Detect and Avoid (DAA) systems are integral to an Unmanned Aircraft System's (UAS) ability to Remain Well Clear (RWC) of other aircraft; they are an enabling technology for UAS to integrate into the National Airspace System (NAS). “Minimum Operational Performance Standards (MOPS) for Detect and Avoid (DAA) Systems” (RTCA DO-365 [1]) specifies requirements criteria for displaying conflict predictive information to the UAS Pilot in Command (PIC). General Atomics Aeronautical Systems, Inc. (GA-ASI), in conjunction with Information Systems Delft, developed an additional conflict predictive display mechanism called conflict probes. Current GA-ASI implementations of DAA have conflict probes displayed whenever a DAA heading band (a band generated on a traffic display to indicate hazardous headings) is displayed. Conflict probes predict the state of an intruder for a given heading, climb rate, and look ahead time. Effectively, rather than displaying the headings and altitudes/climb rates that will result in a DAA Loss of Well Clear (LoWC), they convey to the PIC the volume in space that correlates to a LoWc. This gives the PIC an area on their traffic display to avoid, rather than merely a heading. This allows the PIC more options to avoid a conflict, such as airspeed adjustment in certain geometries. These features may be helpful as a supplement to pre-existing guidance algorithms, or used as a DAA alerting and guidance algorithm on its own. The possibilities for implementation of conflict probes and the results on the effectiveness of DAA alerting and guidance are discussed. Anecdotal feedback from PICs utilizing this augmentation have preferred DAA heading bands with conflict probes. Subjective PIC data have corroborated that conflict probes are useful to the PIC in situations where Air Traffic Control (ATC) is not providing separation services, such as uncontrolled airspace. Further human factors studies are recommended.


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    Title :

    Applications of Conflict Probes for Detect and Avoid Systems


    Contributors:


    Publication date :

    2019-09-01


    Size :

    947063 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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