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EMS helicopter incidents reported to the NASA Aviation Safety Reporting System

The objectives of this evaluation were to: Identify the types of safety-related incidents reported to the Aviation Safety Reporting System (ASRS) in Emergency Medical Service (EMS) helicopter operations; Describe the operational conditions surrounding these incidents, such as weather, airspace, flight phase, time of day; and Assess the contribution to these incidents of selected human factors considerations, such as communication, distraction, time pressure, workload, and flight/duty impact.

Connell, Linda J.↗

A Practical Guide to Interpretation of Large Collections of Incident Narratives Using the QUORUM Method

Analysis of incident reports plays an important role in aviation safety. Typically, a narrative description, written by a participant, is a central part of an incident report. Because there are so many reports, and the narratives contain so much detail, it can be difficult to efficiently and effectively recognize patterns among them. Recognizing and addressing recurring problems, however, is vital to continuing safety in commercial aviation operations. A practical way to interpret large collections of incident narratives is to apply the QUORUM method of text analysis, modeling, and relevance ranking. In this paper, QUORUM text analysis and modeling are surveyed, and QUORUM relevance ranking is described in detail with many examples. The examples are based on several large collections of reports from the Aviation Safety Reporting System (ASRS) database, and a collection of news stories describing the disaster of TWA Flight 800, the Boeing 747 which exploded in mid- air and crashed near Long Island, New York, on July 17, 1996. Reader familiarity with this disaster should make the relevance-ranking examples more understandable. The ASRS examples illustrate the practical application of QUORUM relevance ranking.

McGreevy, Michael W.↗

Cross-Cultural Barriers to Effective Communication in Aviation

Recent research on communication and performance in airline flight crews has led to a concept of shared mental models that is associated with effective, efficient team coordination in problem solving and decision making situations. Elements that characterize efficient communication have been identified. This research, however, was based strictly on US crews. More recent studies supported by NASA have identified cultural factors that influence communication among team members who vary in their status and roles. Research is just beginning to identify commonalities and culturally distinct strategies for accomplishing joint tasks. ASRS incident reports have been analyzed to identify language barriers in flight that have safety consequences. Implications of these concepts and findings for multi-cultural command and control will be explored.

Orasanu, Judith↗

Identification of Error Patterns in Terminal-Area ATC Communications

Advancing air traffic management technologies have enabled a greater number of aircraft to use the same airspace more effectively. As aircraft separations are reduced and final approaches are more finely timed, there is less room for error. The present study examined 122 terminal-area, loss-of-separation and procedure violation incidents reported to the Aviation Safety Reporting System (ASRS) by air traffic controllers. Narrative description codes were used for the incidents for type of violation, contributing factors, recovery strategies, and consequences. Usually multiple errors occurred prior to the violation. Error sequences were analyzed and common patterns of errors were identified. In half of the incidents, errors were noticed in time to correct mistakes. Of these, almost 43% committed additional errors during the recovery attempt. This analysis shows that redundancies in the present air traffic control system may not be sufficient to support large increases in traffic density. Error prevention and design considerations for air traffic management systems are discussed.

Quinn, Cheryl↗

Human Factors Considerations for Area Navigation Departure and Arrival Procedures

Area navigation (RNAV) procedures are being implemented in the United States and around the world as part of a transition to a performance-based navigation system. These procedures are providing significant benefits and have also caused some human factors issues to emerge. Under sponsorship from the Federal Aviation Administration (FAA), the National Aeronautics and Space Administration (NASA) has undertaken a project to document RNAV-related human factors issues and propose areas for further consideration. The component focusing on RNAV Departure and Arrival Procedures involved discussions with expert users, a literature review, and a focused review of the NASA Aviation Safety Reporting System (ASRS) database. Issues were found to include aspects of air traffic control and airline procedures, aircraft systems, and procedure design. Major findings suggest the need for specific instrument procedure design guidelines that consider the effects of human performance. Ongoing industry and government activities to address air-ground communication terminology, design improvements, and chart-database commonality are strongly encouraged. A review of factors contributing to RNAV in-service errors would likely lead to improved system design and operational performance.

Barhydt, Richard↗

Causal Factors and Adverse Conditions of Aviation Accidents and Incidents Related to Integrated Resilient Aircraft Control

The causal factors of accidents from the National Transportation Safety Board (NTSB) database and incidents from the Federal Aviation Administration (FAA) database associated with loss of control (LOC) were examined for four types of operations (i.e., Federal Aviation Regulation Part 121, Part 135 Scheduled, Part 135 Nonscheduled, and Part 91) for the years 1988 to 2004. In-flight LOC is a serious aviation problem. Well over half of the LOC accidents included at least one fatality (80 percent in Part 121), and roughly half of all aviation fatalities in the studied time period occurred in conjunction with LOC. An adverse events table was updated to provide focus to the technology validation strategy of the Integrated Resilient Aircraft Control (IRAC) Project. The table contains three types of adverse conditions: failure, damage, and upset. Thirteen different adverse condition subtypes were gleaned from the Aviation Safety Reporting System (ASRS), the FAA Accident and Incident database, and the NTSB database. The severity and frequency of the damage conditions, initial test conditions, and milestones references are also provided.

Reveley, Mary S.↗

Causal Factors and Adverse Events of Aviation Accidents and Incidents Related to Integrated Vehicle Health Management

Causal factors in aviation accidents and incidents related to system/component failure/malfunction (SCFM) were examined for Federal Aviation Regulation Parts 121 and 135 operations to establish future requirements for the NASA Aviation Safety Program s Integrated Vehicle Health Management (IVHM) Project. Data analyzed includes National Transportation Safety Board (NSTB) accident data (1988 to 2003), Federal Aviation Administration (FAA) incident data (1988 to 2003), and Aviation Safety Reporting System (ASRS) incident data (1993 to 2008). Failure modes and effects analyses were examined to identify possible modes of SCFM. A table of potential adverse conditions was developed to help evaluate IVHM research technologies. Tables present details of specific SCFM for the incidents and accidents. Of the 370 NTSB accidents affected by SCFM, 48 percent involved the engine or fuel system, and 31 percent involved landing gear or hydraulic failure and malfunctions. A total of 35 percent of all SCFM accidents were caused by improper maintenance. Of the 7732 FAA database incidents affected by SCFM, 33 percent involved landing gear or hydraulics, and 33 percent involved the engine and fuel system. The most frequent SCFM found in ASRS were turbine engine, pressurization system, hydraulic main system, flight management system/flight management computer, and engine. Because the IVHM Project does not address maintenance issues, and landing gear and hydraulic systems accidents are usually not fatal, the focus of research should be those SCFMs that occur in the engine/fuel and flight control/structures systems as well as power systems.

Reveley, Mary S.↗

Analysis of Aviation Safety Reporting System Incident Data Associated with the Technical Challenges of the Atmospheric Environment Safety Technology Project

This study analyzed aircraft incidents in the NASA Aviation Safety Reporting System (ASRS) that apply to two of the three technical challenges (TCs) in NASA's Aviation Safety Program's Atmospheric Environment Safety Technology Project. The aircraft incidents are related to airframe icing and atmospheric hazards TCs. The study reviewed incidents that listed their primary problem as weather or environment-nonweather between 1994 and 2011 for aircraft defined by Federal Aviation Regulations (FAR) Parts 121, 135, and 91. The study investigated the phases of flight, a variety of anomalies, flight conditions, and incidents by FAR part, along with other categories. The first part of the analysis focused on airframe-icing-related incidents and found 275 incidents out of 3526 weather-related incidents over the 18-yr period. The second portion of the study focused on atmospheric hazards and found 4647 incidents over the same time period. Atmospheric hazards-related incidents included a range of conditions from clear air turbulence and wake vortex, to controlled flight toward terrain, ground encounters, and incursions.

Withrow, Colleen A.↗

Identification of Vehicle Health Assurance Related Trends

Trend analysis in aviation as related to vehicle health management (VHM) was performed by reviewing the most current statistical and prognostics data available from the National Transportation Safety Board (NTSB) accident, the Federal Aviation Administration (FAA) incident, and the NASA Aviation Safety Reporting System (ASRS) incident datasets. In addition, future directions in aviation technology related to VHM research areas were assessed through the Commercial Aviation Safety Team (CAST) Safety Enhancements Reserved for Future Implementations (SERFIs), the National Transportation Safety Board (NTSB) Most-Wanted List and recent open safety recommendations, the National Research Council (NRC) Decadal Survey of Civil Aeronautics, and the Future Aviation Safety Team (FAST) areas of change. Future research direction in the VHM research areas is evidently strong as seen from recent research solicitations from the Naval Air Systems Command (NAVAIR), and VHM-related technologies actively being developed by aviation industry leaders, including GE, Boeing, Airbus, and UTC Aerospace Systems. Given the highly complex VHM systems, modifications can be made in the future so that the Vehicle Systems Safety Technology Project (VSST) technical challenges address inadequate maintenance crew's trainings and skills, and the certification methods of such systems as recommended by the NTSB, NRC, and FAST areas of change.

Phojanamongkolkij, Nipa↗

Analysis of Aviation Safety Reporting System Incident Data Associated With the Technical Challenges of the Vehicle Systems Safety Technology Project

This analysis was conducted to support the Vehicle Systems Safety Technology (VSST) Project of the Aviation Safety Program (AVsP) milestone VSST4.2.1.01, "Identification of VSST-Related Trends." In particular, this is a review of incident data from the NASA Aviation Safety Reporting System (ASRS). The following three VSST-related technical challenges (TCs) were the focus of the incidents searched in the ASRS database: (1) Vechicle health assurance, (2) Effective crew-system interactions and decisions in all conditions; and (3) Aircraft loss of control prevention, mitigation, and recovery.

Withrow, Colleen A.↗

Analysis of Aviation Safety Reporting System Incident Data Associated with the Technical Challenges of the System-Wide Safety and Assurance Technologies Project

The Aviation Safety Program (AvSP) System-Wide Safety and Assurance Technologies (SSAT) Project asked the AvSP Systems and Portfolio Analysis Team to identify SSAT-related trends. SSAT had four technical challenges: advance safety assurance to enable deployment of NextGen systems; automated discovery of precursors to aviation safety incidents; increasing safety of human-automation interaction by incorporating human performance, and prognostic algorithm design for safety assurance. This report reviews incident data from the NASA Aviation Safety Reporting System (ASRS) for system-component-failure- or-malfunction- (SCFM-) related and human-factor-related incidents for commercial or cargo air carriers (Part 121), commuter airlines (Part 135), and general aviation (Part 91). The data was analyzed by Federal Aviation Regulations (FAR) part, phase of flight, SCFM category, human factor category, and a variety of anomalies and results. There were 38 894 SCFM-related incidents and 83 478 human-factorrelated incidents analyzed between January 1993 and April 2011.

Withrow, Colleen A.↗

Assessing Several Non-Traditional Data Sources for Value in Aviation Safety

The NASA System-Wide Safety (SWS) project and its predecessor projects have been developing Machine Learning (ML) algorithms for commercial aviation safety for many years. These algorithms have been applied to Flight Operations Quality Assurance (FOQA); radar track data (e.g., Threaded Track); and safety reports, including Aviation Safety Reporting System (ASRS) and Aviation Safety Action Plan (ASAP). SWS is working with partners to get access to other data that air carriers provide, such as maintenance data, and has been assisting carriers in working with other data, such as Line Operations Safety Audit (LOSA) data, using manual methods. However, the project has discussed whether there are other data that are not traditionally used in aviation safety analysis that may be useful. This paper discusses four sets of data and models that are not traditionally used in aviation safety but that have shown promise for such use. In the future, we plan to incorporate such data into ML algorithms to use with data that we have used before and determine the additional benefit that is actually achieved under different contexts from the inclusion of these non-traditional data sources.

Nikunj C. Oza↗

BERT-Based Topic Modeling and Information Retrieval to Support Fishbone Diagramming for Safe Integration of Unmanned Aircraft Systems in Wildfire Response

Recent concepts for emerging wildfire response operations have included unmanned aircraft systems (UAS) due to their increasing accessibility and capabilities. To integrate UAS into wildfire response safely, researchers have studied the use of large repositories of historic incident reports to improve the scope of root cause analysis. Recent work has emphasized applying state-of-the-art natural language processing techniques to extract useful information from these repositories. However, it has not yet been studied how these results can be interpreted and integrated into the systems engineering process. In this work, we propose a process in which Bidirectional Encoder Representations from Transformers (BERT)-based topic modeling and information retrieval are applied to a relevant set of documents in order to support the development of a fishbone diagram in a semiautomated process. High-level themes in the document set are identified using topic modeling, which are then refined and interpreted by a human analyst. Then, the themes are used to guide a finer search using information retrieval, which returns specific incident reports of relevance. This provides traceability to specific incidents as well as broader categorizations that comprise the fishbone branches. We apply the proposed process to relevant documents from NASA’s Aviation Safety Reporting System (ASRS). The proposed process is widely applicable when relevant documents are available, and the results from this study will be useful to identifying potential causes of wildfire response UAS incidents.

Hazard analysis↗

BERT-based Topic Modeling and Information Retrieval to Support Fishbone Diagramming for Safe Integration of Unmanned Aircraft Systems in Wildfire Response

Recent concepts for emerging wildfire response operations have included unmanned aircraft systems (UAS) due to their increasing accessibility and capabilities. To integrate UAS into wildfire response safely, researchers have studied the use of large repositories of historic incident reports to improve the scope of root cause analysis. Recent work has emphasized applying state-of-the-art natural language processing techniques to extract useful information from these repositories. However, it has not yet been studied how these results can be interpreted and integrated into the systems engineering process. In this work, we propose a process in which Bidirectional Encoder Representations from Transformers (BERT)-based topic modeling and information retrieval are applied to a relevant set of documents in order to support the development of a fishbone diagram in a semiautomated process. High-level themes in the document set are identified using topic modeling, which are then refined and interpreted by a human analyst. Then, the themes are used to guide a finer search using information retrieval, which returns specific incident reports of relevance. This provides traceability to specific incidents as well as broader categorizations that comprise the fishbone branches. We apply the proposed process to relevant documents from NASA’s Aviation Safety Reporting System (ASRS). The proposed process is widely applicable when relevant documents are available, and the results from this study will be useful to identifying potential causes of wildfire response UAS incidents.

hazard analysis↗

Testing of Advanced Capabilities to Enable In-time Safety Management and Assurance for Future Flight Operations

In order to refine an initial Concept of Operations, explore Concepts of Use, and expose/validate requirements for future In-Time Aviation Safety Management Systems (IASMS), testing architectures were created, along with a set of capabilities and underlying information exchange protocols. These systems were conceived and developed based on hazards associated with two envisioned urban area flight domains: (1) highly autonomous small uncrewed aerial systems (sUAS) operating at low altitudes, and (2) highly autonomous air taxis. The initial scope of this development is described in [1]; this report provides an update, focusing on the subsequent developments and test activities. As stated in [1], it is important to note that there are many capabilities already in use by the industry (or soon to be in use) that will play critical roles in future IASMS designs. Those reported here were developed to address a gap in the current state-of-the-art regarding specific hazards/risks, and/or to allow for investigation of the interplay between and across hazard types — particularly regarding how overall safety risk can be reduced or managed effectively. Results of testing and development activities are organized by the operational phase wherein a particular capability would be employed (i.e., preflight, in-flight, and post-flight/off-line). Pre-flight: A set of capabilities were developed to help mitigate safety risk prior to flight (e.g., during flight and mission planning). Results of testing summarize (1) validation activities to raise the Technology Readiness Level (TRL) and (2) evaluation activities where the capabilities were applied to flight/mission planning procedures and used by operators/pilots. For the latter, flight plans were automatically assessed, and operators/pilots were notified of hazardous flight segments so as to enable adjustment of the flight plan and re-evaluation, and/or to better inform go/no-go decisions. Capabilities addressed hazards associated with power consumption, third-party risk, wind, navigation system performance, radiofrequency interference, and proximity to geo-spatial threats (e.g., buildings, trees, and no-fly zones). In-flight: Flight experiments tested capabilities that detect and respond to hazards encountered during flight. In the first series, safety hazards were monitored and assessed onboard, and system-generated mitigation maneuvers were recorded (but not acted upon by the vehicle). In the second series, mitigation maneuver commands directed the aircraft in response to safety hazards (i.e., auto-mitigation). The sUAS used for testing is described in full, as is the test architecture, which included commercial avionics, research avionics, and onboard software designed to detect, assess, and respond to hazards. The onboard system was designed as a run-time assurance framework, consistent with [2] and supportive of both supervisory and automated modes. The primary functions included: real-time risk assessment (RTRA), auto-pilot monitoring, constraint monitoring, and contingency select/triggering. RTRA performs integrated risk assessment considering data from several hazard-related monitors (e.g., battery, motors, navigation, communications, population density, and loss-of-control). Post-flight/off-line: Data monitored and recorded during flights can enable IASMS capabilities that execute after flights have completed (or “off-line”). These include: (1) the ability to identify anomalies and trends that may only be observable when comparing data spanning a number of similar flights; (2) the ability to update and validate pre-flight and in-flight capabilities and any underlying models to improve their performance; (3) the ability to report anomalies/off-nominals that may indicate design changes or maintenance actions are needed; and (4) the ability for humans involved in operations to report safety-relevant observations to help in understanding the flight data and/or the operational context of a flight. Progress on three such capabilities is summarized; the first investigates anomaly detection given a limited set of flight logs and applies an approach previously used for space operations. The second explores what could be identified using a larger set of flight logs, including from web-based forums where flight logs are posted by sUAS autopilot users. The third creates a new means of collecting information on UAS incidents and accidents via the Aviation Safety Reporting System (ASRS).

sUAS↗

BERT-based Topic Modeling and Information Retrieval to Support Fishbone Diagramming for Safe Integration of Unmanned Aircraft Systems in Wildfire Response

Recent concepts for emerging wildfire response operations have included unmanned aircraft systems (UAS) due to their increasing accessibility and capabilities. To integrate UAS into wildfire response safely, researchers have studied the use of large repositories of historic incident reports to improve the scope of root cause analysis. Recent work has emphasized applying state-of-the-art natural language processing techniques to extract useful information from these repositories. However, it has not yet been studied how these results can be interpreted and integrated into the systems engineering process. In this work, we propose a process in which Bidirectional Encoder Representations from Transformers (BERT)-based topic modeling and information retrieval are applied to a relevant set of documents in order to support the development of a fishbone diagram in a semiautomated process. High-level themes in the document set are identified using topic modeling, which are then refined and interpreted by a human analyst. Then, the themes are used to guide a finer search using information retrieval, which returns specific incident reports of relevance. This provides traceability to specific incidents as well as broader categorizations that comprise the fishbone branches. We apply the proposed process to relevant documents from NASA’s Aviation Safety Reporting System (ASRS). The proposed process is widely applicable when relevant documents are available, and the results from this study will be useful to identifying potential causes of wildfire response UAS incidents.

hazard analysis↗

Perceive: Proactive Exploration of Risky Concept Emergence for Identifying Vulnerabilities & Exposures

National databases that collect various kinds of textual threat reports such as ASRS, CERT, and NVD manually process their reports individually. They then offer data products to disseminate the aggregate information, like newsletters, alerts or individual report searching. The goal of this research is to connect these individual reports thematically and temporally to identify emerging or recurring threats, by analyzing large collections of text, source code, collaboration and communication patterns. This capability, I argue, enables us to identify the emergence and recurrence of such themes, and the contexts in which they re-occur, facilitating faster and more capable mitigation. I propose two models to shed light on this goal: An empirical model of vulnerabilities as bugs, the commit flow model, and one of the vulnerabilities and aviation safety threats as topics, the topic flow model. I use as gold standard existing manual workflows in both domains, reflected in the existing data products by these organizations, and empirically evaluate if the automated model scan match or outperform existing manual practices.

ASRS↗

What ASRS incident data tell about flight crew performance during aircraft malfunctions

This research examined 230 reports in NASA's Aviation Safety Reporting System's (ASRS) database to develop a better understanding of factors that can affect flight crew performance when crew are faced with inflight aircraft malfunctions. Each report was placed into one of two categories, based on severity of the malfunction. Report analysis was then conducted to extract information regarding crew procedural issues, crew communications and situational awareness. A comparison of these crew factors across malfunction type was then performed. This comparison revealed a significant difference in ways that crews dealt with serious malfunctions compared to less serious malfunctions. The authors offer recommendations toward improving crew performance when faced with inflight aircraft malfunctions.

Sumwalt, Robert L.↗