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Now showing 1 - 5 of 235
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    Autonomous Separation in U-Space: Assessing the Impact of Position Uncertainty
    (SESAR Joint Undertaking, 2024) Rahman, M.F. ; Vlaskin, A.V. ; Ellerbroek, J. ; Hoekstra, J.M.
    With the rapid increase in the use of Unmanned Aerial Systems (UAS) for commercial applications such as medical and parcel delivery, the need for safe airborne separation in airspace has become critical. This paper examines the impact of position uncertainty on autonomous separation methods within U-Space, a European Union initiative for managing drone traffic. The study focuses on evaluating various conflict resolution algorithms—specifically, Modified Voltage Potential (MVP) and Velocity Obstacle (VO) variations—under conditions of navigational uncertainty. Through Monte Carlo simulations using the BlueSky ATM simulator, position uncertainty stemming from Global Navigation Satellite Systems (GNSS) errors is modelled and analysed. The research compares the effectiveness of different conflict resolution strategies in preventing conflicts between UAS, measuring intrusion prevention rates and the closest point of approach during encounters. The results indicate that MVP provides superior performance in handling positional uncertainty, offering more robust conflict resolution capabilities than VObased methods. These findings are critical for ensuring the safe integration of UAS into increasingly congested airspace environments, guiding future developments in U-Space operations.
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    Remote pilot modelling for evaluation of ACAS Xu
    (SESAR Joint Undertaking, 2023) Stroeve, S.H. ; Villanueva-Cañizares, C.J. ; Dean, G.
    A remote pilot (RP) model is developed for evaluation of unmanned aircraft (UA) manoeuvring in response to remain well clear guidance and resolution advisories by the ACAS Xu detect-and-avoid system. The model describes RP situation awareness, decisions, response modes, delays, strengths and flight control in deterministic and stochastic settings. It is integrated in a simulation environment that describes sets of aircraft and their sensing systems. Simulation results illustrate the impact and complexity of UA manoeuvring by RPs for ACAS Xu advices.
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    Close proximity and collision risk assessment of drones and urban air mobility
    (EUROCONTROL, 2021) Stroeve, S.H. ; Bakker, G.J. ; Villanueva Canizares, C.J. ; Fota, N.O.
    For quantitative assessment of close proximity and collision risks of drones and urban air mobility there is a need for simulation approaches that can represent a variety of operations and types of uncertainty and hazards that can affect them. This paper shows that agent-based modelling in combination with Interacting Particle System (IPS) Monte Carlo (MC) simulation and risk decomposition for global failure conditions can be effectively used for assessment of small probabilities of close proximity and collision events. It is demonstrated for a use case with drone and air taxi traffic simulations in an urban area south of Paris.