This paper investigates the demand and capacity management in very low level urban airspace, using the notion of Reasonable Time to Act (RTTA) from the European Concept of Operations for U-space (CORUS) and its Urban Air Mobility (UAM) extension (CORUSXUAM). We develop methodology for determining optimal RTTA values which balance early airspace reservation versus the flexibility of last-minute adjustments. Our analysis addresses the trade-offs between early deconfliction (which may lead to inefficient airspace use due to unnecessary reservations), and late deconfliction (which implies reduced predictability for uncrewed aerial systems operators). We incorporate weather uncertainties, using simulations to quantify the impact of varying RTTA lengths on airspace congestion and delay costs.

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. 

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.

The Metropolis II project aimed to study the impact of centralised separation management for urban aerial mobility. Three concepts were developed in this study: a fully centralised, strategically separated concept, a hybrid concept featuring centralised strategic separation and distributed tactical separation, and a fully distributed tactical concept. A comparative simulation study was performed, using traffic scenarios based on predicted demand in an urban airspace in the city of Vienna. Simulations were performed with varying traffic densities and situations. Results show that the purely strategic and purely tactical strategies perform comparably in terms of safety, and that further improvements can be achieved with a combination of those strategies.

This paper explores tradeoffs between ground impact and efficiency of drone flights in urban scenarios. We give an algorithm which produces a set of routes with different lengths and varying number of people affected by the drone. We also present an interactive online visualization tool allowing the user to modify flightpaths in order to explore routing options. Our path finder and the GUI are implemented for a metropolitan area of Norrköping municipality in Sweden. The methods studied in this paper may give UTM service provider the tools to negotiate flightplans which will be acceptable by both the regulator and the drone operator.

Specific Operations Risk Assessment (SORA) is a qualitative methodology for assessing risks of drone operations. In this paper, SORA is compared to and complemented with quantitative estimations of the risk (earlier called HFRM: High-fidelity risk modeling). We highlight intrinsic shortcomings of both SORA and HFRM, and show how HFRM may help to deal with SORA’s ambiguities. (We do not have a recipe to remedy HFRM’s drawbacks with the help of SORA, but suggest a possible regulatory fix to HFRM, addressing its deficiency.) With its focus on ground risk, this paper complements the works of TU Dresden which suggested integrating “agent simulation as air risk assessment in SORA” [Fricke et al., ATM Seminar 2021] and of SESAR’s ER4 BUBBLES project “proposing a quantitative risk analysis which enhances or replaces the qualitative model of SORA” (also for the air risk) [BUBBLES Deliverable 4.1]; we also connect to CORUS observations on SORA shortcomings and use U-space services for addressing them. Our work advocates for stricter regulations, including digitalization and automation not only in definitions, but also in mandates/requirements. Our arguments are illustrated on simple synthetic cases and on real-world experimental examples from urban areas.

We give algorithms for splitting a geographical region into ”approximately flat” rectangular zones. Each zone is assigned a feasible flight altitude, providing simple flight level guidance for future operations of unmanned aerial systems in low-level airspace. We consider a rural scenario with uneven ground level and an urban setting featuring many tall structures. In both cases, our solutions adapt to the underlying terrain or city landscape. In the rural scenario, operating on a fixed altitude within a rectangle allows the drone to stay within the upper limit of 120m while not flying too close to the ground; our objective is to minimize the complexity of the airspace. In the urban case, we aim at minimizing the volume of airspace reserved for drone operations, while allowing overflight over tall buildings in the city. Experiments with real landscape and city skyline data demonstrate output of our solutions with various input parameters.

We consider paths with low exposure to a 2D polygonal domain, i.e., paths which are seen as little as possible; we differentiate between integral exposure (when we care about how long the path sees every point of the domain) and 0/1 exposure (just counting whether a point is seen by the path or not). For the integral exposure, we give a PTAS for finding the minimum-exposure path between two given points in the domain; for the 0/1 version, we prove that in a simple polygon the shortest path has the minimum exposure, while in domains with holes the problem becomes NP-hard. We also highlight connections of the problem to minimum satisfiability and settle hardness of variants of planar min- and max-SAT.

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.

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.