As concepts for incorporating uncrewed aerial vehicles (UAS) into controlled airspace are being developed, the need for automated UAS traffic management (UTM) systems to guide UAS and maintain safety is becoming more apparent. A major point of concern for the implementation of UTM is how such systems could coexist alongside the human-centric air traffic management system that is already in place. The European Union’s U-space concept proposes the use of dynamic segregation of airspace reserved for UAS within the control zone. We conducted a simulation experiment with ten air traffic control officer (ATCO) volunteers to gather insights into the feasibility of tower controllers performing the dynamic segregation task. An interface prototype that supports dynamic geofencing and low-level UAS control was developed for this purpose. We found that our proposed interface design helped ATCOs detect potential conflicts between UAS and crewed aircraft. However, they were not always able to adequately resolve them, which resulted in several loss of separation events. It appears that the limitations of the dynamic segregation concept do not fit well with typical air traffic control strategies used by ATCOs. To substantiate our findings, we propose future research to investigate how to overcome the limitations of dynamic segregation to resolve tactical conflicts by revising ATCO control strategies, reevaluating their role in dynamic segregation, as well as considering the definition of flight rules and separation minima for UAS. @en

Any-angle path planning is an extension of traditional path-planning algorithms that aims to generate smoother and shorter paths in graphs by allowing any-angle moves between vertices, rather than being restricted by edges. Many any-angle path-planning algorithms have been proposed, such as Theta*, Block A* and Anya, but most of them are designed only for static environments, which is not applicable when dynamic obstacles are present. Time-Optimal Any-Angle Safe-Interval Path Planning (TO-AA-SIPP) was developed to fill this gap, which can find an optimal collision-free any-angle path that minimizes the traversal time. However, as indicated by its authors, TO-AA-SIPP may not be efficient enough to be used in multi-agent pathfinding (MAPF). Therefore, this paper presents a new algorithm Zeta*-SIPP to improve TO-AA-SIPP by means of 1) reducing useless search nodes that have no contribution to finding optimal solutions, and 2) introducing Field of View (FoV) instead of Line of Sight (LoS) to speed up visibility checks with static obstacles. Benchmark experiments showed that Zeta*-SIPP reduced the computation time of TO-AA-SIPP by around 70%-90% on average.@en

To facilitate a smooth integration of drones into the current Air Traffic Management (ATM) system, Unmanned Air Traffic Management (UTM) systems, services and protocols are currently under development. Unlike current ATM, UTM will rely on high levels of automation. This is potentially problematic, because 100% safe and reliable automation under all circumstances cannot be guaranteed. UTM therefore warrants human supervision and interaction, especially at small airports near urban areas where drone traffic may cross the arrival and departure routes of manned air traffic. Supervision, however, requires some form of transparency for humans to understand the limitations and the behavior of an automated system (e.g., what is it currently doing, what it is planning to do next, and why?). Previous research underlined the importance of UTM transparency, but also indicated that it remains unclear what type of human operator will eventually supervise the UTM system. The background, training and expertise of a human operator may impact the transparency needs and what information needs to be communicated and when. In this paper, the results of a questionnaire-based user study are presented in which information needs were collected from twelve operational Air Traffic Controllers and twelve drone operators and engineers. Results indicate that transparency is deemed imperative for UTM and that information elements categorized as ‘operational transparency’ are typically preferable over ‘engineering transparency’ elements, regardless of operator group. Surprisingly, we found no significant difference in transparency needs between controllers and drone operators, suggesting that a ‘one-size-fits-all’ transparency solution for UTM would be possible.@en