General Aviation Weather Hazards:Current Human Factors Research, Pilot Practices, and Tools

2020 ◽  
Vol 64 (1) ◽  
pp. 123-126
Author(s):  
Beth Blickensderfer ◽  
Lori J Brown ◽  
Alyssa Greenman ◽  
Jayde King ◽  
Brandon Pitts
Keyword(s):  
Human Factors ◽  
Panel Discussion ◽  
General Aviation ◽  
Transportation Safety ◽  
Laboratory Research ◽  
Related Factors ◽  
Future Directions ◽  
The Past ◽  
Flight Operations ◽  
Human Factors Research

When General Aviation (GA) pilots encounter unexpected weather hazards in-flight, the results are typically deadly. It is unsurprising that the National Transportation Safety Board repeatedly lists weather related factors in GA flight operations as an unsolved aviation safety challenge. Solving this problem requires multidisciplinary perspectives. Fortunately, in the past several years innovative laboratory research and industry products have become available. This panel discussion brings together Human Factors and Ergonomics researchers and practitioners to discuss and describe the current work and future directions to avoid weather related accidents in GA.

Qualitative ergonomics/human factors research in health care: Current state and future directions

2017 ◽  
Vol 62 ◽  
pp. 43-71 ◽  
Author(s):  
Rupa Sheth Valdez ◽  
Kerry Margaret McGuire ◽  
A. Joy Rivera
Keyword(s):  
Health Care ◽  
Human Factors ◽  
Future Directions ◽  
Current State ◽  
Human Factors Research

Machine Learning and Human Factors: Status, Applications, and Future Directions

2018 ◽  
Vol 62 (1) ◽  
pp. 135-138 ◽  
Author(s):  
Nathan Lau ◽  
Lex Fridman ◽  
Brett J. Borghetti ◽  
John D. Lee
Keyword(s):  
Machine Learning ◽  
Human Factors ◽  
Interaction Design ◽  
Intelligent Systems ◽  
Consumer Products ◽  
Learning Approaches ◽  
Future Directions ◽  
Industrial Systems ◽  
Human Factors Research ◽  
And Training

As machine learning approaches ubiquity in industrial systems and consumer products, human factors research must attend to machine learning, specifically on how intelligent systems built on machine learning are different from early generations of automated systems, and what these differences mean for human-system interaction, design, evaluation and training. This panel invites five researchers in different domains to discuss how human factors can contribute to machine learning research and applications, as well as how machine learning presents both challenges and contributions for human factors.

Designing Synthetic Tasks for Human Factors Research: An Application to Uninhabited Air Vehicles

1998 ◽  
Vol 42 (1) ◽  
pp. 123-127 ◽  
Author(s):  
Elizabeth Martin ◽  
Don R. Lyon ◽  
Brian T. Schreiber
Keyword(s):  
Human Factors ◽  
Real World ◽  
Lessons Learned ◽  
Laboratory Research ◽  
Preliminary Design ◽  
Design Study ◽  
Air Vehicle ◽  
Human Factors Research ◽  
Laboratory Task ◽  
Air Vehicles

Research from different laboratories could be compared more easily if a common set of research tasks were used. Such tasks should be amenable to controlled laboratory research, yet the results should generalize to important real-world tasks. In this paper, we describe the design of synthetic tasks, which are research tasks constructed by systematic abstraction from a corresponding real-world task. We present as an example a laboratory task (the cloud-break task) derived from a particularly demanding part of the reconnaissance mission of the USAF Predator uninhabited air vehicle. We describe potential pitfalls in decoupling a synthetic task from its normal mission context, and discuss some lessons learned from a preliminary design study.

HFACS Analysis of U.S. General Aviation Accidents Using Bayesian Network

2020 ◽  
Vol 64 (1) ◽  
pp. 1655-1659
Author(s):  
Chuyang Yang ◽  
John H. Mott
Keyword(s):  
Human Factors ◽  
Bayesian Network ◽  
General Aviation ◽  
Transportation Safety ◽  
Aviation Industry ◽  
Contributing Factors ◽  
The Sustainable Development ◽  
Aviation Accidents ◽  
Prior Probabilities ◽  
Probability Table

Safety is one of the most important factors that affects the sustainable development of the aviation industry. With the increasing robustness of technologies, humans have played a progressively more important causal role in aviation accidents. This paper applies an HFACS-BN model (HFACS: Human Factors Analysis and Classification System; BN: Bayesian Network) to analyze the root causes of aviation accidents. General aviation (GA) accident reports were collected from the U.S. National Transportation Safety Board (NTSB) accident database. The authors encoded the human factors of sample cases based on the HFACS framework and constructed a corresponding BN. From this work, parameter estimation associated with a conditional probability table (CPT) was conducted to determine prior probabilities of contributing factors, and a sensitivity test was conducted to determine the most significant factors. This study provides guidance to the federal government to facilitate risk management in order to reduce fatal general aviation accidents.

Ethics Education of Human Factors Engineers for Responsible AI Development

2021 ◽  
Vol 65 (1) ◽  
pp. 1034-1038
Author(s):  
Esa M. Rantanen ◽  
John D. Lee ◽  
Katherine Darveau ◽  
Dave B. Miller ◽  
James Intriligator ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Human Factors ◽  
Data Science ◽  
Ethics Education ◽  
Panel Discussion ◽  
Technical Skills ◽  
The Past ◽  
Human Factors And Ergonomics ◽  
Educational Challenges ◽  
Societal Impacts

This panel discussion is third in a series examining the educational challenges facing future human factors and ergonomics professionals. The past two panels have focused on training of technical skills in data science, machine learning, and artificial intelligence to human factors students. This panel discussion expands on these topics and argues for a need of new and broader training curricula that include ethics for responsible development of AI-based systems that will touch lives of everybody and have widespread societal impacts.

General Aviation Airplane Accidents Involving Spatial Disorientation

1995 ◽  
Vol 39 (1) ◽  
pp. 25-29 ◽  
Author(s):  
Rudolf G. Mortimer
Keyword(s):  
Human Factors ◽  
General Aviation ◽  
Transportation Safety ◽  
Physical Impairment ◽  
Human Factors Engineering ◽  
Physical Impairments ◽  
Spatial Disorientation ◽  
Flight Experience ◽  
Accident Data ◽  
Airplane Accidents

National Transportation Safety Board accident data for 1983-1991 were used to compare those general aviation accident cases that involved spatial disorientation (SD) with all others. About 2.1% of general aviation airplane accidents involved SD. Those accidents were associated with low ceilings, restricted visibility, precipitation, darkness and instrument flight conditions. Pilots in certain professions, particularly those in business, were more involved in SD accidents. Pilots in SD accidents were more often under pressure, fatigue, anxiety, physical impairment and alcohol or drugs. The pilots' total and night flying experience were inversely related to involvement in SD accidents. Spatial disorientation accidents accounted for a small number of crashes, but they were very severe-fatalities occurred in 92%, they accounted for 9.9% of the fatal accidents, 11% of the fatalities and in 95% the aircraft were destroyed. The results suggest that the pilots in SD accidents lacked the flight experience necessary to recognize or cope with the stimuli that induce SD, which was compounded by fatigue, alcohol/drugs or pressure and other psychological and physical impairments. Specific exposure to conditions leading to SD in training of general aviation and all pilots should be evaluated to help them to recognize it, and the techniques used by experienced pilots to combat its onset and effects should be studied and used in training. Improved human factors engineering of the cockpit instrumentation is also needed.

Review of Human Factors Applications in Forest Harvesting

1982 ◽  
Vol 26 (3) ◽  
pp. 271-275
Author(s):  
Leo A. Smith ◽  
Donald L. Sirois
Keyword(s):  
Human Factors ◽  
Environmental Stress ◽  
Forest Harvesting ◽  
Equipment Design ◽  
Work Physiology ◽  
The Past ◽  
Harvesting Systems ◽  
Human Factors Research

A review of human factors applications in forest harvesting operations is presented. The discussion covers work physiology, environmental stress, equipment design, and safety. The importance of each topic to forest harvesting and representative human factors studies are described. Several suggestions for research that appears needed are also mentioned. It is concluded that human factors research has significantly contributed to the improvement of forest harvesting systems in the past and that future human factors applications should result in similar benefits.

Making ‘Human Factors’ Truly Human: Cultural Considerations in Human Factors Research and Practice

2005 ◽  
Vol 49 (10) ◽  
pp. 941-945 ◽  
Author(s):  
Katherine Lippa ◽  
Helen Altman Klein
Keyword(s):  
Human Factors ◽  
Cultural Difference ◽  
Cultural Variation ◽  
Symbolic Communication ◽  
Cultural Considerations ◽  
The Past ◽  
Complex Processes ◽  
National Differences ◽  
Research Findings ◽  
Human Factors Research

Traditionally, human factors research has been conducted in Western nations to answer the questions of Western practitioners. This approach was appropriate in the past and still works well in many situations. However, as the world of work is becoming more international it is important to consider how national differences affect human factors applications. We review recent issues of the Human Factors journal to see how cultural differences are being addressed in research. Five domains where important cultural difference may influence research findings are reviewed. These areas are physical design, visual displays, symbolic communication, information technology and managing complex processes. We present recommendations for incorporating greater cultural variation into Ergonomic and Human Factors work.

Sex: The Missing Variable in Human Factors Research

1978 ◽  
Vol 20 (2) ◽  
pp. 245-249 ◽  
Author(s):  
Gerald A. Hudgens ◽  
Patricia A. Billingsley
Keyword(s):  
Sex Differences ◽  
Human Factors ◽  
Work Force ◽  
The Past ◽  
Human Factors And Ergonomics ◽  
Time Period ◽  
Males And Females ◽  
Male Subjects ◽  
Human Factors Research

During the past 35 years, an ever-increasing number of women has been entering the work force and assuming numerous jobs that were traditionally reserved for men. To see if human factors research has been keeping up with the problems and questions this trend inevitably poses, the content of two leading human factors journals (Human Factors and Ergonomics) was analyzed for the time period 1965 through 1976. Nearly half the 859 studies examined included only male subjects; only a quarter included females, either exclusively (6%), or with males (19%); and nearly a third gave no indication of the subjects' sex. Even in studies that included both males and females, only a third did analyses to determine whether there were sex differences. The desirability of considering the sex variable in human factors studies and several of the problems associated with doing so are discussed, and recommendations are offered.

scholarly journals Positive bias in the ‘Trust in Automated Systems Survey’? An examination of the Jian et al. (2000) scale

2019 ◽  
Vol 63 (1) ◽  
pp. 217-221 ◽  
Author(s):  
Robert S. Gutzwiller ◽  
Erin K. Chiou ◽  
Scotty D. Craig ◽  
Christina M. Lewis ◽  
Glenn J. Lematta ◽  
...  
Keyword(s):  
Self Report ◽  
Automated Systems ◽  
Future Directions ◽  
Alarm Signals ◽  
The Past ◽  
Original Scale ◽  
Potential Impact ◽  
Trust In Technology ◽  
Human Factors Research ◽  
Report Measure

Measuring trust in technology is a mainstay in Human Factors research. While trust may not perfectly predict reliance on technology or compliance with alarm signals, it is routinely used as a design consideration and assessment goalpost. Several methods of measuring trust have been employed in the past decades, but one self-report measure stands out due to its popular use, the Trust in Automated Systems Survey (Jian, Bisantz, & Drury, 2000). We conducted a study to assess whether the survey could create biased responses, and found evidence the original scale is in fact skewed toward positive ratings. Assessing the literature revealed the survey has been used in unaltered form across at least 100 different reports and remains frequently administered – therefore, the potential impact of this bias may be widespread. Future directions, considerations, and caveats for our assessment, and for using this scale, are discussed.

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