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.
The automatic identification of unstable approaches from flight data by Coumou, Hunink and de Boer. Unstable approaches have been identified as a major risk factor in approach and landing accidents and runway excursions, but hardly ever lead to go-arounds despite strong safety initiatives.
Sickness absenteeism among flight crews is a pervasive problem disruptive to operations and costly for the employer. According to literature, exposure to certain schedule attributes has been associated with adverse health issues. However, the relationship between schedule characteristics and sickness absenteeism remains unclear. Therefore, the aim of this study is to identify schedule characteristics increasing the odds of sickness absenteeism based on historical data. Here, data records for each flight crew member were obtained from a Dutch low-cost airline in the period between 1 January 2018 and 24 January 2020. Schedule characteristics with an adverse effect on both the circadian and/or social rhythm, as identified in literature, were extracted from the available data, and included in the model. Exploration on these potential harmful schedule attributes was done using two generalised additive models. After adjusting for the socio-demographic and work-related confounding variables, simulations revealed that employees exposed to night shifts, backward, and forward rotations over a thirty-day period were significantly more likely to report sick. Furthermore, employees who flew four sectors showed higher odds to call in sick compared to employees who flew two sectors. Based on the results, it is recommended to schedule either sufficient rest periods after exposure or limit the occurrence of the identified schedule attributes.
Flying insects like dragonflies, flies, bumblebees are able to couple hovering ability with the ability for a quick transition to forward flight. Therefore, they inspire us to investigate the application of swarms of flapping-wing mini-drones in horticulture. The production and trading of agricultural/horticultural goods account for the 9% of the Dutch gross domestic product. A significant part of the horticultural products are grown in greenhouses whose extension is becoming larger year by year. Swarms of bio-inspired mini-drones can be used in applications such as monitoring and control: the analysis of the data collected enables the greenhouse growers to achieve the optimal conditions for the plants health and thus a high productivity. Moreover, the bio-inspired mini-drones can detect eventual pest onset at plant level that leads to a strong reduction of chemicals utilization and an improvement of the food quality. The realization of these mini-drones is a multidisciplinary challenge as it requires a cross-domain collaboration between biologists, entomologists and engineers with expertise in robotics, mechanics, aerodynamics, electronics, etc. Moreover a co-creation based collaboration will be established with all the stakeholders involved. With this approach we can integrate technical and social-economic aspects and facilitate the adoption of this new technology that will make the Dutch horticulture industry more resilient and sustainable.
Agricultural/horticultural products account for 9% of Dutch gross domestic product. Yearly expansion of production involves major challenges concerning labour costs and plant health control. For growers, one of the most urgent problems is pest detection, as pests cause up to 10% harvest loss, while the use of chemicals is increasingly prohibited. For consumers, food safety is increasingly important. A potential solution for both challenges is frequent and automated pest monitoring. Although technological developments such as propeller-based drones and robotic arms are in full swing, these are not suitable for vertical horticulture (e.g. tomatoes, cucumbers). A better solution for less labour intensive pest detection in vertical crop horticulture, is a bio-inspired FW-MAV: Flapping Wings Micro Aerial Vehicle. Within this project we will develop tiny FW-MAVs inspired by insect agility, with high manoeuvrability for close plant inspection, even through leaves without damage. This project focusses on technical design, testing and prototyping of FW-MAV and on autonomous flight through vertically growing crops in greenhouses. The three biggest technical challenges for FW-MAV development are: 1) size, lower flight speed and hovering; 2) Flight time; and 3) Energy efficiency. The greenhouse environment and pest detection functionality pose additional challenges such as autonomous flight, high manoeuvrability, vertical take-off/landing, payload of sensors and other equipment. All of this is a multidisciplinary challenge requiring cross-domain collaboration between several partners, such as growers, biologists, entomologists and engineers with expertise in robotics, mechanics, aerodynamics, electronics, etc. In this project a co-creation based collaboration is established with all stakeholders involved, integrating technical and biological aspects.
The CARTS (Collaborative Aerial Robotic Team for Safety and Security) project aims to improve autonomous firefighting operations through an collaborative drone system. The system combines a sensing drone optimized for patrolling and fire detection with an action drone equipped for fire suppression. While current urban safety operations rely on manually operated drones that face significant limitations in speed, accessibility, and coordination, CARTS addresses these challenges by creating a system that enhances operational efficiency through minimal human intervention, while building on previous research with the IFFS drone project. This feasibility study focuses on developing effective coordination between the sensing and action drones, implementing fire detection and localization algorithms, and establishing parameters for autonomous flight planning. Through this innovative collaborative drone approach, we aim to significantly improve both fire detection and suppression capabilities. A critical aspect of the project involves ensuring reliable and safe operation under various environmental conditions. This feasibility study aims to explore the potential of a sensing drone with detection capabilities while investigating coordination mechanisms between the sensing and action drones. We will examine autonomous flight planning approaches and test initial prototypes in controlled environments to assess technical feasibility and safety considerations. If successful, this exploratory work will provide valuable insights for future research into autonomous collaborative drone systems, currently focused on firefighting. This could lead to larger follow-up projects expanding the concept to other safety and security applications.
