9/5/2002 General Aviation Requirements Requirement ID: 868 Special Category:  NONE Sponsor Organization:  AFS Sponsor POC: Mike Henry Keywords:  Acc/Inc Analysis/Invest, Decision Making, Errors Title: Human error and general aviation accidents: A comprehensive, fine-grained analysis using HFACS Research Statement: The Human Factors Analysis and Classification System (HFACS) is a theoretically based tool for investigating and analyzing human error associated with aviation accidents and incidents. Previous HFACS research performed at both at the University of Illinois and the Civil Aerospace Medical Institute (CAMI) has been highly successful and has shown that HFACS can be reliably used to analyze the underlying human factors causes of both commercial and general aviation accidents. Furthermore, these analyses have helped identify general trends in the types of human factors issues and aircrew errors that have contributed to civil aviation accidents. Key members of the FAA (e.g., AFS-800) and several committees chartered to address general aviation safety (e.g., Aeronautical Decision Making (ADM) JSAT and the General Aviation Data Improvement Team (GADIT)) have acknowledged the added value and insights gleaned from these HFACS analyses. However, these individuals and committees have directly requested that additional analyses be done to answer specific questions about the exact nature of the human errors identified, particularly within the context of general aviation. The purpose of the proposed research project, therefore, is to address these questions by performing a more fine-grained HFACS analysis of the individual human causal factors associated with fatal GA accidents and to assist in the generation of possible intervention programs.1453 Background: Humans by their vary nature make mistakes; therefore it is unreasonable to expect error-free human performance. It is no surprise then, that human error has been implicated in a variety of occupational accidents, including 70% to 80% of those in civil and military aviation (O'Hare, Wiggins, Batt, & Morrison, 1994; Yacavone, 1993). In fact, while the number of aviation accidents attributable solely to mechanical failure have decreased markedly over the past 40 years, those attributable at least in part to human error have declined at a much slower rate (Shappell & Wiegmann, 1996). It appears that interventions aimed at reducing the occurrence or consequences of human error have not been as effective as those directed at mechanical failures. Clearly, if accidents are to be reduced further, more emphasis has to be placed on the genesis of human error as it relates to accident causation. The predominant means of investigating the causal role of human error in aviation accidents remains the analysis of accident and incident data (Shappell & Wiegmann, 1997). Unfortunately, most accident reporting systems are not designed around any theoretical framework of human error. Indeed, most accident reporting systems are designed and employed by engineers and front-line operators with limited backgrounds in human factors. As a result, these systems have been effective at identifying engineering and mechanical failures, whereas the human factors component of these systems are generally narrow in scope. Furthermore, even when human factors are specifically addressed, the terms and variables used are generally ill defined and the data structures poorly organized. Postaccident databases are therefore not conducive to a traditional human error analysis, making the identification of intervention strategies onerous (Wiegmann & Shappell, 1997). What is required therefore, is a general human error framework around which new investigative methods can be designed and existing postaccident databases restructured. However, previous attempts to apply error frameworks to accident analysis have met with encouraging, yet limited, success (O'Hare et. al., 1994; Wiegmann & Shappell, 1997). This is due primarily to the fact that performance failures are influenced by a variety of human factors that usually are not addressed by traditional frameworks. With few exceptions (e.g., Ramussen, 1982), human error taxonomies do not consider the potential adverse mental and physiological condition of the individual (e.g., fatigue, illness, attitudes, etc.) when describing errors in the cockpit. Furthermore, latent errors committed by officials within the management hierarchy, such as line managers and supervisors are often not addressed, even though it is known that these factors directly influence the condition and decisions of pilots (Reason, 1990). Therefore, if a comprehensive analysis of human error is to be conducted, a taxonomy that takes into account these multiple causes of human failure must be offered. A comprehensive Human Factors Analysis and Classification System (HFACS) has recently been developed to meet these needs (see Figure 1). This system, which is based upon Reason’s (1990) model of latent and active failures addresses human error at each of four levels of failure: 1) unsafe acts of operators (e.g., aircrew), 2) preconditions for unsafe acts, 3) unsafe supervision, and 4) organizational influences. The HFACS framework was originally developed for the U.S. Navy and Marine Corps as an accident investigation and data analysis tool. Since its original development however, HFACS has been employed by other military organizations (e.g., U.S. Army, Air Force, and Canadian Defense Force) as an adjunct to preexisting accident investigation and analysis systems. To date, the HFACS framework has been applied to over 1,000 military aviation accidents yielding objective, data-driven intervention strategies while enhancing both the quantity and quality of human factors information gathered during accident investigations (Shappell & Wiegmann, 2001). Other organizations such as the FAA and NASA have explored the use of HFACS as a complement to preexisting systems within civil aviation in an attempt to capitalize on gains realized by the military. These initial attempts, performed both at the University of Illinois and the Civil Aerospace Medical Institute (CAMI) have been highly successful and have shown that HFACS can be reliably used to analyze the underlying human factors causes of both commercial and general aviation accidents (Shappell & Wiegmann, 2001; Wiegmann & Shappell, in press). Furthermore, these analyses have helped identify general trends in the types of human factors issues and aircrew errors that have contributed to civil aviation accidents. Indeed, AFS-800, the Aeronautical Decision Making (ADM) JSAT and the General Aviation Data Improvement Team (GADIT) have acknowledged the added value and insights gleaned from these HFACS. To date, however, these initial analyses using HFACS have generally been performed at a global level and several questions remain concerning the underlying nature and prevalence of different error types. In fact, AFS-800, the ADM JSAT, and the GADIT committees have directly requested that additional analyses be done to answer specific questions about the exact nature of the human errors identified, particularly within the context of general aviation. Some of these questions are: 1. What are the exact types of errors committed within each error category? In other words, how often do skill-based errors involve stick-and-rudder errors, verses attention failures (slips) or memory failures (lapses)? 2. How important is each error type, or how often is each error type the “primary” cause of an accident? For example, 80% of accidents might be associated with skill-based errors, but how often are skill-based errors the “initiating” error or simply the “consequence” of another type of error, such as decision errors? 3. How do the different error types relate to one another, or with other HFACS variables? Are there connections between the categories that, if known, could improve intervention development? 4. Do accidents that occur in different geographical regions or training facilities within the U.S. have different error patterns or trends? 5. What can be done to intervene given the information that is now available, and what more might be done with the additional refined data? Answers to these questions are not available in the database as it currently exists. Therefore, additional fine-grained analyses of the specific human error categories within HFACS are needed to answer these, and other questions that may arise, and to target problem areas within general aviation for future interventions. Output: The proposed research project, therefore, is in response to these questions and requests made by AFS-800, the ADM JSAT, and the GADIT committees. Specifically, the goal of this project is to perform a comprehensive and systematic analysis of the individual human causal factors associated with fatal GA accidents. As a joint effort between researchers at the University of Illinois and the FAA’s Civil Aerospace Medical Institute, the HFACS framework will be used to perform fine-grained analyses of GA accident data to explore the nature of the underlying human errors associated with these events. The results of these analyses will then be used to map intervention strategies onto different error categories to determine plausible prevention programs for reducing GA accidents. Results will be provided to appropriated FAA officials and committees for consideration. Ultimately, this project will represent the next step in the development of a larger civil aviation safety program whose ultimate goal is to reduce the aviation accident rate through systematic, data-driven investment strategies and objective evaluation of intervention programs. Regulatory Link: a. Supports Safer Skies through Areonautical Decision Making (ADM) JSAT b. AOA (FAA) Strategic Plan (1998-2003) Mission Goal:Safety. Key Strategies "to enable the goal to include identification of root causes of past accidents; and (2) use a more proactive analytical approach, with new data sources, to identify key risk factors and intervene to prevent potential causes of future accidents" (Page 13). c. FY2001 Performance Plan: Focus Area: Accident Prevention. "Aviation Human Factors to coordinate human factors research, development and based on detailed causal analysis" (Page 2) d. AVR Performance Plan:Reduce General Aviation fatal accidents (pg 2). Contribute to aviation safety by developing policies,standards, programs, and systems to reduce the number of aviation accidents and incidents related to human factors (pg 9)