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Current investigations into urban aerial mobility, as well as the continuing growth of global air transportation, have renewed interest in conflict detection and resolution (CD&R) methods. The use of drones for applications such as package delivery, would result in traffic densities that are orders of magnitude higher than those currently observed in manned aviation. Such densities do not only make automated conflict detection and resolution a necessity, but will also force a re-evaluation of aspects such as coordination vs. priority, or state vs. intent. This paper looks into enabling a safe introduction of drones into urban airspace by setting travelling rules in the operating airspace which benefit tactical conflict resolution. First, conflicts resulting from changes of direction are added to conflict resolution with intent trajectory propagation. Second, the likelihood of aircraft with opposing headings meeting in conflict is reduced by separating traffic into different layers per heading–altitude rules. Guidelines are set in place to make sure aircraft respect the heading ranges allowed at every crossed layer. Finally, we use a reinforcement learning agent to implement variable speed limits towards creating a more homogeneous traffic situation between cruising and climbing/descending aircraft. The effects of all of these variables were tested through fast-time simulations on an open source airspace simulation platform. Results showed that we were able to improve the operational safety of several scenarios.
Marta Ribeiro; Joost Ellerbroek; Jacco Hoekstra. Velocity Obstacle Based Conflict Avoidance in Urban Environment with Variable Speed Limit. Aerospace 2021, 8, 93 .
AMA StyleMarta Ribeiro, Joost Ellerbroek, Jacco Hoekstra. Velocity Obstacle Based Conflict Avoidance in Urban Environment with Variable Speed Limit. Aerospace. 2021; 8 (4):93.
Chicago/Turabian StyleMarta Ribeiro; Joost Ellerbroek; Jacco Hoekstra. 2021. "Velocity Obstacle Based Conflict Avoidance in Urban Environment with Variable Speed Limit." Aerospace 8, no. 4: 93.
Current investigations into urban aerial mobility, as well as the continuing growth of global air transportation, have renewed interest in Conflict Detection and Resolution (CD&R) methods. With the new applications of drones, and the implications of a profoundly different urban airspace, new demands are placed on such algorithms, further spurring new research. This paper presents a review of current CR methods for both manned and unmanned aviation. It presents a taxonomy that categorises algorithms in terms of their approach to avoidance planning, surveillance, control, trajectory propagation, predictability assumption, resolution manoeuvre, multi-actor conflict resolution, considered obstacle types, optimization, and method category. More than a hundred CR methods were considered, showing how most work on a tactical, distributed framework. To enable a reliable comparison between methods, this paper argues that an open and ideally common simulation platform, common test scenarios, and common metrics are required. This paper presents an overview of four CR algorithms, each representing a commonly used CR algorithm category. Both manned and unmanned scenarios were tested, through fast-time simulations on an open-source airspace simulation platform.
Marta Ribeiro; Joost Ellerbroek; Jacco Hoekstra. Review of Conflict Resolution Methods for Manned and Unmanned Aviation. Aerospace 2020, 7, 79 .
AMA StyleMarta Ribeiro, Joost Ellerbroek, Jacco Hoekstra. Review of Conflict Resolution Methods for Manned and Unmanned Aviation. Aerospace. 2020; 7 (6):79.
Chicago/Turabian StyleMarta Ribeiro; Joost Ellerbroek; Jacco Hoekstra. 2020. "Review of Conflict Resolution Methods for Manned and Unmanned Aviation." Aerospace 7, no. 6: 79.