Assistive DAA refers to the use of DAA technology in onboard-piloted aircraft to augment pilots' see-and-avoid abilities and thus enhance the safety and efficiency of visual flight operations. ADAA is anticipated to be safety-enhancing in airspace where traffic density is high or traditional air traffic services are limited, such as in future Urban Air Mobility (UAM) environments. UAM concepts under development by the FAA, NASA, and industry focus on moving people and cargo in urban and suburban areas using innovative technologies, operations, and aircraft, including electric vertical takeoff and landing (eVTOL) aircraft. Researchers at NASA, in collaboration with FAA researchers, have conducted a series of medium-fidelity, human-in-the-Ioop research simulations of potential future UAM operations. These simulations have included use of a NASA-developed ADAA research tool called DANTi. This paper reports on experience and observations made during testing of the DANTi ADAA capability in a simulation environment for UAM operations.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Assistive Detect and Avoid Technology in Urban Air Mobility Environments


    Contributors:


    Publication date :

    2024-09-29


    Size :

    1647184 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Assistive Detect and Avoid for Pilots in the Cockpit

    Victor A Carreno / Paolo Masci / Maria Consiglio | NTRS


    DANTi: A Tool for Assistive Detect and Avoid Research

    Masci, Paolo / Chamberlain, James / Munoz, Cesar et al. | IEEE | 2024


    Assistive Detect and Avoid for Pilots in the Cockpit

    Víctor A. Carreño / Paolo Masci / María Consiglio | NTRS


    Assistive Detect and Avoid for Pilots in the Cockpit

    Carreno, Victor A. / Masci, Paolo / Consiglio, Maria | IEEE | 2022


    Detect and Avoid Considerations for Safe sUAS Operations in Urban Environments

    Martinez, Victor Celdran / Ince, Bilkan / Selvam, Praveen Kumar et al. | IEEE | 2021