on straight-in approach at a Class D airport encountering a second aircraft either landing or taking off, has been developed using a Bayesian network framework like other MIT Lincoln Laboratory encounter models. In this case, the Bayesian networks have been tailored to address structured terminal operations, i.e., correlations between trajectories and the airfield and each other. FAA terminal radar track data over 3 to 8 months in 2015 at 14 single-runway airports throughout the National AIr Space (NAS) have been used to train the model. The model has been sampled to generate a set of one million terminal area encounters for use in initial terminal area safety analyses. Development of the model continues with plans to address additional ownship operations in an expanded set of terminal areas.