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Density-Adapting Layers towards PBN for UTM
Ecole Nationale de l’Aviation Civile (ENAC).
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering. (AEAR)
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

We study separating urban unmanned aerial vehicles (UAV) traffic into altitude levels, using a PBN-inspired approach in which low-density airspace has few layers while congested areas in the city center are split into a larger number of layers. Navigating in the many-layers environment may require better vehicle equipage to support higher performance in terms of altimetry precision; our work thus follows the stakeholders encouragements to use performance-based navigation (PBN) in UAV traffic management (UTM). We present results for several traffic volume scenarios over Norrköping municipality in Sweden, demonstrating applicability of our solutions in a city setting.

Place, publisher, year, edition, pages
2019.
Keywords [en]
Unmanned Traffic Management, UTM, PBN
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:liu:diva-168454OAI: oai:DiVA.org:liu-168454DiVA, id: diva2:1460517
Conference
Thirteenth USA/Europe Air Traffic Management Research and Development Seminar (ATM2019), Vienna, Austria, 17 - 21 June, 2019
Available from: 2020-08-24 Created: 2020-08-24 Last updated: 2023-11-01Bibliographically approved
In thesis
1. Handling demand-capacity imbalances in aerial vehicle traffic
Open this publication in new window or tab >>Handling demand-capacity imbalances in aerial vehicle traffic
2020 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

It is expected that the number of drones used in both commercial and leisure operations will grow significantly in the coming years, which raises the need for a solid framework for management of this traffic. Unmanned traffic management (UTM) is a system for handling autonomous drone flights over urban areas. This thesis addresses the central questions in UTM: how much traffic is sustainable in a city scenario and what are the possible ways of managing the flights. We consider both horizontal-maneuver collision avoidance and vertical deconfliction strategies, including risk management solutions inspired by performance-based navigation (PBN) - a unifying theme for ongoing airspace modernization efforts (we also consider traffic management for the conventional, manned aviation). We use mathematical modeling and conduct numerical simulations to obtain capacity estimations for a geographical area and present algorithms for airspace management. To our knowledge this is the first thesis on UTM, and several directions for future research are also identified.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2020. p. 29
Series
Linköping Studies in Science and Technology. Licentiate Thesis, ISSN 0280-7971 ; 1893
National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:liu:diva-171201 (URN)10.3384/lic.diva-171201 (DOI)9789179297466 (ISBN)
Presentation
2020-11-25, TPM51/TPM53, Täppan, Campus Norrköping, Norrköping, 13:15 (English)
Opponent
Supervisors
Funder
Swedish Transport AdministrationSwedish Research Council
Available from: 2020-11-09 Created: 2020-11-09 Last updated: 2020-11-10Bibliographically approved
2. Development of critical enablers for Unmanned Traffic Management
Open this publication in new window or tab >>Development of critical enablers for Unmanned Traffic Management
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

As the interest in drones continues to grow in both commercial and leisure markets, governments around the world are preparing to face the new challenges arising from unmanned operations. Safe and efficient handling of this novel drone traffic warrants an Unmanned Traf-fic Management (UTM) system capable of dealing with the envisioned high traffic densities. In this dissertation, we identify and address several topics critical for future UTM system development, specifically in the areas of airspace and traffic management. Our work on airspace management includes comparing different airspace designs, developing a risk-management concept inspired by performance-based navigation (PBN), and proposing algorithms for establishing a common altitude reference system. Our contributions to unmanned traffic management include comparing different conflict detection and resolution (CD&R) strategies, developing risk-aware routing algorithms, and proposing an approach for planning mass-scale operations with focus on medical use. We obtained these results primarily through quantitative methods, including mathematical modeling, design and analysis of algorithms, and numerical simulations. With this work, we aim to build a strong foundation for the development of future UTM and discuss directions for future research. 

Abstract [sv]

Då intresset för drönare fortsätter att växa både på kommersiella och fritidsmarknader, förbereder sig regeringar över hela världen för att möta de nya utmaningar som uppstår från obemannade flygningar. Säker och effektiv hantering av denna nya drönartrafik kräver ett system för trafikledning för obemannat flyg (UTM) som kan hantera de förväntade höga trafiktätheterna. I denna avhandling identifierar och behandlar vi flera ämnen som är kritiska för framtida UTM-systemutveckling, specifikt inom områdena luftrums- och trafikhantering. Vårt arbete med luftrumshantering inkluderar jämförelse av olika luftrumsdesigner, utveckling av ett riskhanteringskoncept inspirerat av prestandabaserad navigation (PBN) och förslag på algoritmer för att etablera ett gemensamt höjdreferenssystem. Vårt bidrag till obemannad trafikhantering inkluderar jämförelse av olika strategier för konfliktdetektering och -lösning (CD&R), utveckling av riskmedvetna algoritmer för ruttplanering och förslag på en metod för planering av operationer i stor skala med fokus på medicinsk användning. Vi erhöll dessa resultat främst genom kvantitativa metoder, inklusive matematisk modellering, design och analys av algoritmer och numeriska simuleringar. Med detta arbete strävar vi efter att bygga en stark grund för utveckling av framtida UTM och diskuterar riktningar för framtida forskning.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2023. p. 58
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 2335
National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:liu:diva-198910 (URN)10.3384/9789180752909 (DOI)9789180752893 (ISBN)9789180752909 (ISBN)
Public defence
2023-12-08, K2, Campus Norrköping, Norrköping, 10:15 (English)
Opponent
Supervisors
Note

Funding: This research was funded by Trafikverket through UTMOK and PBN4UTM research projects.

Available from: 2023-11-01 Created: 2023-11-01 Last updated: 2023-11-01Bibliographically approved

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Sedov, LeonidPolishchuk, Valentin

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