The Distributed Operator Model Architecture (D-OMAR) was used as the software environment in which to build an Unmanned Aerial Vehicle (UAV) test bed. Using D-OMAR, models were developed for UAVs each with a sensor package that included daytime-TV and infrared cameras. Human performance models were developed for the Aerial Vehicle Operator (AVO) and the Sensor Operator (SO) The modeled workplace from which the AVO and SO managed a mission included positions for the AVO's control of the vehicle the SO's use of the sensor package. With the basic elements of the test bed defined, a use case was developed based on a scenario (Petkosek, Warfield, and Carre;Lta, 2005) at a commercial airport. The AVO model maintained the UAV flight path and the SO, reading from a list of Essential Elements of Information (EEI), conducted and interpreted the sensor observations of the modeled airport scene coordinating them with a Multi-Function Operator (MFO), the third member of the UAV mission team. The operations of the AVO and MFO are described and additional detail is provided on the SO model that describes multitasking, the modeling of individual difference, the modeling of episodic and declarative memory, and model robustness. The report concludes with suggestions that the UAV test bed might be employed to examine workplace design and operating procedures with the goal of improving UAV mission performance, and reducing staffing and required training time.
UAV Operator Human Performance Models
2006
28 pages
Report
Keine Angabe
Englisch
Aircraft , Human Factors Engineering , Stress Physiology , Psychology , Psychiatry , Performance(Human) , Missions , Drones , Situational awareness , Workload , Scenarios , Military personnel , Learning , Test beds , Reduction , Models , Training , Mfo(Multi-function operator) , Avo(Aerial vehicle operator) , So(Sensor operator) , Observation and interpretation , Recollection of events
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