Unmanned Aircraft Systems: The Mitigation of Human Factors Errors Through Training
Abstract
Eighty percent of aviation accidents have been attributed to human factors errors. Human-centric design and human-in-the-loop studies attempt to allocate human tasks and computer automated tasks to reduce human error. There is a gap in the human error analyses pertaining to the highly automated design of unmanned aircraft systems forecast to be used in civil commercial flight operations. The problem addressed by this research is a lack of understanding of the causal or contributory human factors errors potentially thought to contribute to commercial unmanned aircraft accidents in the future. The purpose of this qualitative, nonexperimental, descriptive case study was to explore the aviation-specific relationship of human factors to technology in the complex human-machine operational environment. A Human Factors Analysis and Classification System-directed study was completed of 4 separate unmanned aircraft systems accidents. The study methods employed a coding schema to compile a list of complicit human factors errors. The list was subjected to a risk analysis and a Pareto prioritization to determine the top 20% of repetitive human errors. These data were verified through application of a Cohen's Kappa and a peer debriefing. By attaining understanding of the issues through this research project, macro training mitigation strategies were proposed to reduce the most prevalent human errors. One outcome of this project will be the inclusion of the findings in Federal Aviation Administration promulgated regulations designed to ensure positive social change by ensuring the safe integration of unmanned aircraft systems into the joint-use national airspace system.
