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(searched for: doi:10.2514/atcq.23.4.275)
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, Marsel Omeri, Miquel Angel Piera
Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, Volume 233, pp 6076-6088; https://doi.org/10.1177/0954410019875241

Abstract:
This study elaborates the conflict management framework of unmanned aerial vehicles, focusing on the identification of the spatiotemporal interdependencies between them, with consideration of the future scalability problems in highly dense traffic scenarios. The paper first tries to justify the applied separation criteria among small cooperative unmanned aerial vehicles based on their performance characteristics and the planned missions’ type. The adopted criteria, obtained from the simulations of 160 missions, present a testing asset, referring to a current lack of the spatiotemporal requirements and a need for extending the research in this area to provide a more rapid integration of these vehicles into the civil controlled airspace. The paper then elaborates the computational framework for the conflict detection and resolution function and operational metrics for causal identification of the spatiotemporal interdependencies between two or more cooperative vehicles. The vehicles are considered as a conflict mission system that strives to achieve an efficient solution by applying certain maneuvering measures, before a loss of separation occurs. The operational trials of five local, short-range missions, supported by the simulation scenario, demonstrate the potential for a time-based complexity analysis in the conflict resolution processes with less demanding and more efficient coordinated maneuvers. The results show that those maneuvers would not induce any new conflicts and disrupt the cooperative mission system when the spatial capacity only might not be favorable in provision of the avoidance maneuvers within an available airspace.
Erik Theunissen, Fabrice Kunzi, Brandon Suarez
2017 Integrated Communications, Navigation and Surveillance Conference (ICNS) pp 3B3-1-3B3-10; https://doi.org/10.1109/icnsurv.2017.8011914

Abstract:
In the context of the development of the Minimum Operational Performance Standards (MOPS) for UAS Detect and Avoid (DAA) systems by RTCA Special Committee 228 (SC-228), three new traffic-related alerts have been defined: Preventive, Corrective and Warning. To achieve an acceptable balance between missed/late alerts and incorrect alerts and minimize the occurrence of realerts on the same target, mitigations are needed that increase the robustness against measurement and prediction inaccuracies. This paper discusses how the use of time to co-altitude, data filtering, alert filtering, alert hysteresis and sensor specific adaptive thresholds can be applied to increase the robustness of the alerting function.
Erik Theunissen, Brandon Suarez, Fabrice Kunzi
2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC) pp 1-10; https://doi.org/10.1109/dasc.2016.7777985

Abstract:
The purpose of Detect and Avoid (DAA) is to maintain Well Clear between ownship and any potential intruders. One sub-function of a DAA system is the human interface where aural alerts and visual guidance for maintaining Well Clear are displayed to the pilot. However, situations can occur where Well Clear is lost. In such situations, the visual guidance must change from displaying guidance meant to maintain Well Clear to guidance that aids the pilot to recover Well Clear. This paper describes a concept for displaying guidance to maintain and recover Well Clear. A distinguishing feature is that the generated guidance is continuous before and after loss of Well Clear, i.e. no discontinuity occurs in the guidance when crossing the Well Clear boundary. The concept was evaluated using simulations and flight-testing, and some of the results are discussed here.
César A. Muñoz, Aaron Dutle, Anthony Narkawicz, Jason Upchurch
ACM SIGLOG News, Volume 3, pp 67-76; https://doi.org/10.1145/2984450.2984459

Abstract:
As the technological and operational capabilities of unmanned aircraft systems (UAS) have grown, so too have international efforts to integrate UAS into civil airspace. However, one of the major concerns that must be addressed in realizing this integration is that of safety. For example, UAS lack an on-board pilot to comply with the legal requirement that pilots see and avoid other aircraft. This requirement has motivated the development of a detect and avoid (DAA) capability for UAS that provides situational awareness and maneuver guidance to UAS operators to aid them in avoiding and remaining well clear of other aircraft in the airspace. The NASA Langley Research Center Formal Methods group has played a fundamental role in the development of this capability. This article gives a selected survey of the formal methods work conducted in support of the development of a DAA concept for UAS. This work includes specification of low-level and high-level functional requirements, formal verification of algorithms, and rigorous validation of software implementations.
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