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Limitations of Conflict Prevention and Resolution inConstrained Very Low-Level Urban Airspace

Paper ID

SIDs-2021-53

Conference

SESAR Innovation Days

Year

2021

Theme

UAM

Project Name

SESAR 2020 ER4 project Metropolis 2

Keywords:

BlueSky ATC Simulator, conflict Detection and Resolution (CD&R), U-space, Unmanned Traffic Management (UTM), Urban Airspace, Velocity Obstacle (VO)

Authors

Calin Andrei Badea, Andres Morfin Veytia, Marta Ribeiro, Malik Doole, Joost Ellerbroek and Jacco Hoekstra

DOI

Project Number

892928

Abstract

Road traffic delay and urban overcrowding are increasing rapidly all over the world. As a result, several companies have proposed the use of small unmanned aerial vehicles (sUAVs) as an alternative to road-based transportation. These small autonomous drones are expected to operate within a thin airspace band (Very Low Level) in high traffic densities in constrained urban environments. This presents a challenge for ensuring the safe separation and efficient routing of drone fights. Current research has made modest progress towards finding solutions for conflict detection and prevention in highly dense and constrained environments (e.g., in-between buildings). In this paper, the state of the art of urban airspace design and conflict prevention and resolution research are discussed, and their applications to constrained environments. Additionally, fast-time high-fidelity simulations of high-density traffic scenarios are used along a non-orthogonal city layout to identify bottlenecks in the performance of speed-based conflict resolution in a multilayered airspace structure. Results show that the current airspace structure and conflict detection and resolution concepts need to be refined to further reduce conflicts and intrusions that occur in constrained environments. First, additional measures must be adapted to further prevent conflicts during turning and merging. Second, conflict resolution manoeuvres must account for speed limits resulting in turn radii which do not cross physical boundaries. Finally, conflict detection needs to consider the topology of the streets to prevent false-positive conflicts and to prepare in advance for conflicts resulting from heading changes in non-linear streets.