Efficiency and Fairness in Unmanned Air Traffic Flow Management

As the demand for Unmanned Aircraft Systems (UAS) operations increases, UAS Traffic Flow Management (UTFM) initiatives are needed to mitigate congestion, and ensure safety efficiency. Congestion mitigation can be achieved by assigning airborne delays (through speed changes or path stretches) ground (holds relative desired takeoff times) aircraft. While assignment of such may increase system efficiency, individual aircraft operators unfairly impacted. Dynamic traffic demand, variability in operator preferences, differences market share complicate issue fairness UTFM. Our work considers delay context To this end, we formulate UTFM problem with show through computational experiments that significant improvements attained at little cost We demonstrate when not aligned how they perceive value fairness, there is a decrease overall solution. find decreases as air-ground ratio increases it improves dominant has weak preference its allocated delays. Finally, implemented rolling-horizon setting dynamic efficiency adversely However, impact on varied depends metric used.