Conflict probability based strategic conflict resolution for UAS traffic management

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dc.contributor.authorTang, Yiwen
dc.contributor.authorXu, Yan
dc.contributor.authorInalhan, Gokhan
dc.date.accessioned2024-01-17T11:51:56Z
dc.date.available2024-01-17T11:51:56Z
dc.date.issued2023-11-10
dc.description.abstractIn this paper, we present a strategic conflict resolution method based on the conflict probability estimation, in the context of Unmanned Aircraft System (UAS) Traffic Management. We first elaborate a classic approach for flight trajectory generation in a designated realistic airspace environment, which is then smoothed by B-spline algorithm to achieve higher realism. The trajectories are extended to 4-dimensional Operational Volumes (OV) following the current UTM development visions. This forms the basis for performing a coarse conflict screening process, as the initial part for conflict detection, primarily based on identifying any OVs overlapping in temporal and spatial. Next, we look into the captured OVs and apply a well-studied conflict probability estimation approach, which contributes to a refined and more accurate conflict detection outcome. To resolve the potential conflicts, we propose two models including First-Come, First-Served (FCFS) and optimisation, both embedded with the probability-based conflict detection. In the FCFS approach, flights are delayed in the order of their submission, while the optimisation model aims at cherry-picking flights to seek the optimal solution. Numerical experiments with various case studies are performed to assess the effects with and without such probability concern, as well as different implementation strategies in real world. Results suggest that, allowing OVs’ overlapping to some extent does not necessarily incur conflict over an acceptable probability, whereas the efficiency of airspace use could be improved.en_UK
dc.description.sponsorshipThis work was partially funded by the SESAR JU under grant agreement No 101017702, as part of the European Union’s Horizon 2020 research and innovation programme: AMU-LED (Air Mobility Urban - Large Experimental Demonstrations).en_UK
dc.identifier.citationTang Y, Xu Y, Inalhan G. (2023) Conflict probability based strategic conflict resolution for UAS traffic management. In 2023 IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC), 1-5- October 2023, Barcelona, Spainen_UK
dc.identifier.eisbn979-8-3503-3357-2
dc.identifier.eissn2155-7209
dc.identifier.isbn979-8-3503-3358-9
dc.identifier.issn2155-7195
dc.identifier.urihttps://doi.org/10.1109/DASC58513.2023.10311236
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/20659
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectStrategic conflict resolutionen_UK
dc.subjectUAS traffic managementen_UK
dc.subjectU-spaceen_UK
dc.subjectconflict probabilityen_UK
dc.subjectoperational volumeen_UK
dc.titleConflict probability based strategic conflict resolution for UAS traffic managementen_UK
dc.typeConference paperen_UK
dcterms.dateAccepted2023-04-22

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