Urban air mobility has gained increased attention in recent years due to the emergence of novel technologies. Several use cases within different industries exist. These services can substitute existing services as well as offering entirely new ones. Previous research has focused on novel technologies and changes needed to be made in order for the technology to be established in the market. However, non-technological aspects are lacking, specifically concerning suitable business models. Thus, the role of business models, and changes related to these, required for a commercialization of urban air mobility services constitutes a research gap and are of interest for further exploration. To understand how actors are changing their business models to commercialize urban air mobility three different case studies were conducted on three projects focusing on use cases connected to urban air mobility. Interviews were used as the primary data gathering method, and in total 13 were conducted. The theoretical STOF framework, which delimits the business model into four domains, was used to identify potential changes. The main results indicate important future actors in a commercialization, the degree of change of these actors and potential challenges for them. Due to the uncertainty of the role business models play in a commercialization of urban air mobility services, this thesis will contribute to bridging this research gap. Concrete changes are identified, as well as specific business model areas in need of more attention. Furthermore, the thesis contributes to the literature concerning challenges related to urban air mobility services, as well as suggesting how they can be handled. Finally, the thesis evaluates and explains how the STOF framework can be extended to new industries. / Urban air mobility har fått ökad uppmärksamhet de senaste åren på grund av uppkomsten av nya teknologier. Flera användningsområden inom olika branscher existerar. Dessa tjänster kan ersätta befintliga tjänster samt erbjuda helt nya. Tidigare forskning har främst fokuserat på nya teknologier och förändringar som behöver göras för att tekniken ska etableras på marknaden. Emellertid saknas aspekter som inte är teknologiska, särskilt lämpliga affärsmodeller. Därmed är inte affärsmodellens roll samt nödvändiga förändringar relaterade till den för en kommersialisering av urban air mobility tillräckligt belysta och är därför intressant för vidare forskning. För att förstå hur aktörer ändrar sina affärsmodeller för att kommersialisera urban air mobility genomfördes tre olika fallstudier på tre projekt som fokuserar på användningsområden kopplade till urban air mobility. Den teoretiska STOF modellen, som avgränsar affärsmodellen i fyra områden, användes för att identifiera potentiella förändringar för de olika projektaktörernas affärsmodeller. De främsta resultaten indikerar vilka de viktiga framtida aktörerna i en kommersialisering är, graden av affärsmodellsförändring för dem, samt potentiella utmaningar. På grund av osäkerheten kring vilken roll affärsmodeller har vid kommersialisering av tjänster relaterade till urban air mobility bidrar denna avhandling till att ytterligare belysa detta forskningsområde. Konkret identifierar avhandlingen nödvändiga affärsmodellsförändringar för de olika aktörerna, samt specifika områden inom affärsmodellen som behöver mer uppmärksamhet. Dessutom bidrar avhandlingen till forskningslitteraturen om utmaningar relaterade till urban air mobility tjänster, samt föreslår hur de kan hanteras. Slutligen utvärderar och förklarar avhandlingen hur STOF modellen kan utökas till fler branscher än internetbaserade tjänster.

The rise of crowdsourcing practices has revolutionized the way in which organizational tasks can be performed. One application of crowdsourcing that has been receiving growing attention over the past decade is using the crowd to collect environmental data that is needed to monitor, manage and predict environmental events. Most projects are still in their initial stages and since these projects often require high levels of citizen participation, there is a need to better understand the motivations for individuals to(dis)engage in these crowdsourcing projects, especially when long-term participation is required. Therefore, the aim of this thesis is to explore the motivations of individuals that participated in a crowdsourcing project for environmental data collection. Building on Self-Determination Theory, Social Exchange Theory and Social Identity theory, a case was studied of an organization that successfully motivated citizens from all over the world to use their drones to collect geographic climate data. In total, ten interviews were conducted with the drone-operators. The findings suggest that participants felt intrinsically motivated to engage because they wanted to do good, cared about climate change and were passionate about flying drones. Additionally, they experienced extrinsic motivations such as the possibility of gaining future job offers, recognition, and experience. Moreover, since participation was deemed relatively easy and straightforward, costs of participation were low and outweighed by the benefits. Finally, feeling part of a wider community made the participants more motivated to engage. Using crowdsourcing to collect environmental data on a wider spatiotemporal scale can help guide policy-making that mitigates or manages the impacts of climate change. Future projects would benefit from more and diversified research that support the design of long-term participation schemes, as the success of the projects depends on the level of citizen engagement.

This is a master thesis by Maria Ader and David Axelsson, students at the Master of Science in Engineering degree program in Design and Product Realization at KTH, within the master program Integrated Product Design. The thesis work will benefit ÅF and the EU project ɪɴᴛᴇʀᴀᴄᴛ. The ɪɴᴛᴇʀᴀᴄᴛ project is part of the EU’s effort to forward climate research, and aims to “coordinate and harmonize research and monitoring efforts that will greatly contribute to our knowledge and understanding of changes occurring in the arctic environment.” One out of 12 subprojects within ɪɴᴛᴇʀᴀᴄᴛ aims to “increase awareness of drone technology and sensors among researchers and research station managers while making industry aware of innovative potential uses requiring drone and sensor development.” A drone is an unmanned aerial system/vehicle (UAS/UAV), i.e. an airborne vehicle without a human pilot aboard. This master thesis examines the need of drones at the ɪɴᴛᴇʀᴀᴄᴛ research stations and how arctic climates affect drone technology and the ergonomics of piloting a drone. The thesis also provides an overview of the current state of the drone market and the laws and regulations that affect the use of drones. A survey was distributed within ɪɴᴛᴇʀᴀᴄᴛ to map the researchers’ need of, and attitudes towards, drones, followed by exhaustive interviews with researchers and other key figures. Field testing at Tarfala Research Station provided complementing data. The primary insight from the study was that the researchers’ need, as well as the tasks and methods that they employ, vary greatly. Another insight was that many researchers want to use drones primarily as a sensor platform to collect data from large areas in a short time span. A situation-based drone recommendation and a concept proposal for a simple water sampling solution were made based on the results of the study / Detta är ett examensarbete utfört av Maria Ader och David Axelsson, studenter på civilingenjörsprogrammet Design och Produktframtagning på KTH, med masterinriktning Teknisk Design. Arbetet är utfört åt ÅF i syfte att bidra till EU-projektet ɪɴᴛᴇʀᴀᴄᴛ. Iɴᴛᴇʀᴀᴄᴛ är EU:s satsning på klimatforskning i Arktis och syftar till att “koordinera och harmonisera forskning och miljöbevakning som bidrar till vår kunskap och förståelse av förändringar som sker i de arktiska miljöerna.” Ett av tolv delprojekt inom ɪɴᴛᴇʀᴀᴄᴛ-projektet syftar till att öka medvetenheten om drönarteknologi och sensorer bland forskare och föreståndare på forskningsstationerna inom ɪɴᴛᴇʀᴀᴄᴛ, samt att göra drönarindustrin medveten om nya potentiella användningsområden. En drönare är ett obemannat luftfartyg, d.v.s. en flygfarkost utan pilot ombord. Drönare benämns ibland som “UAS” och “UAV”. I den här rapporten används främst den engelska termen “drones”. Detta examensarbete undersöker behovet av drönare på de forskningsstationer som är delaktiga i ɪɴᴛᴇʀᴀᴄᴛ och hur det arktiska klimatet påverkar drönartekniken och ergonomin. Arbetet kartlägger även drönarmarknaden och de lagar och regler som påverkar användandet av drönare. En utförlig studie genomfördes, där forskarnas behov av drönare undersöktes. En enkät skickades ut inom ɪɴᴛᴇʀᴀᴄᴛ och utförliga intervjuer genomfördes med forskare och andra nyckelpersoner. Ett studiebesök på Tarfala forskningsstation kompletterade med fältdata. Den främsta insikten från studien var att behov, arbetsuppgifter och metoder varierar mycket mellan de olika forskarna. En annan insikt var att många ville använda drönare som sensorbärare, och på så sätt insamla data från stora områden på kort tid. Resultatet från studien låg till grund för en situationsbaserad drönarrekommendation samt ett konceptförslag för en enkel vattenprovtagningslösning.

The potential of Unmanned Aerial Vehicles (UAVs) for surveillance and military applications is significant — with continued technical advances in the field. The number of incidents where UAVs have intruded into unauthorized areas has increased in recent years and armed drones are commonly used in modern warfare. It is therefore of great interest to investigate methods for UAVs to locate and track intruder drones to prevent and counter surveillance of unauthorized areas and attacks from intruder UAVs. This master’s thesis studied how two autonomous seeker UAVs can be used cooperatively to track and pursue a target UAV. To locate the target UAV, simulated measurements from received Radio Frequency (RF) signals were used by extracting bearing and Received Signal Strength (RSS) data. To track the target and predict its future position, the study employed an Extended Kalman Filter (EKF) on each seeker UAV, which acted together as a Mobile Wireless Sensor Network (MWSN). The thesis explored two formation control methods to keep the seeker UAVs in formation while pursuing the target drone. The formation methods used the predicted position of the target to produce reference positions and/or reference distances for a controller to follow. A Distributed Model Predictive Controller (DMPC) was implemented on the seeker UAVs to pursue the target while maintaining formation and avoiding collisions. The EKF, MPC, and formation methods were first evaluated individually in simulation to assess their performance and for parameter tuning. The respective modules were then combined into the complete system and tuned to achieve improved pursuit and formation in simulation. The results showed that, with the chosen parameters and with a high level of measurement noise, the seeker UAVs were able to pursue the target with a combined average distance error of less than 2 m when the target drone flew in a square pattern with a velocity of 2 m/s. The quality of the pursuit was highly affected by the increase in velocity of the target and the initial positions of the seekers, where a high velocity and a large initial deviation from the reference positions/distances resulted in poorer quality.

<p dir="ltr">This research explored a solution to a high accident rate in remotely operating Unmanned Aerial Vehicles (UAVs) in a complex environment; it presented a new Brain-Computer Interface (BCI) enabled supervisory control system to fuse human and machine intelligence seamlessly. This study was highly motivated by the critical need to enhance the safety and reliability of UAV operations, where accidents often stemmed from human errors during manual controls. Existing BCIs confronted the challenge of trading off a fully remote control by humans and an automated control by computers. This study met such a challenge with the proposed supervisory control system to optimize human-machine collaboration, prioritizing safety, adaptability, and precision in operation.</p><p dir="ltr">The research work included designing, training, and testing BCI and the BCI-enabled control system. It was customized to control a UAV where the user’s motion intents and cognitive states were monitored to implement hybrid human and machine controls. The DJI Tello drone was used as an intelligent machine to illustrate the application of the proposed control system and evaluate its effectiveness through two case studies. The first case study was designed to train a subject and assess the confidence level for BCI in capturing and classifying the subject’s motion intents. The second case study illustrated the application of BCI in controlling the drone to fulfill its missions.</p><p dir="ltr">The proposed supervisory control system was at the forefront of cognitive state monitoring to leverage the power of an ML model. This model was innovative compared to conventional methods in that it could capture complicated patterns within raw EEG data and make decisions to adopt an ensemble learning strategy with the XGBoost. One of the key innovations was capturing the user’s intents and interpreting these into control commands using the EmotivBCI app. Despite the headset's predefined set of detectable features, the system could train the user’s mind to generate control commands for all six degrees of freedom of adapting to the quadcopter by creatively combining and extending mental commands, particularly in the context of the Yaw rotation. This strategic manipulation of commands showcased the system's flexibility in accommodating the intricate control requirements of an automated machine.</p><p dir="ltr">Another innovation of the proposed system was its real-time adaptability. The supervisory control system continuously monitors the user's cognitive state, allowing instantaneous adjustments in response to changing conditions. This innovation ensured that the control system was responsive to the user’s intent and adept at prioritizing safety through the arbitrating mechanism when necessary.</p>

Uninterrupted network connectivity is vital for real-time and mission-critical communication networks. The failure of Base Stations due to unforeseen circumstances such as natural disasters or emergencies can affect the coverage and capacity provided by terrestrial communication networks. The use of Unmanned Aerial Vehicles (UAVs) or drones in cellular networks is an upcoming area of research interest in 5G where the public sector and the communication service providers are fervently discussing it. The drones can be rapidly deployed to bridge the gaps in coverage or capacity of the network due to unforeseen circumstances. This thesis explores drone base stations' use for a simple hexagonal cell deployment scenario where the deployable base stations replace two failed macro base stations to improve the mean network capacity. Simulations show that the introduction of the deployable base stations indeed helps improve mean network capacity in case of one or multiple macro base station fail. The Genetic Algorithm is used to achieve Pareto optimality between downlink and uplink capacity of the simulated network. The simulation results show that introducing deployable nodes in a network can improve the network's capacity while also giving near-optimal transmit power values. / Oavbruten nätverksanslutning är avgörande för realtids- och missionskritiska kommunikationsnätverk. Fel på basstationer på grund av oförutsedda omständigheter som naturkatastrofer eller nödsituationer kan påverka täckningen och kapaciteten som tillhandahålls av markbundna kommunikationsnätverk. Användningen av Unmanned Aerial Vehicles (UAV) eller drönare i cellulära nätverk är ett kommande område av forskningsintresse inom 5G där den offentliga sektorn och leverantörerna av kommunikationstjänster ivrigt diskuterar det. Drönarna kan snabbt sättas in för att överbrygga klyftorna i nätverkets täckning eller kapacitet på grund av oförutsedda omständigheter. Denna avhandling utforskar drönarbasstationers användning för ett enkelt scenarie för hexagonal celldistribution där de utplacerbara basstationerna ersätter två misslyckade makrobasstationer för att förbättra den genomsnittliga nätverkskapaciteten. Simuleringar visar att introduktionen av de utplacerbara basstationerna verkligen hjälper till att förbättra den genomsnittliga nätverkskapaciteten i händelse av att en eller flera makrobasstationer misslyckas. Den genetiska algoritmen används för att uppnå Pareto-optimalitet mellan nedlänks- och upplänkkapaciteten i det simulerade nätverket. Simuleringsresultaten visar att införandet av utplacerbara noder i ett nätverk kan förbättra nätverkets kapacitet samtidigt som det ger nästan optimala värden för sändningseffekt.

The aim of this thesis is to answer the question whether the U.S. policy on targeted killings with combat drones is compatible with the legal doctrine of just war theory, applicable international law, and human rights law. Moreover, this paper intends to examine the legal issues arising from the U.S. practice of international law in relation to the justification of targeted killings. The purpose of this thesis is to determine whether the practice of targeted killings can be considered lawful and, if not, to provide knowledge about how the method violates applicable international law and the ethics of war. The focus is placed on relevant treaties and customary international law, and just war theory is used as a theoretical complement to explain the meaning and purpose of selected laws in order to determine their applicability to the research problem. Furthermore, this procedure has been conducted by using a legal method to identify the legal problem and interpret relevant sources of law in order to determine their applicability to the research problem. The thesis has determined that the U.S. policy on targeted killings with combat drones is not consistent with applicable international law and fundamental human rights law. In particular, the practice of targeted killings violates the principle of distinction.

This thesis aims to analyse the Central Intelligence Agency’s (CIA) potential violation of the right to a fair trial in placing alleged terrorists on the infamous ‘kill list’ without due process. The CIA has operated a targeted killing program using Armed Unmanned Aerial Vehicles (AUAV) over ‘areas outside active hostilities’, such as Yemen, since 2002. Due process is inherent to modern democratic societies and shapes their rule of law. The doctrinal legal analysis makes use of the key principles of due process to analyse the relevant Presidential Policy Guidance, its compliance with International Covenant on Civil and Political Rights (ICCPR) Art. 14, and a case study. These key principles and analyses will result in a clear overview of the program’s violations of the right to a fair trial. Concluding that the CIA’s AUAV program for targeted killing, particularly in Yemen, constitute extrajudicial executions.

L'extraction des paramètres de surface est une activité essentielle des Sciences de la vie et de la Terre. Ce mémoire propose une nouvelle méthodologie pour l'analyse des paramètres biophysiques et géophysiques, appelée Réalité Terrain Étendue, et qui mêle les avantages des relevés terrain et de la télédétection. Nous nous sommes en particulier attachés aux avantages de la télédétection basse altitude et d'un système micro-drone multi-caméras pour la cartographie de la dynamique de la végétation à l'échelle des individus. Cette problématique pose de nombreuses contraintes sur notre système car l'identification des arbrisseaux nécessite des capteurs innovants et une adaptation aux cycles phénologiques pour améliorer leur capacité de discrimination. La télédétection basse altitude semble être une solution intéressante en terme de résolution spatiale et de souplesse opérationnelle, et le développement des micro-drones civils permet des outils d'autant plus performants et fiables pour les missions terrain. Nous avons donc mis en place un système complet de drone avec une charge utile spécifique emportant simultanément trois appareils photographiques pour l'acquisition à la demande d'images obliques, stéréoscopiques ou multispectrales et permettant le développement de nouvelles méthodes d'identification de la végétation. Enfin, en participant à un relevé terrain du Muséum national d'Histoire naturelle, nous avons validé l'intérêt de notre système pour la cartographie de la dynamique de la végétation. Ce travail s'ouvre sur de nombreuses applications et perspectives de recherche, comme l'extraction de paramètres biophysiques par stéréo-restitution et l'agriculture de précision

Thesis (M. of Military Art and Science)--U.S. Army Command and General Staff College, 2007. / The original document contains color images.