Hybrid Human-in-The-Loop Simulations for Evaluating Detect and Avoid System

초록

Detect And Avoid (DAA) is one of the most important functionalities for the operation of large Unmanned Aircraft Systems (UAS). Since the UAS pilot must maneuver the aircraft by interacting with the DAA system and Air Traffic Control (ATC), studying their interactions is essential for the further development of such systems. However, conducting flight tests requires high-performance UASs and large airspaces. In contrast, flight testing with smaller surrogate UASs is logistically easier but integration with the ATC is difficult because they tend to fly at lower altitudes and are not detected by the standard radar surveillance systems. This study proposes alternative testing methods based on smaller surrogate UAS. First, the DAA system parameters are scaled based on the speeds of the surrogate UASs so that the time scale remains the same. Second, compact standalone Automatic Dependent Surveillance - Broadcast (ADS-B) out transponders are installed on the surrogate UASs so that the surveillance information is received by ADS-B receivers. Two phase flight tests were conducted. The first tests were with a simulated virtual intruder with an ADS-B out equipped drone. The second test involved two drones, each equipped with an ADS-B out transponders The escalation in alert levels and the execution of avoidance maneuvers according to the ATC instructions were successfully executed. Both tests demonstrated that it is possible to conduct DAA flight tests using surrogate UAS that are realistic enough to mimic the larger system, and it can become a cost-effective tool for studying the interactions between UAS pilots, the DAA system, and ATC.

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