Current forecasts on the future of aeronautics suggest an in- creasing number of unmanned aerial vehicles entering the low- altitude airspace in the next decades (FAA, 2018; Kopardekar et al., 2016). Small vehicles for package delivery as well as larger vehicles for urban air mobility will change the airspace drastically, increasing density of operations both in time, i.e. high number of take-off and landings per unit time, and in space, operating in dense urban environment. This scenario poses challenges to the current approach to air traffic control, and large efforts from academia, industry and regulatory bodies are dedicated to the development of new traffic management strategies that leverage higher computing and simulating capabilities available today. In this paper, we propose a simple look-ahead approach to predict potential minimum separation violations at the strategic level, that is before vehicles start flying, depending on the predefined 4D trajectories and uncertainty affecting the wind acting along those routes. The wind field is extracted from the NOAA North America Mesoscale Forecast System and interpolated using Gaussian process regression, while uncertainty affecting the expected cruise airspeed is propagated through error intervals. The approach allows the prediction of aircraft separation as a function of time, highlighting potential safety violations that would go undetected if uncertainty affecting the expected 4D trajectories is not considered. The paper will also discuss issues related to accuracy and scalability of the approach to multiple vehicle operations.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    Uncertainty Propagation in Pre-Flight Prediction of Unmanned Aerial Vehicle Separation Violation


    Contributors:

    Conference:

    13th Annual Conference of the Prognostics and Health Management Society ; 2021 ; Nashville, TN, US


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English





    Uncertainty Propagation in Pre-Flight Prediction of Unmanned Aerial Vehicle Separation Violations

    Corbetta, Matteo / Jarvis, Katelyn / Banerjee, Portia | IEEE | 2022


    Unmanned Aerial Vehicle, Unmanned Aerial Vehicle Flight Control Device, Unmanned Aerial Vehicle Flight Control Method and Program

    RAABE CHRISTOPHER THOMAS / BERGSTROM NIKLAS | European Patent Office | 2022

    Free access


    Unmanned-aerial-vehicle-based violation identification system

    ZHENG PEIYU / CHEN BO / CHEN BING et al. | European Patent Office | 2020

    Free access