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.

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 3-8 months in 2015 at 14 single-runway airports throughout the 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.

Assumptions

The following assumptions and limitations of MIT Lincoln Laboratory Terminal Encounter Model (LLTEM) Version 1.0 should be noted:

  • Ownship is an unmanned aircraft operating under Instrument Flight Rules (IFR) per DO-365A
  • Ownship is on a straight-in approach to a Class D airfield
  • The airfield has a single runway
  • Arbitrary intruder aircraft may be landing or taking off but not merely transiting the area
  • Trajectories are constrained to within 8 NM of the airfield and 3000 ft above airfield elevation
  • Trajectories are a maximum of 240 seconds long

Dataset Content

This dataset consists of trajectories for 1,000,000 encounters sampled from Version 1.0 of the LLTEM. All encounters are between two aircraft, where Aircraft 1 is the unmanned ownship on straight-in approach. Trajectory data is provided in two forms: a single binary file containing position points for all encounters, and full state data (position/velocity/attitude) in individual text files for each aircraft and each encounter. An additional file indicates the sampled encounter conditions as well as CPA information for each encounter.

License

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