Author_Institution :
Sch. of Autom. Sci. & Electr. Eng., Beijing Univ. of Aeronaut. & Astronaut. Univ., Beijing, China
Abstract :
Notice of Violation of IEEE Publication Principles
"Investigation of Human Factors in UAV Accidents Based on Analysis of Statistical Data,"
by Mansoor M. Nasir and Shi-Yin Qin
in the Proceedings of the First International Conference on Instrumentation, Measurement, Computer, Communication and Control, October 2011, pp. 1011-1015
After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.
This paper copied large portions of text and figures from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.
Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:
"A Summary of Unmanned Aircraft Accident/Incident Data: Human Factors Implications"
by Kevin W. Williams,
in Final Report DOT/FAA/AM-04/24, US Department of Transportation, Federal Aviation Administration
Human errors are held responsible for over 65% of accidents in more than one hundred years of manned aviation history. To evaluate the role of human factors related to accidents of unmanned aerial vehicles (UAVs), a sample data of 56 US Army UAV accidents was used in this study, out of which 32 were related to accidents of Hunter UAV and remaining 24 accidents were of Shadow UAV. The study revealed that human factor was involved in 15 (47%) accidents for Hunter and 5 (21%) for Shadow. Classification of the accident data was a two-step process. In the first step, accidents were classified into the categories of human factors, maintenance, aircraft, and unknown. Accidents could be classified into more than one category. In the second step, those accidents classified as human factors-rela- ed were further categorized according to specific human factors issues such as alerts/alarms, display design, procedural error, skill-based error, or others. For most of the UAV systems, electromechanical failure was more of a causal factor than human error. One significant finding from an analysis of the data is that these two UAV systems are very different, resulting in different kinds of accidents and different human factors issues. A second finding is that many of the occurred accidents could have been anticipated through an analysis of the user interfaces employed and procedures implemented for their use. Finally this paper summarizes the various human factors issues related to the UAV accidents, and some recommendations are given to minimize the failures due to human factors.
Keywords :
air accidents; air safety; aircraft maintenance; alarm systems; autonomous aerial vehicles; data analysis; human factors; statistical analysis; user interfaces; Hunter UAV; Shadow UAV; US Army UAV accidents; aircraft; alarms; alerts; display design; electromechanical failure; human factor investigation; maintenance; procedural error; skill-based error; statistical data analysis; unmanned aerial vehicles; user interfaces; Accidents; Aircraft; Automation; Human factors; Humans; Reliability; Unmanned aerial vehicles; Accident; Human Factors; UAV;
Conference_Titel :
Instrumentation, Measurement, Computer, Communication and Control, 2011 First International Conference on