General Aviation Accidents Research Articles

Insufficient safety capability among general aviation practitioners: Evidence from Chinese accident data

The rapid development of China’s general aviation (GA) industry has brought about an increase in safety risks and accidents. Despite extensive investigations into these accidents, the factors related to the safety capability (SC) of practitioners have been largely overlooked, resulting in a lack of targeted safety education and training policies. Hence, this study aims to investigate the characteristics of practitioners’ SC deficiencies in the GA industry. Data for this study were sourced from GA accident reports in China from 2018 to 2022. First, the reports were identified and encoded to extract relevant concepts and categories based on grounded theory. Second, the 24Model was used to classify these categories. After that, the relationship between the core category and the main category was delineated according to the accident scenarios. This comprehensive study has resulted in the development of a SC conceptual framework comprising five core categories and fifteen main categories. In addition, the correspondence between flight tasks, practitioners, and SC factors and the relationship between cases and SC factors are revealed. The findings underscore that insufficient theoretical knowledge and a lack of risk awareness, particularly among pilots, emerge as pivotal SC factors contributing to GA accidents, especially during flight training. In summary, this study introduces a framework that advances our comprehension of SC deficiencies among GA practitioners and offers valuable insights for the enhancement of GA safety through safety education and training. Additionally, it offers guidance to stakeholders in formulating the most effective strategies for cultivating SC.

Over a decade of UAV incidents: A human factors analysis of causal factors

This analysis examined systemic causes of Uncrewed Air Vehicle (UAV) accidents identifying operator, environmental, supervisory, and organisational factors through the use of the Human Factors Analysis and Classification System (HFACS). HFACS is a system-based analysis method for investigating the causal factors associated with accidents and incidents and has previously been used to reliably and systematically identify active and latent failures associated with both military and general aviation accidents. Whilst HFACS has previously been applied to UAV accidents, the last known application was conducted in 2014. Using reports retrieved from nine accident investigation organisations’ databases, causal factors were coded against unsafe acts, preconditions, and failures at the supervisory, organisational, and environmental levels. Causal factors were assessed on 77 medium or large UAV mishaps/accidents that occurred over a 12-year period up to 2024. 42 mishap reports were deemed to involve a human factor as a causal factor. A large proportion of the mishaps contained factors attributed to Decision Errors at level 1 (Unsafe Acts) which was found to be associated with both the Technological Environment and Adverse Mental State at level 2 (Pre-conditions). Causal factors were identified at each of the other 3 levels (Supervisory, Organisational and External) with a number of emergent associations between causal factors. These data provide support for the identification and development of interventions aimed at improving the safety of organisations and advice of regulators for Uncrewed Air Systems.

Human Factors in General Aviation Loss of Control: Survey of Pilot Experiences

Inflight loss of control (LOC-I) is a major cause of general aviation (GA) accidents. Previous studies have identified LOC-I causes from sources such as the National Transportation Safety Board (NTSB) database. NTSB GA accident reports include limited detail on human factors. Getting pilots’ perspectives from other sources, such as surveys, may reveal insights into pilot actions and conditions. This study investigates the role of human factors in LOC-I by analyzing demographics in NTSB accidents and conducting a survey of pilots’ LOC-I experiences based on the Human Factors Analysis and Classification System framework. Note that 80% of the LOC-I events shared by the pilots involved pilot error, most of which were skill-based and decision errors. About one-quarter of pilots mentioned that their instructor had not prepared them well or taught them methods to recover from LOC-I. Several pilots mentioned that, because of their lack of LOC-I recovery training, they could not recover from LOC-I. The study helped in identifying specific pilot errors and issues in training that were not mentioned explicitly in the NTSB reports. Findings from the study may help improve training methods and operating procedures for GA pilots to prevent loss of control in the future.

Key Insights from Preflight Planning for Safety Improvement in General Aviation: A Systematic Literature Review

This study highlights the disproportionate number of fatal and non-fatal accidents in general aviation (GA) compared to airline carriers, emphasizing the need to investigate the contributing factors to these incidents. It identifies poor decision-making and a lack of situational awareness as key issues and presents a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to analyze preflight information used by GA pilots. The findings underscore the significance of operational factors in ensuring a successful flight and suggest modifications to pilot license renewal processes, with an emphasis on the adoption of digital preflight tools. A new theoretical framework based on the operational factors identified is also introduced, which could serve as a foundation for future studies and interventions aimed at enhancing safety in general aviation.

Nose-Over and Nose-Down Accidents in General Aviation: Tailwheels and Aging Airplanes

Safety in General Aviation has been a continuous concern. About 12% of all airplane accidents in General Aviation involve nose-overs and nose-down events. A total of 134 accidents reported by the National Transportation Safety Board that include nose-overs and nose-downs were analyzed for their main causes. It was found that 35% of the defining events involved a loss of control on the ground while 58% of the total dataset involved tailwheel-type aircraft. A relatively high proportion of aircraft built before 1950 were found, which are also aircraft that have tailwheel-type landing gear, and thereby a higher propensity for ground loops and nose-overs. It is shown that the high accident rate in General Aviation, especially for accidents that did not result in a fatality, was, to an important extent, explained by tailwheel and older aircraft in the US General Aviation airplane fleet struggling with controlling the aircraft on the ground. Attention to this group of aircraft in future studies may help to more effectively address the relatively high accident rates in General Aviation.

Deficient Aeronautical Decision-Making Contributions to Fatal General Aviation Accidents.

INTRODUCTION: General aviation (GA), mainly comprised of light (≤12,500 lb) aircraft, maintains an inferior safety record compared with air carriers. To improve safety, aeronautical decision-making (ADM) practices have been advocated to GA pilots since 1991. Herein, we determined the extent to which GA pilots disregard such practices.METHODS: Fatal accidents (1991-2019) involving private pilots (PPLs) in single-engine airplanes were identified (N = 1481) from the National Transportation Safety Board AccessR database. Of these, deficient go/no-go and in-flight ADM-related mishaps were scored using the PAVE (pilot, aircraft, environment, external pressure)/IMSAFE (illness, medicine, stress, alcohol, fatigue, eating) and PPP (perceive, process, perform) models, respectively. Statistical testing used Poisson distributions, Fisher exact tests, and Mann-Whitney U-tests.RESULTS: Of the 1481 accidents, 846 were identified as deficient ADM-related. Electing to depart into a hazardous environment (PAVE), disregarding wellness (IMSAFE), and poor aircraft familiarity (PAVE) represented the most common categories (54%, 21%, and 20%, respectively) of errant go/no-go ADM. A 64% decline in fatal accidents related to errant go/no-go decisions for the environment category was evident over the 30-yr period, with little decrements in the other domains. Within the errant environment-related category accidents, the decision to depart into forecasted adverse weather (e.g., degraded visibility, icing, thunderstorms) constituted the most prevalent subcategory (56%, N = 195). Surprisingly, of this subcategory, accidents were overrepresented by over nine- and threefold for instrument-rated PPLs disregarding icing and thunderstorm forecasts, respectively.CONCLUSION: With little decrement in ADM-related accidents in the pilot, aircraft, and external pressure domains, new strategies to address such deficiencies for PPLs are warranted.Boyd DD, Scharf MT. Deficient aeronautical decision-making contributions to fatal general aviation accidents. Aerosp Med Hum Perform. 2023; 94(11):807-814.

Nonlinear Time Series Analysis and Prediction of General Aviation Accidents Based on Multi-Timescales

General aviation accidents have complex interactions and influences within them that cannot be simply explained and predicted by linear models. This study is based on chaos theory and uses general aviation accident data to conduct research on different timescales (HM-scale, ET-scale, and EF-scale). First, time series are constructed by excluding seasonal patterns from the statistics of general aviation accidents. Secondly, the chaotic properties of multi-timescale series are determined by the 0–1 test and Lyapunov exponent. Finally, by introducing the sparrow search algorithm and tent chaotic mapping, a CSSA-LSSVM prediction model is proposed. The accident data of the National Transportation Safety Board (NTSB) of the United States in the past 15 years is selected for case analysis. The results show that the phase diagram of the 0–1 test presents Brownian motion characteristics, and the maximum Lyapunov exponents of the three scales are all positive, proving the chaotic characteristics of multi-timescale series. The CSSA-LSSVM prediction model’s testing results illustrate its superiority in time series predicting, and when the timescale declines, the prediction error reduces gradually while the fitting effect strengthens and then decreases. This study uncovers the nonlinear chaotic features of general aviation accidents and demonstrates the significance of multi-timescale research in time series analysis and prediction.

Securing air transportation safety through identifying pilot's risky VFR flying behaviours: An EEG-based neurophysiological modelling using machine learning algorithms

Most general aviation accidents result from pilot errors while flying under visual flight rules (VFR), many of which are linked to situation awareness prone to meteorological and situational effects. This study reveals the impacts of weather and flight route factors contributing to unsafe flight behaviours on pilots’ performance (flight operation & neurophysiology). Importantly, another purpose is to identify risky flight behaviours by executing EEG-based neurophysiological modelling for securing air transportation safety. A two-by-two (adverse/clear weather; experienced/inexperienced flight route) within-subject experiment was conducted. Inexperienced flight routes have an explicit impact on contributing to unsafe flight operations except during departure and descent. However, the neurophysiological activity in power spectrum density and cooperative correlation showed that meteorology deterioration may require more mental efforts and have an implicit impact on maintaining safe flight awareness, making it challenging to correct risky flight operations due to mental resource exhaustion possibly. For the pilot's risky behaviour identification, neurophysiological modelling using EEG data was established, and a leave-one-subject-out cross-validation was used to evaluate the modelling feasibility, with the highest accuracy of 80.8%. This work could serve as the foundation for developing a real-time risky flight behaviour prediction modelling that could support safety-enhancing air transportation via artificial intelligence.

A Self-Learning Mechanism-Based Approach to Helicopter Entry and Departure Recognition.

In order to accurately record the entry and departure times of helicopters and reduce the incidence of general aviation accidents, this paper proposes a helicopter entry and departure recognition method based on a self-learning mechanism, which is supplemented by a lightweight object detection module and an image classification module. The original image data obtained from the lightweight object detection module are used to construct an Automatic Selector of Data (Auto-SD) and an Adjustment Evaluator of Data Bias (Ad-EDB), whereby Auto-SD automatically generates a pseudo-clustering of the original image data. Ad-EDB then performs the adjustment evaluation and selects the best matching module for image classification. The self-learning mechanism constructed in this paper is applied to the helicopter entry and departure recognition scenario, and the ResNet18 residual network is selected for state classification. As regards the self-built helicopter entry and departure data set, the accuracy reaches 97.83%, which is 6.51% better than the bounding box detection method. To a certain extent, the strong reliance on manual annotation for helicopter entry and departure status classification scenarios is lifted, and the data auto-selector is continuously optimized using the preorder classification results to establish a circular learning loop in the algorithm.

Density Altitude: Climatology of Daily Maximum Values and Evaluation of Approximations for General Aviation

Abstract Density altitude (DA) is an aviation parameter that helps determine specific aircraft performance characteristics for the expected atmospheric conditions. However, there are currently no detailed graphical tools for general aviation (GA) pilot education demonstrating the spatial and temporal variation of DA to help improve situational awareness. In this study, the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate (ERA5) dataset is used to construct a 30-yr monthly climatology of DA for the conterminous United States. Several DA characteristics are also investigated, including the effect of humidity on DA, the determination of reasonable worst-case conditions, and the applicability of two DA rules of thumb (ROTs). Maximum values of DA (worst aircraft performance) occur during July, reaching 3600 m over areas with high surface elevations. Humidity, while tertiary to the effects of temperature and pressure, causes the DA to increase from their dry values by more than 140 m as far north as the U.S.-Canada border. The dry DA ROT performs well for all conditions outside of strong tropical cyclones, where GA flights would not be expected. The ROT to correct for the effects of humidity performs well except in high elevations or when the dewpoint temperatures fall outside the applicable range of ≥5°C. When applied outside this range, in some situations, DA errors can be greater than if no humidity correction were applied. Therefore, a new ROT to correct for humidity is introduced here that extends the applicable dewpoint temperature range to ≥−28°C and reduces errors in estimated DA. Significance Statement The impacts of density altitude on aircraft performance have led to numerous general aviation (GA) accidents. This study helps GA pilots better understand the spatial and temporal variability in density altitude, thereby increasing their situational awareness during flight planning. This study also evaluates commonly used approximations to estimate density altitude, so pilots can understand the situations where these approximations are (in)applicable. Results suggest the need for a humidity correction approximation when dewpoint temperatures are <5°C, which is introduced in this study.

Charting a Path Through the Storm: General Aviation Weather Training Recommendations

For general aviation (GA) pilots, weather was the primary contributing factor for 25% of accidents between 1982 and 2013 (Fultz & Ashley, 2016). All GA pilots must complete the same certification exam and requirements, however not all GA pilots are receiving the same depth of training. Depending on their flight school, pilots-in-training may be lacking important opportunities to practice applying weather theory to aviation. Attending to this gap in training by providing more opportunities to practice applying their weather knowledge may help reduce the number of weather-related accidents in GA. This paper outlines certification requirements and guidelines to become a private pilot, clarifies weather-knowledge requirements, outlines how pilots currently learn their weather, and makes training recommendations to potentially reduce the number of weather-related accidents in GA.

Measuring Mental Models: General Aviation Pilots’ Understanding of Preflight Weather

Weather has contributed to hundreds of General Aviation accidents. Research suggests inadequate preflight planning and lack of aviation weather knowledge are contributing factors. This study describes the development of three mental model measures (departure, enroute, and arrival) designed to assess pilots’ understanding of current and forecasted conditions. Each measure requires pilots (n=23) to evaluate weather conditions (flight category) at different regions within the flight area. A two-way mixed ANOVA examined differences in pilots’ understanding of flight category across three preflight weather briefing conditions (flight services call, self-briefing, and a combined condition) and three phases of flight (POF). No significant interaction occurred between briefing condition and POF on pilots’ ability to identify the correct flight category. However, significant differences in pilots’ understanding of weather conditions occurred between phases. Pilots were most effective at assessing flight category/weather on the enroute mental model measure and least effective at assessing weather forecasted surrounding arrival.

Adherence to Selected Air Carrier (Airline) Operational Regulations for Improved General Aviation Flight Safety in Degraded Visibility

Introduction: General aviation largely comprises fixed-wing piston-engine light aircraft (,12,500 lbs). Unfortunately, this civil aviation sector suffers a vastly inferior safety record when compared with air carriers (60- to 80-fold higher accident rate). Additionally, such mishaps pose a considerable financial burden to both the affected family and the United States: US$1.64–4.64 billion annually. We hypothesize that this safety disparity partly reflects more stringent operational regulations for air carriers. Herein, we determined whether compliance with six selected air carrier regulations could potentially reduce general aviation accidents in degraded visibility (IMC) the majority of which are fatal. Methods: Accidents (2005–2019) were identified from the National Transportation Safety Board Access database. Fleet data for rate calculations were per the general aviation survey and the Bureau of Transportation Statistics. Statistics used Poisson distributions. Results: Of 219 general aviation accidents in IMC, 43 (20%) could potentially have been averted had one, or more, of the selected air carrier regulations been complied with. The largest percentage (62%) of the 43 mishaps were due to pilots operating contrary to the air carrier regulation specifying takeoff or landing weather minimums. The second largest group related to more conservative weather minimums required for an inexperienced airline pilot-in-command, eschewed in 19% of preventable general aviation IMC mishaps. Conclusions: Alignment with the aforementioned air carrier operational rules could potentially blunt the IMC accident rate (by 20%) for general aviation. Practical Applications: Adherence to the aforementioned air carrier regulations should be advocated to general aviation pilots operating in IMC.

General Aviation Accidents Involving Fixed-Wing Aircraft on the Ground.

BACKGROUND: Accidents during start-up and shut-down procedures of aircraft can lead to fatalities or destroyed aircraft. Start-up procedures for propeller aircraft include the possibility of hand-propping, which may increase the occurrence of injuries from propeller strikes.METHODS: A set of 142 accidents from a 10-yr period were selected from the U.S. National Transportation Safety Board online database. Only fixed-wing aircraft in the "standing" phase of flight were included in the dataset. The significance of differences was determined using Pearson's Chi-squared analysis.RESULTS: The severity of the injuries sustained in the accidents were inversely related to the amount of damage to the aircraft. Hand-propping without properly securing the aircraft was more likely to result in substantial damage to the aircraft. Pilots with less than a thousand hours of flight experience were significantly more likely to use an incorrect hand-propping procedure.CONCLUSIONS: It is recommended to make the advisory on hand-propping a regulatory article of the Federal Aviation Administration so that pilots' knowledge of this procedure is mandatory and part of their initial training, especially securing the aircraft during hand-propping. Highlighting throttle positions in both regular and hand-propping procedures may optimize checklist design and further mitigate accidents during start-up procedures.de Voogt AJ, Kalagher H, Burns S. General aviation accidents involving fixed-wing aircraft on the ground. Aerosp Med Hum Perform. 2022; 93(7):597-600.

Go-around accidents and general aviation safety

Introduction: Changes in General Aviation (GA) accident rates, specifically in the go-around phase, are examined by comparing the number of accidents, the proportion of fatal accidents, and the proportion of certain causes of accidents over time. Methods: Two sets of accidents from 2000 to 2004 and from 2013 to 2017 were extracted from the National Transportation Safety Board (NTSB) online database. Results: Although the total number of GA accidents per landing significantly decreased over time, the proportion of fatal accidents in the go-around phase increased. Fatalities most often occurred in instrument meteorological conditions. Conclusion: Advances in technology and training show improvements in GA accident rates, but not for accidents in the go-around phase. Practical Applications: Scenario-based learning is recommended to include specific instruction concerning the timing of go-around procedures in unstable flights.

Identification and Validation of the Cessna Citation X Longitudinal Aerodynamic Coefficients in Stall Conditions using Multi-Layer Perceptrons and Recurrent Neural Networks

The increased number of accidents in general aviation due to loss of aircraft control has necessitated the development of accurate aerodynamic airplane models. These models should indicate the linear variations of aerodynamic coefficients in steady flight and the highly nonlinear variations of the aerodynamic coefficients due to stall and post-stall conditions. This paper presents a detailed methodology to model the lift, drag, and pitching moment aerodynamic coefficients in the stall regime, using Neural Networks (NN). A system identification technique was used to develop aerodynamic coefficients models from flight data. These data were gathered from a level-D Research Aircraft Flight Simulator (RAFS) that was used to execute the stall maneuvers. Multilayer Perceptrons and Recurrent Neural Networks were used to learn from flight data and find correlations between aerodynamic coefficients and flight parameters. This methodology is employed in here to optimize neural network structures and find ideal hyperparameters: training algorithms and activation functions used to learn the data. The developed stall aerodynamic models were successfully validated by comparing the lift, drag, and pitching moment aerodynamic coefficients predicted for given pilot inputs with experimental data obtained from the Cessna Citation X RAFS for the same pilot inputs.

Cause analysis of unsafe acts of pilots in general aviation accidents in China with a focus on management and organizational factors

Objectives. General aviation (GA) safety has become a key issue worldwide and pilot errors have grown to be the primary cause of GA accidents. However, fewer empirical studies have examined the contribution of management and organizational factors for these unsafe acts. Flawed decisions at the organizational level have played key roles in the performance of pilots. This study provides an in-depth understanding of the management and organizational factors involved in GA accident reports. Methods. A total of 109 GA accidents in China between 1996 and 2021 were analysed. Among these reports, pilot-related accidents were analysed using the human factors analysis and classification system (HFACS) framework. Results. The significant effects of managerial and organizational factors and the failure pathways on GA accidents have been identified. Furthermore, unlike traditional HFACS-based analyses, the statistically significant relationships between failures at the organizational level and the sub-standard acts of the pilots in GA accidents were revealed. Conclusions. Such findings support that the GA accident prevention strategy that attempts to reduce the number of unsafe acts of pilots should be directed to the crucial causal categories at HFACS organizational levels: resource management, organizational process, failure to correct a known problem, inadequate supervision and supervisory violations.

Fixed-Wing Motorized Aircraft Accidents: Analysis of Injury Severity and Concomitant Factors (2000-2019).

BACKGROUND: There is a paucity of research on general aviation accidents in Germany. The authorities investigate only a fraction of all national accidents. The current study analyzes existing accident reports and aims to identify injury severity in regard to concomitant risk factors.METHODS: Data of flight accidents was analyzed for aircraft of <5700 kg maximum takeoff weight (MTOW) over a 20-yr period. Besides descriptive data, concomitant factors (type and category of aircraft, date, occupants and outcome, flight phase, etc.) were analyzed. Statistical analysis was performed using the Chi-squared test.RESULTS: The authorities list 1595 aircraft accidents between 2000 and 2019, but only 17.9% of these were analyzed in detail. Accidents of aircraft of <2000 kg MTOW were over-represented between May and September and between Friday and Sunday. The fraction of fatal accidents was highest during cruise. During landing, significantly more mishaps of larger aircraft occurred. The number of seriously injured or deceased occupants was significantly higher for accidents involving private pilots. An occupancy rate of more than three persons on board correlated significantly with fewer number of deaths.CONCLUSIONS: The annual count of aircraft accidents has almost halved during the previous 20 yr. Unfortunately, only a small number of mishaps were further investigated by authorities, which leads to a lack of evaluable data needed for in-depth investigations. The accumulation of larger aircraft mishaps in winter and the superior outcome of professional pilots in terms of safety, as well as the fewer number of mishaps in larger aircraft, should be further investigated.Liebold F, Hippler C, Schmitz J, Yücetepe S, Rothschild M, Hinkelbein J. Fixed-wing motorized aircraft accidents: analysis of injury severity and concomitant factors (2000-2019). Aerosp Med Hum Perform. 2022; 93(5):442-449.

Situational Awareness and General Aviation Accidents

Abstract. Situational awareness is a concept increasingly used in aircraft accident investigation reports. We analyzed 94 general aviation accidents in which situational awareness was mentioned by the National Transportation Safety Board investigator to determine factors that are significantly more often associated with fatality. We found a consistent use of the situational awareness concept, mainly applied to situations in which aircraft inadvertently collided with each other, with other man-made objects, and with various kinds of terrain. A significantly higher proportion of fatal accidents occurred during nighttime, in instrument meteorological conditions, or low visibility conditions. In addition, flights occurring during the cruise phase or in combination with spatial or geographical disorientation proved most often fatal.

Evolution Mechanism on the Unsafe Behavioural Risks of General Aviation Pilots

The unsafe behaviour prevention and control of general aviation pilots has become an emphasis in the general aviation safety management with the increasing number of general aviation enterprises, lengthening of flight time and frequent occurrence of public safety events caused by general aviation accidents. How to identify the factors influencing the unsafe behaviours of general aviation pilots and clarify the inter factor evolution mechanism is hot issue in the general aviation. To accurately identify the key factors influencing the unsafe behaviours of general aviation pilots and define the interaction mechanism between factors, using the unsafe behaviours of pilots in 200 global general aviation accidents during 2015-2019 and the association rule method, the bottom-layer factors of the Human Factors Analysis and Classification System (HFACS) model were analysed. Furthermore, the influence degree, influenced degree, centrality and causality of the influencing factors in the HFACS model were calculated, and the risk transfer path at different layers was determined on the basis of the integrated decision-making trial and evaluation laboratory (DEMATEL) and fuzzy theory. Results show that the poor individual ready state is strongly associated with skill error, decision-making error and habitual violation. Moreover, 11 factors, such as poor physical environment, physical/intelligence limitation and poor technical environment, constitute the factors in the cause group for pilot unsafe behaviours. 7 factors, such as insufficient supervision, improper operation plan and failure to discover and correct problems, are the factors in the result group. Illegal behaviour, failure to discover and correct problems and decision-making error of pilots, which are of high centrality, are key factors influencing the unsafe behaviours of general aviation pilots. The conclusions obtained from this study compensate the deficiencies for the linear statistical model of risk factors and provide a novel method for regulating and controlling the unsafe behaviours of general aviation pilots.