The continuous increase of accident and incident reports has indicated the potential of drones to threaten public safety. The published regulatory framework for small drones is not visibly based on a comprehensive hazard analysis. Also, a variety in the constraints imposed by different regulatory frameworks across the globe might impede market growth and render small-drone operations even more complicated since light drones might be easily transferred and operated in various regions with diverse restrictions. In our study we applied the Systems-Theoretic Process Analysis (STPA) method to small-drone operations and we generated a first set of Safety Requirements (SR) for the authority, manufacturer, end-user and automation levels. Under the scope of this paper, we reviewed 56 drone regulations published by different authorities, and performed (1) a gap analysis against the 57 SRs derived by STPA for the authority level, and (2) Intra-Class Correlations in order to examine the extent of their harmonization. The results suggest that the regulations studied satisfy 5.3% to 66.7% of the SRs, and they are moderately similar. The harmonization is even lower when considering the range of values of various SRs addressed by the authorities. The findings from the drones’ case show that regulators might not similarly and completely address hazards introduced by new technology; such a condition might affect safety and impede the distribution and use of products in the international market. A timely and harmonized standardization based on a systematic hazard analysis seems crucial for tackling the challenges stemmed from technological advancements, especially the ones available to the public.
This paper presents how the application of the STPA method might support the evaluation of fighter pilots training programs and trigger procedural and technological changes. We applied the STPA method by considering the safety constraints documented in the Standard Operating Procedures (SOPs) of a South European Air Force and regard a flight of a two F-16 aircraft formation. In this context, we derived the control actions and feedback mechanisms that are available to the leader pilot during an Aircraft Combat Maneuver (ACM) mission, and we developed the control flow diagram based on the aircraft manuals. We compared the results of each analysis step with the respective flight training program, which is based on a mixed skill and rule-based decision-making, and we examined the role of the feedback mechanisms during multiple safety constraints violations. The analysis showed that: the flight training program under study does not structurally include cases of infringement of multiple safety constraints; the maintenance of some safety constraints are not supported by alerts, or rely on only one human sense; the existing procedures do not refer to the prioritization of pilot actions in cases of violation of multiple safety constraints; operation manuals do not address the cases of possible human performance deterioration when simultaneous information from feedback mechanisms is received. The results demonstrated the benefits of the STPA method, the application of which uncovered various inadequacies in the flight training program studied, some of them related to the F-16 cockpit ergonomics. The analysis lead to recommendations in regard to the amendment of the corresponding fighter pilots training program, and the conduction of further research regarding the aircraft – pilot interaction when multiple safety constraints are violated. The approach presented in this paper can be also followed for the (re)evaluation of flight training schemes in military, civil and general aviation, as well by any human-machine interface intensive domain.
Airport management is frequently faced with a problem of assigning flights to available stands and parking positions in the most economical way that would comply with airline policies and suffer minimum changes due to any operational disruptions. This work presents a novel approach to the most common airport problem – efficient stand assignment. The described algorithm combines benefits of data-mining and metaheuristic approaches and generates qualitative solutions, aware of delay trends and airport performance perturbations. The presented work provides promising solutions from the starting moments of computation, in addition, it delivers to the airport stakeholders delay-aware stand assignment, and facilitates the estimation of risk and consequences of any operational disruptions on the slot adherence.
MULTIFILE
The utilization of drones in various industries, such as agriculture, infrastructure inspection, and surveillance, has significantly increased in recent years. However, navigating low-altitude environments poses a challenge due to potential collisions with “unseen” obstacles like power lines and poles, leading to safety concerns and equipment damage. Traditional obstacle avoidance systems often struggle with detecting thin and transparent obstacles, making them ill-suited for scenarios involving power lines, which are essential yet difficult to perceive visually. Together with partners that are active in logistics and safety and security domains, this project proposal aims at conducting feasibility study on advanced obstacle detection and avoidance system for low-flying drones. To that end, the main research question is, “How can AI-enabled, robust and module invisible obstacle avoidance technology can be developed for low-flying drones? During this feasibility study, cutting-edge sensor technologies, such as LiDAR, radar, camera and advanced machine learning algorithms will be investigated to what extent they can be used be to accurately detect “Not easily seen” obstacles in real-time. The successful conclusion of this project will lead to a bigger project that aims to contribute to the advancement of drone safety and operational capabilities in low-altitude environments, opening new possibilities for applications in industries where low-flying drones and obstacle avoidance are critical.
Het haalbaarheidsonderzoek HESCO (High-End-Solar-Composites) beoogd succesvolle integratie van zonnecellen in hoogwaardige composieten. Reguliere zonnepanelen zijn door gewicht slecht inzetbaar voor mobiele oplossingen. Dunne flexibele zonnepanelen zijn kwetsbaar en hebben een lage efficiency. HESCO heeft als doel een zonnepaneel te ontwikkelen voor toepassingen waar vorm, gewicht, energieopbrengst en levensduur belangrijk zijn. Integratie van zonnecellen in lichtgewicht composieten maakt het mogelijk om deze zonnepanelen te maken. Het Lectoraat Kunststoftechnologie van Windesheim en bedrijf Mito Solar bundelen kennis op gebied van composieten en zonne-energie voor deze nieuwe toepassing. HESCO wordt onderzocht door een zonne-energie vleugel te ontwikkelen voor de HALE-UAV drones (High-Altitude-Long-Endurance-Unmanned-AerialVehicle).
In the past decade, particularly smaller drones have started to claim their share of the sky due to their potential applications in the civil sector as flying-eyes, noses, and very recently as flying hands. Network partners from various application domains: safety, Agro, Energy & logistic are curious about the next leap in this field, namely, collaborative Sky-workers. Their main practical question is essentially: “Can multiple small drones transport a large object over a high altitude together in outdoor applications?” The industrial partners, together with Saxion and RUG, will conduct feasibility study to investigate if it is possible to develop these collaborative Sky-workers and to identify which possibilities this new technology will offer. Design science research methodology, which focuses on solution-oriented applied research involving multiple iterations with rigorous evaluations, will be used to research the feasibility of the main technological building blocks. They are: • Accurate localization based on onboard sensors. • Safe and optimal interaction controller for collaborative aerial transport Within this project, the first proof-of-concepts will be developed. The results of this project will be used to expand the existing network and formulate a bigger project to address additional critical aspects in order to develop a complete framework for collaborative drones.
