Rule-based conflict management for unmanned traffic management scenarios

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dc.contributor.authorAlharbi, Abdulrahman
dc.contributor.authorPoujade, Arturo
dc.contributor.authorMalandrakis, Konstantinos
dc.contributor.authorPetrunin, Ivan
dc.contributor.authorPanagiotakopoulos, Dimitrios
dc.contributor.authorTsourdos, Antonios
dc.date.accessioned2021-07-09T13:21:33Z
dc.date.available2021-07-09T13:21:33Z
dc.date.issued2020-11-18
dc.description.abstractThe growing use of Unmanned Aerial Vehicles (UAVs) operations will require effective conflict management to keep the shared airspace safe and avoid conflicts among airspace users. Conflicts pose high risk and hazard to human lives and assets as they ma may result in financial and human loss. The proposed rule-based conflict management model consists of three main stages. The first stage includes strategic deconfliction during the flight plan generation. The second stage, pre-tactical deconfliction, applies a ground delay to the agent to resolve the conflict. The third stage corresponds to the tactical deconfliction, where the drone hovers or loiter in the last waypoint before the conflict area until the conflict time window passes. The proposed method differs from most existing conflict management approaches in that it applies deconfliction methods sequentially using a rule-based strategy. Furthermore, a high number of published studies do not consider realistic airspace constraints and potential airspace modernization concepts such as dynamic flight restrictions Assessment and validation are performed in three simulation scenarios that consider different patterns of the airspace availability in the areas where flights may be restricted, such as airfields, recreational areas, and prisons. The Particle Swarm Optimization (PSO) algorithm was used for drone path planning. For the simulated scenarios all of the conflicts were resolved after implementation of the proposed method. The implemented method is simple, flexible and suitable for the management of more complex and dense airspaces.en_UK
dc.identifier.citationAlharbi A, Poujade A, Malandrakis K, Petrunin I, Panagiotakopoulos D & Tsourdos A (2020) Rule-based conflict management for unmanned traffic management scenarios. In: 2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC), 11-15 October 2020, San Antonio, USAen_UK
dc.identifier.isbn978-1-7281-8088-5
dc.identifier.issn2155-7209
dc.identifier.urihttps://doi.org/10.1109/DASC50938.2020.9256690
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/16864
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectUAVen_UK
dc.subjectNo-fly zonesen_UK
dc.subjectConflict Detection and Resolutionen_UK
dc.subjectSimulationsen_UK
dc.subjectTime-baseden_UK
dc.titleRule-based conflict management for unmanned traffic management scenariosen_UK
dc.typeConference paperen_UK

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