Commercial Aviation Accidents Research Articles

A novel sequential risk assessment model for analyzing commercial aviation accidents: Soft computing perspective.

Due to the importance of the commercial aviation system and, also, the existence of countless accidents and unfortunate occurrences in this industry, there has been a need for a structured approach to deal with them in recent years. Therefore, this study presents a comprehensive and sequential model for analyzing commercial aviation accidents based on historical data and reports. The model first uses the failure mode and effects analysis (FMEA) technique to determine and score existing risks; then, the risks are prioritized using two multi-attribute decision making (MADM) methods and two novel and innovative techniques, including ranking based on intuitionistic fuzzy risk priority number and ranking based on the vague sets. These techniques are based in an intuitionistic fuzzy environment to handle uncertainties and the FMEA features. A fuzzy cognitive map is utilized to evaluate existing interactions among the risk factors, and additionally, various scenarios are implemented to analyze the role of each risk, group of risks, and behavior of the system in different conditions. Finally, the model is performed for a real case study to clarify its applicability and the two novel risk prioritization techniques. Although this model can be used for other similar complex transportation systems with adequate data, it is mainly employed to illustrate the most critical risks and for analyzing existing relationships among the concepts of the system.

Near miss prediction in commercial aviation through a combined model of grey neural network

Owing to unprecedented level of safety management, there have been few commercial aviation accidents recently, obstructing accurate prediction of safety trends. The innovative approach of proactive safety management was employed to replace reactive safety management for predicting commercial aviation near misses. In light of positive correlation between flight time and commercial aviation near-miss with different severity levels, this study aims to predict total / serious / non-serious near-miss per million flight hours. Considering grey system theory is good at prediction without adequate data, and artificial neural networks can handle nonlinear data well, the combined models of grey neural networks were developed for forecasting three data sequences over time respectively. Based on the empirical results of commercial aviation near-miss forecasting, BP neural network had the potential to enhance accuracy of grey prediction model. The three statistical measures of MAE/MSE/MAPE denoted the combined model of grey neural network outperformed the single model of GM (1, 1) or BP neural network. Predictions with a high degree of accuracy is beneficial to determining actual trends of commercial aviation near-misses at present or in future. Quantitative data will be offered for making specific decisions on maintaining preventive measures or promoting commercial aviation safety performance by introducing additional management actions

Near miss prediction in commercial aviation through a combined model of grey neural network

Owing to unprecedented level of safety management, there have been few commercial aviation accidents recently, obstructing accurate prediction of safety trends. The innovative approach of proactive safety management was employed to replace reactive safety management for predicting commercial aviation near misses. In light of positive correlation between flight time and commercial aviation near-miss with different severity levels, this study aims to predict total / serious / non-serious near-miss per million flight hours. Considering grey system theory is good at prediction without adequate data, and artificial neural networks can handle nonlinear data well, the combined models of grey neural networks were developed for forecasting three data sequences over time respectively. Based on the empirical results of commercial aviation near-miss forecasting, BP neural network had the potential to enhance accuracy of grey prediction model. The three statistical measures of MAE/MSE/MAPE denoted the combined model of grey neural network outperformed the single model of GM (1, 1) or BP neural network. Predictions with a high degree of accuracy is beneficial to determining actual trends of commercial aviation near-misses at present or in future. Quantitative data will be offered for making specific decisions on maintaining preventive measures or promoting commercial aviation safety performance by introducing additional management actions

Native Language Effects on Flight Training Performance

Several high-profile commercial aviation accidents in the past that were caused in part by inadequate English language proficiency confirmed the importance of clear and concise communication between air traffic controllers and pilots. Although the connection between English language proficiency and aviation safety has been well established, there has been very little research concerning the relationship between English language proficiency and flight training performance. Thousands of international students who are not native speakers of the English language come to the United States and Canada for ab initio flight training every year. While the ability to communicate with air traffic controllers is critical for the safety of flight, communication skills can also have a profound effect on flight training performance. International flight students not only must communicate with air traffic controllers, but they must also communicate with their flight instructors on the ground and in flight. In addition, they must also be able to read and understand textbooks, manuals, and check lists that are all written in the English language. This research is focused on the relationship between English language proficiency and performance in ab initio flight training programs.

The dynamics between voluntary safety reporting and commercial aviation accidents

Since 1975, the Aviation Safety Reporting System (ASRS) has collected over 1.6 million reports from aviation community members and contributed to the efficiency and safety improvement of the National Airspace System (NAS) of the United States. Despite a large number of studies using ASRS data, the dynamics between safety reporting and aviation accidents remains unclear. Focusing specifically on the Part 121 air carriers of the U.S., this paper addresses the temporal relationship between voluntary safety reporting and the occurrence of commercial aviation accidents. Due to the uncertain and potentially mixed order of integration of the time-series data, this study uses Autoregressive Distributed Lag (ARDL) bounds testing and a special Vector Autoregressive (VAR) model based on Toda and Yamamoto (1995) for data analysis and cross-validation of the results. The ARDL bounds testing finds a long-run relationship from aviation accidents to safety reporting. This finding is confirmed by the estimation results of the VAR model that aviation accidents Granger cause voluntary safety reporting. Short-run relationships identified in ADRL bounds testing and impulse-response function (IRF) of the VAR model reveal that the response of safety reporting to aviation accidents peaks in the 4th and 5th quarter after the occurrence of accidents. Understanding the inter-temporal relationship between safety reporting and aviation accidents could facilitate the interpretation of reporting data for government agencies or safety departments of airlines overseeing safety reporting systems. The short-run and long-run relationships between voluntary safety reporting and aviation accidents identified in this study for U.S. air carriers could be used as benchmarks for other national aviation safety agencies or airlines to assess their safety reporting cultures.

Visual scanning strategies in the cockpit are modulated by pilots' expertise: A flight simulator study.

During a flight, pilots must rigorously monitor their flight instruments since it is one of the critical activities that contribute to update their situation awareness. The monitoring is cognitively demanding, but is necessary for timely intervention in the event of a parameter deviation. Many studies have shown that a large part of commercial aviation accidents involved poor cockpit monitoring from the crew. Research in eye-tracking has developed numerous metrics to examine visual strategies in fields such as art viewing, sports, chess, reading, aviation, and space. In this article, we propose to use both basic and advanced eye metrics to study visual information acquisition, gaze dispersion, and gaze patterning among novices and pilots. The experiment involved a group of sixteen certified professional pilots and a group of sixteen novice during a manual landing task scenario performed in a flight simulator. The two groups landed three times with different levels of difficulty (manipulated via a double task paradigm). Compared to novices, professional pilots had a higher perceptual efficiency (more numerous and shorter dwells), a better distribution of attention, an ambient mode of visual attention, and more complex and elaborate visual scanning patterns. We classified pilot's profiles (novices-experts) by machine learning based on Cosine KNN (K-Nearest Neighbors) using transition matrices. Several eye metrics were also sensitive to the landing difficulty. Our results can benefit the aviation domain by helping to assess the monitoring performance of the crews, improve initial and recurrent training and ultimately reduce incidents, and accidents due to human error.

Application of HFACS to the Nighttime Aviation Accidents and Incidents

Commercial aviation accidents and incidents more prevalent at the certain times of the day. Operational problems (e.g., night vision, flash blindness, black hole illusion, and reflection) faced by pilots while performing nighttime flights pose threats to flight safety. The present paper aims to examine the contributing factors to commercial aviation accidents occurred at night. In this paper, accident reports of 30 commercial airplane crashes occurred over the past five years were analyzed. The contributing factors of those accidents were examined by using HFACS (Human Factors Analysis and Classification System). The relative importance of the causal factors was determined. Literature reviews have indicated that no study has examined the causality of nighttime commercial aircraft accidents by using HFACS as a framework. It was found that physical environment was the most significant causal factor. Skill-based errors were second-highest contributing factors. Perceptual errors and decision errors were ranked as third-highest causal factors. We believe that our results may be useful for reducing the chances of human error and raising safety standards of commercial airline operations.

Research on potential ground risk regions of aircraft crashes based on ADS-B flight tracking data and GIS

With the rapid development of the global aviation industry, the number of aircraft flying in the airspace has continuously increased. Although aviation safety has been improved in the last several decades, many general aviation and a few commercial aviation accidents occur every year, resulting in fatalities and significant economic loss. Aircraft crash accidents not only cause fatalities of crew members and passengers onboard, but also seriously affect people and property on the ground, especially if the crashed aircraft falls into dense urban areas. However, unlike emergencies caused by natural disasters such as floods, hurricanes, or a terrorist attack, very little research looked into the potential consequences of aviation accidents to people and property on the ground from the view of urban planning and emergency management. The object of this study is to propose a model for identifying potential ground risk areas of aviation crash accidents. Different from studies in existing literature, actual flight trajectories obtained from automatic dependent surveillance—broadcast (ADS-B) data was introduced in this study and incorporated in modeling development. With the trajectory information, a GIS density analysis method was applied to obtain a regional aircraft flight-path line density distribution map and to model crash trajectories of aircraft falling to the ground if a crash occurred or aircraft malfunctioned in the air. Combining relevant socio-economic factors that are sensitive to disasters, a ground potential risk mapping model for aircraft crashes was built. Risk areas were divided into five categories indicating the crash severities of potential aviation crash-caused impacts. To demonstrate the research approach, the State of Florida is used as an example. The outcomes of the proposed model can be used by emergency management departments to develop management plans for better responding to potential risks and provide decision support for city managers on zoning and land use planning.

A review of accidents & incidents on Boeing and Airbus commercial aircraft’s avionics-related system in two decades (1996-2015)

Aviation accidents still hit the news even though the growth of technological advancement on commercial aircraft avionic systems has been impressive. Hence, one of the objectives of this study is to plot the time-based graph of commercial aviation accidents, with direct consequence from avionics instrumentations in the period of two decades, from 1996 to 2015. The second objective is to analyse two main aircraft manufacturers, Boeing and Airbus, in determining specific model of its kind that significantly involved in avionics-related instrumentation as one of the contributing factors that leads to the incidents or accidents. The third objective is to identify which avionics system that most frequently involved in aviation incidents, for both manufacturers. The final objective is to examine the main probable cause that has the highest percentage in those accidents within the said time frame. The method of collecting data is by doing comparative analysis from reliable official websites of four well-known bodies such as National Transportation Safety Board (NTSB), Federal Aviation Administration (FAA), Aviation Safety Network and Flight Safety Foundation. Results show that misfortune occurrences are directly associated with avionics within the said two decades, which mainly involved Autopilot and Flight Management System (FMS) (14% each), meanwhile the aircraft model Boeing 737 carries the highest percentage of avionics-related incidents or accidents. Nonetheless, 67% of the misfortune occurrences within the scope of study are mainly due to human error instead of technology.

Pilot Mental Health, Negative Life Events, and Improving Safety with Peer Support and a Just Culture.

In the last 35 yr, 17 commercial aviation accidents and incidents, with 576 fatalities, could likely have been attributed to mental disease of a pilot. Screening tools for mental health risks in airline pilots are needed. There is growing interest in pilot peer-support programs and how to incorporate them in a just culture, meaning that pilots can report mental health complaints without a risk of job or income loss. We combined findings from aviation accidents and incidents with a search of scientific literature to provide data-based recommendations for screening, peer-support, and a just culture approach to mental health problems. Commercial aviation accidents and incidents in which a mental disorder of a pilot was thought to play a role were reviewed. Subsequently, PubMed and PsychInfo literature searches were performed on peer-support programs, just culture human resource management, and the risk of negative life events on developing suicidal ideation and behavior in comparable professional groups. Lethal accidents were mostly related to impaired coping with negative life events. Negative life events are clearly related to suicidal thoughts, attempts, and completed suicide. A protective effect of peer-support programs on mental health problems has not been established, although peer-support programs are generally appreciated by those involved. We did not find relevant literature on just culture. Negative life events are likely a useful screening tool for mental health risks. There is still a lack of evidence on how peer-support groups should be designed and how management of mental health risks can be implemented in a just culture.Mulder S, de Rooy D. Pilot mental health, negative life events, and improving safety with peer support and a just culture. Aerosp Med Hum Perform. 2018; 89(1):41-51.

Analysis of alerting system failures in commercial aviation accidents

The role of an alerting system is to make the system operator (e.g., pilot) aware of an impending hazard or unsafe state so the hazard can be avoided or managed successfully. A review of 46 commercial aviation accidents (between 1998 and 2014) revealed that, in the vast majority of events, either the hazard was not alerted or relevant hazard alerting occurred but failed to aid the flight crew sufficiently. For this set of events, alerting system failures were placed in one of five phases: Detection, Understanding, Action Selection, Prioritization, and Execution. This study also reviewed the evolution of alerting system schemes in commercial aviation, which revealed naïve assumptions about pilot reliability in monitoring flight path parameters; specifically, pilot monitoring was assumed to be more effective than it actually is. Examples are provided of the types of alerting system failures that have occurred, and recommendations are provided for alerting system improvements.

A systems perspective on the unstable approach in commercial aviation

Unstable approaches remain a significant contributory factor in commercial aviation accidents that occur during the approach and landing phase. A safe approach requires a carefully ordered sequence of changes to the configuration and speed of the aircraft in order to carry out a safe landing and criteria regarding configuration and speed must be met for an approach to be classified as stable. When an approach does not meet these criteria, often because of unexpected changes, the approach is classified as unstable and the risk of a landing accident or incident is greatly increased. Traditional accident models follow a linear path from cause to effect or describe a linear path through absent or weakened defences. A systems perspective attempts to understand failures by understanding successes under dynamic conditions. Pilots were interviewed about how they choose a particular configuration style during approaches and their reactions to influences that caused them to adapt their profile. Grounded theory method was used to uncover how pilots successfully manage to adapt their working practices in dynamic environments and why these adaptations sometimes fail. The grounded theory based on the data was that pilots must reconcile multiple goals, including those of outside agencies, and it is the success or failure of this reconciliation that determines the success or failure of the approach. The theory of multiple goal reconciliation formed the basis of recommendations to improve the safety of approach procedures, the key one being that a published speed profile would unify the goals of pilots and air traffic controllers, the sole aim then being to get the aircraft to particular positions at particular speeds.

Human Error and Commercial Aviation Accidents: An Analysis Using the Human Factors Analysis and Classification System

The aim of this study was to extend previous examinations of aviation accidents to include specific aircrew, environmental, supervisory, and organizational factors associated with two types of commercial aviation (air carrier and commuter/ on-demand) accidents using the Human Factors Analysis and Classification System (HFACS). HFACS is a theoretically based tool for investigating and analyzing human error associated with accidents and incidents. Previous research has shown that HFACS can be reliably used to identify human factors trends associated with military and general aviation accidents. Using data obtained from both the National Transportation Safety Board and the Federal Aviation Administration, 6 pilot-raters classified aircrew, supervisory, organizational, and environmental causal factors associated with 1020 commercial aviation accidents that occurred over a 13-year period. The majority of accident causal factors were attributed to aircrew and the environment, with decidedly fewer associated with supervisory and organizational causes. Comparisons were made between HFACS causal categories and traditional situational variables such as visual conditions, injury severity, and regional differences. These data will provide support for the continuation, modification, and/or development of interventions aimed at commercial aviation safety. HFACS provides a tool for assessing human factors associated with accidents and incidents.

Characterizing the severe turbulence environments associated with commercial aviation accidents. A real-time turbulence model (RTTM) designed for the operational prediction of hazardous aviation turbulence environments

In this paper, we will focus on the real-time prediction of environments that are predisposed to producing moderate-severe (hazardous) aviation turbulence. We will describe the numerical model and its postprocessing system that is designed for said prediction of environments predisposed to severe aviation turbulence as well as presenting numerous examples of its utility. The purpose of this paper is to demonstrate that simple hydrostatic precursor circulations organize regions of preferred wave breaking and turbulence at the nonhydrostatic scales of motion. This will be demonstrated with a hydrostatic numerical modeling system, which can be run in real time on a very inexpensive university computer workstation employing simple forecast indices. The forecast system is designed to efficiently support forecasters who are directing research aircraft to measure the environment immediately surrounding turbulence. The numerical model is MASS version 5.13, which is integrated over three different grid matrices in real-time on a university workstation in support of NASA-Langley’s B-757 turbulence research flight missions. The model horizontal resolutions are 60, 30, and 15 km and the grids are centered over the region of operational NASA-Langley B-757 turbulence flight missions. The postprocessing system includes several turbulence-related products including four turbulence forecasting indices, winds, streamlines, turbulence kinetic energy, and Richardson numbers. Additionally there are convective products including precipitation, cloud height, cloud mass fluxes, lifted index, and K-index. Furthermore, soundings, sounding parameters, and Froude number plots are also provided. The horizontal cross section plot products are provided from 16,000–46,000 feet in 2,000 feet intervals. Products are available every three hours at the 60 and 30 km grid interval and every 1.5 hours at the 15 km grid interval. The model is initialized from the NWS ETA analyses and integrated two times a day.

Organizational Factors in Commercial Aviation Accidents

In recent years, several major transportation accidents have brought significant attention to the role organizational factors play in motivating operator safety within high-risk systems, yet very little has been studied regarding the direct contribution organizational factors play in accidents. This study elucidates the types of organizational factors associated with aviation accidents attributed principally to pilot error, through case-based analyses of commercial accidents from 1990 to 2000. Results indicate inadequate procedures and directives rank highest among organizational problems. Findings suggest interventions aimed at organizational contributions may potentially ameliorate a myriad of systemic problems, rather than assigning blame to the pilot at the operational level.

Characterizing the severe turbulence environments associated with commercial aviation accidents. Part 1: A 44-case study synoptic observational analyses

In this paper, we describe the results of 44 case study analyses of synoptic scale data sets that define the atmospheric structure prior to the development of accident-producing turbulence. First, the 44 case studies are categorized as a function of the location, altitude, time of year, time of day, and turbulence environment, i.e., in clear air, cloudiness, convection, near mountains, or in the proximity of deep convection. It is noteworthy that this later category was much more ubiquitous than was anticipated. Second, NCEP Reanalysis data sets as well as both visible and infrared satellite imagery are employed to diagnose “predictor” fields associated with the synoptic-scale environment preceding severe turbulence. These predictor fields are calculated based on jet stream configuration, kinematic, dynamical, and thermodynamic analyses of the synoptic-scale atmosphere.

Characterizing the severe turbulence environments associated with commercial aviation accidents. Part 2: Hydrostatic mesoscale numerical simulations of supergradient wind flow and streamwise ageostrophic frontogenesis

Simulation experiments reveal key processes that organize a hydrostatic environment conducive to severe turbulence. The paradigm requires the juxtaposition of the entrance region of a curved jet streak, which is highly subgeostrophic, with the entrance region of a straight jet streak, which is highly supergeostrophic. The wind and mass fields become misphased as the entrance regions converge, resulting in significant spatial variation of inertial forcing, centripetal forcing, as well as along and cross-stream pressure gradient forcing over a meso-β scale region. Maxima of these forces are misphased where the two dissimilar jet streaks converge and geostrophic balance is disrupted. Velocity divergence within the subgeostrophic region of largest upstream-directed pressure gradient force and velocity convergence near the region of largest downstream-directed centripetal/inertial-advective forcing act to produce a mesoscale front due to spatially varying confluent flow flanked by zones of increasing velocity divergence. This results in frontogenesis as well as the along-stream divergence of cyclonic and convergence of cyclonic ageostrophic vertical vorticity. The nonuniform centripetally forced mesoscale front becomes the locus of large gradients of ageostrophic vertical vorticity along an overturning isentrope. This region becomes favorable for streamwise vorticity gradient formation enhancing the environment for the organization of horizontal vortex tubes in the presence of buoyant forcing. This is because the mesoscale convergence of vertical vorticity on an overturning isentropic surface creates vertical rotation for the development of horizontal vorticity in regions where isentropic surfaces overturn. Vorticity, shear, and buoyancy are focused in one location by this front thus favoring an environment favorable for microvortex formation leading to turbulence.

Synthetic Vision CFIT Experiments for GA and Commercial Aircraft: “A Picture is Worth a Thousand Lives”

Because restricted visibility has been implicated in the majority of commercial and general aviation accidents, solutions will need to focus on how to enhance safety during instrument meteorological conditions (IMC). The NASA Synthetic Vision Systems (SVS) project is developing technologies to help achieve these goals through the synthetic presentation of how the outside world would look to the pilot if vision were not reduced. The potential safety outcome would be a significant reduction in several accident categories, such as controlled-flight-into-terrain (CFIT), that have restricted visibility as a causal factor. The paper describes two experiments that demonstrated the efficacy of synthetic vision technology to prevent CFIT accidents for both general aviation and commercial aircraft.

Are pilots at risk of accidents due to fatigue?

Problem: There is concern in the aviation community that pilot schedules can lead to fatigue and increased chance of an aviation accident. Yet despite this concern, there is little empirical analysis showing the relationship between pilot schedules and commercial aviation accidents. This study attempts to demonstrate an empirical relationship between pilot schedules and aviation accidents. Method: Data for human factors-related accidents and pilot work patterns were identified. The distribution of pilot work schedule parameters for the accidents was compared to that for all pilots using a chi-square test to determine if the proportions of accidents and length of duty exposure were the same. If the distributions are the same, then one could infer that pilot human factor accidents are not affected by work schedule parameters. Results: The proportion of accidents associated with pilots having longer duty periods is higher than the proportion of longer duty periods for all pilots. Discussion: There is a discernible pattern of increased probability of an accident as duty time increases for commercial aircraft pilots in the United States. Impact on Industry: The analysis suggests that establishing limits on duty time for commercial pilots would reduce risk. Such a rule is likely to be expensive and could substantially impact the commercial airlines. In return, there is likely to be a reduction in the risk of commercial aviation accidents due to pilot fatigue.