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Semantic Scholar · Article (Promet - Traffic&Transportation)

Detection and Prediction of a Pair of Unmanned Aircraft Contact

Published 2022-06-01 From Promet - Traffic&Transportation 3 authors

Attribution

This is the abstract and citation. Full text lives at Semantic Scholar — we link out rather than host. All credit to the authors and Promet - Traffic&Transportation.

Abstract

Verbatim from Semantic Scholar. Not paraphrased, not summarized.

In the current world of increasing density of unmanned aerial vehicle operations in the airspace, there is an enhanced emphasis on their safety due to the potential for mid-air collision, either with another aircraft or with each other. At the same time, unmanned aerial vehicles are also being used in the context of introducing smart technologies into maintenance processes, where there is also a need to prevent a potentially possible conflict when two drones come close together. The paper introduces a mathematical model for tactical prediction of a conflict between a pair of drones. The tactical prediction of drone conflict is intended to alert the drone operator to an immediate potentially dangerous situation. The mathematical simulation in this paper extrapolates the 3D trajectory in the direction of the relative velocity vector of the convergence over the advance time. If the extrapolated trajectory has at least one point in common with the conflict space of the other drone, the conflict is signalled to the drone operator. This model can then be used in practice to simulate flight operations in shared airspace or to develop the currently required rules in selected situations.

Authors

  • A. Novák
  • Alena Novák Sedláčková
  • P. Pecho

Keywords

  • Engineering
  • Computer Science

Citation: A. Novák, Alena Novák Sedláčková, P. Pecho (2022). Detection and Prediction of a Pair of Unmanned Aircraft Contact. Promet - Traffic&Transportation. Semantic Scholar ID 9a1cd5ce0a6270294bd1fc7448f0ebab1abe2fba. https://doi.org/10.7307/ptt.v34i3.4078 ↗