The Relationship Among HFACS Levels and Analysis of Human Factors in Unmanned and Manned Air Vehicles
type: CreativeWork
description: This dissertation analyzes the structural relationships among the Human Factors Accident Classification System levels for unmanned air vehicle and manned air vehicle accidents and the common relationships between unmanned air vehicle and manned air vehicle accident causes. The study acquired DOD HFACS accident classification data from 347 United States Air Force Class A accident reports for the years between 2000 and 2013. The dissertation utilized a set of analysis that is considered to contribute substantially to the respective domain of the study. The correlations found among categorical levels were applied to HFACS taxonomy based on the Reason Model via path analysis – structural equation modeling. The study concluded the presence of statistically significant paths at both UAV and MAV accidents and common partial paths of those aircraft types within the framework of DOD HFACS taxonomy. The study also suggests that accident data can be utilized to test and improve the failure model of an organization through identification of significant effects such as technology and structural changes in the organization.
abstract: This dissertation analyzes the structural relationships among the Human Factors Accident Classification System levels for unmanned air vehicle and manned air vehicle accidents and the common relationships between unmanned air vehicle and manned air vehicle accident causes. The study acquired DOD HFACS accident classification data from 347 United States Air Force Class A accident reports for the years between 2000 and 2013. The dissertation utilized a set of analysis that is considered to contribute substantially to the respective domain of the study. The correlations found among categorical levels were applied to HFACS taxonomy based on the Reason Model via path analysis – structural equation modeling. The study concluded the presence of statistically significant paths at both UAV and MAV accidents and common partial paths of those aircraft types within the framework of DOD HFACS taxonomy. The study also suggests that accident data can be utilized to test and improve the failure model of an organization through identification of significant effects such as technology and structural changes in the organization.
author: Yesilbas, Veysel
keywords: Accident Investigation, Aviation, HFACS, Human Factors, SEM, UAV, Aerospace Engineering, Military and Veterans Studies, Systems Engineering
date published: 2014-04-01T07:00:00Z
date modified: 2026-07-24T03:34:25Z
provider: Old Dominion University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Old Dominion University