This research reviews the current literature on the impact of Artificial Intelligence (AI) in the operation of autonomous Unmanned Aerial Vehicles (UAVs). This paper examines three key aspects in developing the future of Unmanned Aircraft Systems (UAS) and UAV operations: (i) design, (ii) human factors, and (iii) operation process. The use of widely accepted frameworks such as the "Human Factors Analysis and Classification System (HFACS)" and "Observe– Orient–Decide–Act (OODA)" loops are discussed. The comprehensive review of this research found that as autonomy increases, operator cognitive workload decreases and situation awareness improves, but also found a corresponding decline in operator vigilance and an increase in trust in the AI system. These results provide valuable insights and opportunities for improving the safety and efficiency of autonomous UAVs in the future and suggest the need to include human factors in the development process.
In safety science and practice, there have been various safety models, each of them reflecting a particular approach to safety management and accident causality. The large variety of models suggested in literature and applied in practice serve the communication of diverse perspectives towards safety and the need to consider contextual factors, but it does not allow the establishment of a common language within and across organisations and industry sectors. Considering the potential benefits of talking a lingua franca when it comes to safety and inspired by the Standard Model used in particle physics and recent suggestions from relevant studies, we thought of exploring the possibility to introduce a Standard Safety Model (STASAM). As a first step, we focused on four representative safety and accident models widely used, discussed and debated: the Swiss Cheese Model, AcciMap, Functional Resonance Analysis Method (FRAM) and Systems-Theoretic Accident Model and Processes (STAMP). We reviewed literature which compares the particular models, and we listed the strengths and weaknesses of each as a means to set the grounds for the STASAM. The combinations of these models with a focus to host their advantages and avoiding their disadvantages led to a three-level STASAM. The concept STASAM was used in two random incident investigation reports to assess its applicability and visualisation against the original models. The results of the application along with the STASAM concept were reviewed by three safety professionals and three safety researchers. The comments received were in the positive direction and indicated the potential of establishing an inclusive and commonly accepted safety/accident model. The next research phase will be the additional review of the STASAM and its pilot application to a variety of safety events and systems as a means to test its reliability and strengthen its validity.
Most safety oriented organizations have established their accidents classification taking into account the magnitude of the combined adverse outcomes on humans, assets and the environment without considering the accidents‟ potential and the actual attempts of the involved persons to intervene with the accident progress. The specific research exploited a large sample of an aviation organization accident records for an11 years‟ time period and employed frequency and chi-square analyses to test a new accident classification scheme based on the distinction among the safety events with or without human intervention on the accident scene, indicating the management or not of their ultimate consequences. Furthermore, the research depicted the effectiveness of personnel strains to alleviate the accident potential outcomes and studied the contribution of time, local and complexity factors on the accident control attempt and the humans‟ positive or negative interference. The specific newly proposed accident classification successfully addressed the “controlled” or “uncontrolled” traits of the safety events studies, prior their severities consideration, and unveiled the effectiveness of personnel efforts to compensate for the adverse accident march. The portion between controlled and uncontrolled accidents in terms of the human intervention along with the effectiveness of the later may comprise a useful safety performance indicator that can be adopted by any industry sector and may be recommended through international and state safety related authorities.
