A Drone Encounter Model for Detect and Avoid Evaluation in U-space

This paper introduces a Drone Encounter Generation (DEG) model designed to generate conflict trajectories between two or more drone unmanned vehicles. Conflict encounters are a key element in developing Detect and Avoid (DAA) systems, one of the cornerstones that should enable the safe extension of U-space into BVLOS operations. At the moment, no well-defined strategy exists in the literature to generate encounters between drones. Contrarily, in manned aviation, there exists a well-established tradition of generating large encounter sets based on realistic statistical information. DEG intends to fill this gap by enabling the modelling of the desired encounters, capturing the peculiarities of drone operations in U-space, and the different mission profiles that may exist. This work describes the initial efforts in defining the encounter modelling strategy and the algorithms employed to generate the necessary trajectories. For example, a potential DAA protection volume is analyzed as a potential use case demonstrating how the drone operational factor is captured correctly. The final objective of this work is to facilitate openly available encounter sets that could be employed by the research community to perform fair comparisons between DAA system proposals.