Author:
Alharasees Omar,Al-Rabeei Samer,Kale Utku
Abstract
Drone systems have become increasingly applied to various commercial, technical, agricultural, and military sectors. With the emerging significant effects on the frequency of drone accidents in many situations and areas, it has become increasingly necessary to form unmanned aircraft systems and usage limitations. The first step to do that is by highlighting the sources of accidents in the current process. The Human Factors Analysis and Classification System (HFACS) is the main technique for accident risk assessments in drone systems which clusters the accident key factors causes into 4 basic domains. In this study, 4 categories of drone experts participated in the study. The research utilized a new approach that integrates an analytical hierarchical decision-making model with the HFACS for drone accident causation investigation. The results of the study showed discrepancies among the different groups of drone operators and identified organizational factors and unsafe actions as being key issues in the evaluation.
Publisher
Technical University of Kosice - Faculty of Aeronautics
Cited by
2 articles.
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1. Evaluating AI-UAV Systems: A Combined Approach with Operator Group Comparison;2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA);2023-06-08
2. Human Factors in the Age of Autonomous UAVs: Impact of Artificial Intelligence on Operator Performance and Safety;2023 International Conference on Unmanned Aircraft Systems (ICUAS);2023-06-06