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NASA NTRS2023

SafeAeroBERT: Towards a Safety-Informed Aerospace-Specific Language Model

As aviation systems continue to operate with high traffic, large amounts of documents containing safety-relevant data continue to be generated via reporting systems such as the ASRS. Advanced natural language processing techniques, specifically pre-trained language models, have shown great success in domain-specific applications; however, the text in aviation safety reports is inundated with jargon and thus not fully utilized by general pre-trained models. In this research, we work towards developing a safety-informed aerospace-specific language model by pre-training a Bidirectional Encoder Representations from Transformer (BERT) model on reports from the Aviation Safety Reporting System and the National Transportation Safety Board. The resulting model, called SafeAeroBERT, is fine-tuned for the specific task of document classification, and can be further tuned for named-entity recognition, relation detection, information retrieval, and summarization. Results from the classification task are compared between SafeAeroBERT, the base BERT, and SciBERT models and show SafeAeroBERT outperforms the general BERT and SciBERT on classifying reports about human factors, aircraft, and procedure. SafeAeroBERT can be used on custom tasks, not limited to document classification, and is intended to aid an intelligent knowledge manager for safety report repositories.

Aviation↗
NASA NTRS1997

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.↗
NASA NTRS1996

Cross-Cultural Barriers to Effective Communication in Aviation

Communication is essential to safe flight, as evidenced by several accidents in which crew communicates was found to have contributed to the accidents. This chapter documents the essential role of explicit efficient communication to flight safety with a global context. It addresses communication between flight crews and air traffic controllers in regions a the world where pilots and controllers speak different native languages, as well as cases in which crew members within the flight deck represent different native languages and cultures. It also addresses problems associated with "exporting" crew resource management training programs to parts of the world which values and norms differ from those of the United States, where these programs were initially developed. This chapter is organized around several central questions: (1) What are various kinds of communication failures and what are their consequences; (2) What are the causes of communication failure; (3) What are features of effective crew communication; (4) What can be done to enhance communication success? To explore a wider range of communication failures than available from accident reports, we examined a set of incident reports from the Aviation Safety Reporting System. These could be classified into three major categories: those in which language actually interfered with transmission of a message; those in which transmission was adequate but the context was not expressed unambiguously and thus the message received was not the same as the message intended; and those in which the message was received as intended, but was not adequately understood or acted upon, mainly because of cultural factors. The consequences of failed communication can be flight errors (such as when a clearance is not received correctly), loss of situation awareness, or failure of crew members (or ATC and pilots) to build a shared understanding of a situation. Causes of misunderstanding can be traced to a number of sources, often grounded in faulty assumptions held by one or both parties to a conversation. Speakers and listeners often experience "illusionary understanding" in which they think they understand each other, but in fact do not. While this problem can exist within a single culture, it is much more serious across cultures. Training in effective explicit communication is a component of Crew Resource Management training programs developed in the U.S. These programs are being adopted by airlines around the world, with varying degrees of success. The level of success in part depends on how similar the conversational and social styles of those cultures are to those of the U.S. A factor that influences conversational style is a culture's relative positioned on two major dimensions that distinguish national cultural groups: individualism vs. collectivism and degree of power distance. The chapter concludes with a discussion of techniques for overcoming the various classes of communication failures and for effectively adapting training programs to fit the values and norms of cultures around the globe.

Fischer, U.↗
NASA NTRS2010

Correlated Topics in a Scalable Multidimensional Text Cube: Algorithms and Aviation Safety Case Study

As world-wide air traffic continues to grow even at a modest pace, the overall complexity of the system will increase significantly. This increased complexity can lead to a larger number of fatalities per year even if the extremely low fatality rate that we currently enjoy is maintained. One important source of information about the safety of the aviation system is in Aviation Safety Text Reports which are written by members of the flight crew, air traffic controllers, and other parties involved with the aviation system. These anonymized narrative reports contain fixed-field contextual information about the flight but also contain free-form narratives that describe, in the author s own words, the nature of the safety incident and, in many cases, the contributing factors that led to the safety incident. Several thousand such reports are filed each month, each of which is read and analyzed by highly trained experts. However, it is possible that there are emerging safety issues due to the fact that they may be reported very infrequently and in different contexts with different descriptions. The goal of this research paper is to develop correlated topic models which uncover correlations in the subspaces defined by the intersection of numerous fixed fields and discovered correlated topics. This task requires the discovery of latent topics in the text reports and the creation of a topic cube. Furthermore, because the number of potential cells in the topic cube is very large, we discuss novel methods of pruning the search space in the topic cells, thereby making the analysis feasible. We demonstrate the new algorithms on an analysis of pilot fatigue and its contributing factors, as well as the safety incidents that are correlated with this phenomenon.

Zhao, Bo↗
NASA NTRS2021

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↗
NASA NTRS2014

Coordination Between Sectors in Shared Airspace Operations

Recent studies have shown that a more efficient use of airspace may involve shared airspace operations, i.e., temporal as well as spatial separation of arrival and departure flows [1][2]. Temporal separation would permit a departure aircraft to fly through an arrival flow, depending on an available gap. This would necessitate careful and precise coordination between controllers in different sectors. Three methods of coordination which permit the penetration of a controller's airspace by another controller's aircraft are described: point out, look-and-go, and prearranged coordination procedure. Requirements of each method are given, along with associated problems that have surfaced in the field as described by Aviation Safety and Reporting System (ASRS) and other reports. A Human-in-the-Loop simulation was designed to compare two of the methods: point out and prearranged coordination procedures. In prearranged coordination procedures (P-ACP), the controllers control an aircraft in another controller's airspace according to specified prearranged procedures, without coordinating each individual aircraft with another controller, as is done with point outs. In the simulation, three experienced controllers rotated through two arrival sectors and a non-involved arrival sector of a Terminal Radar Approach Control (TRACON) airspace. Results of eighteen one-hour simulation runs (nine in each of the two conditions) showed no impact of the coordination method on separation violations nor on arrival times for 208 departing aircraft crossing an arrival stream. Participant assessment indicated that although both coordination conditions were acceptable, the prearranged coordination procedure condition was slightly safer, more efficient, timely, and overall, worked better operationally. Problems arose in the point out condition regarding controllers noticing acceptance of point outs. Also, in about half of the point-out runs, time pressure was felt to have had an impact on when and if the departures could cross an arrival stream. An additional problem with point outs may be confusion in the field about which controller has responsibility for separating point-out aircraft from other aircraft.

Parke, Bonny↗
NASA NTRS2007

Air Data Report Improves Flight Safety

NASA's Aviation Safety Program in the NASA Aeronautics Research Mission Directorate, which seeks to make aviation safer by developing tools for flight data analysis and interpretation and then by transferring these tools to the aviation industry, sponsored the development of Morning Report software. The software, created at Ames Research Center with the assistance of the Pacific Northwest National Laboratory, seeks to detect atypicalities without any predefined parameters-it spots deviations and highlights them. In 2004, Sagem Avionics Inc. entered a licensing agreement with NASA for the commercialization of the Morning Report software, and also licensed the NASA Aviation Data Integration System (ADIS) tool, which allows for the integration of data from disparate sources into the flight data analysis process. Sagem Avionics incorporated the Morning Report tool into its AGS product, a comprehensive flight operations monitoring system that helps users detect irregular or divergent practices, technical flaws, and problems that might develop when aircraft operate outside of normal procedures. Sagem developed AGS in collaboration with airlines, so that the system takes into account their technical evolutions and needs, and each airline is able to easily perform specific treatments and to build its own flight data analysis system. Further, the AGS is designed to support any aircraft and flight data recorders.

Source record↗
NASA NTRS2024

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↗
NASA NTRS2019

The Role of Alerting System Failures in Loss of Control Accidents CAST SE-210 Output 2

This report is part of a series of reports that address flight deck design and evaluation, written as a response to loss of control accidents. In particular, this activity is directed at failures in airplane state awareness in which the pilot loses awareness of the airplane's energy state or attitude and enters an upset condition. In a report by the Commercial Aviation Safety Team, an analysis of accidents and incidents related to loss of airplane state awareness determined that hazard alerting was not effective in producing the appropriate pilot response to a hazard (CAST, 2014). In the current report, we take a detailed look at 28 airplane state awareness accidents and incidents to determine how well the hazard alerting worked. We describe a five-step integrated alerting-to-recovery sequence that prescribes how hazard alerting should lead to effective flight crew actions for managing the hazard. Then, for each hazard in each of the 28 events, we determine if that sequence failed and, if so, how it failed. The results show that there was an alerting failure in every one of the 28 safety events, and that the most frequent failure (20/28) was tied to the flight crew not orienting to (not being aware of) the hazard. The discussion section summarizes findings and identifies alerting issues that are being addressed and issues that are not currently being addressed. We identify a few recent upgrades that have addressed certain alerting failures. Two of these upgrades address alerting design, but one response to the safety events is to upgrade training for approach to stall and stall recovery. We also describe issues that are not being addressed adequately: better alert integration for flight path management types of hazards, airplanes in the fleet that do not meet the current alerting regulations, a lack of innovation for addressing cases of channelized attention, and existing vulnerabilities in managing data validity.

aviation safety↗
NASA NTRS2007

Preliminary Evaluation of an Aviation Safety Thesaurus' Utility for Enhancing Automated Processing of Incident Reports

This document presents a preliminary evaluation the utility of the FAA Safety Analytics Thesaurus (SAT) utility in enhancing automated document processing applications under development at NASA Ames Research Center (ARC). Current development efforts at ARC are described, including overviews of the statistical machine learning techniques that have been investigated. An analysis of opportunities for applying thesaurus knowledge to improving algorithm performance is then presented.

Barrientos, Francesca↗
NASA NTRSDate not supplied

An Approach for Defining IASMS Services, Functions, and Capabilities

Assuring safety in the NAS with the inclusion of new entrants, such as Advanced Air Mobility (AAM), will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using autonomous vehicles. The focus of the In-time Aviation Safety Management System (IASMS) is to overcome AAM’s safety assurance challenges. The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs) designed to manage operational risks, identify unknown risks, and inform system designs. This paper describes an approach for defining SFCs based on technology trends in research, assessment of known and unknown risks in voluntary safety reports, and causal and contributing factors in aviation accidents and incidents. This approach would identify potential SFCs that further expand the Monitor, Assess, and Mitigate (M-A-M) functionality that represents the enabling framework of the IASMS. Safety implications that will result from integration of AAM in the transformation of the National Airspace System (NAS) were addressed in National Academies committees reports on AAM and IASMS. Development of a ConOps for IASMS was a top recommendation and can be represented as a reframing of safety assurance that builds on real-time alerting such as the Traffic Alert and Collision Avoidance System, and adds the more encompassing in-time temporal parameter in recognition of the different timelines for collecting and assessing safety data for risk mitigations. For example, mining for safety trends from data sources such as the Aviation Safety Information Analysis and Sharing system occurs over a longer time period. Research on AAM operations poses that SFCs can be designed to monitor the safety margin appropriate for AAM including with regards to the distance between current flight parameters and nominal ideal conditions. These in-time comparisons will become more complex as the density of operations increases at least in certain areas and can include planned and actual 4D trajectory, and in-time comparisons having implications on conflict modeling and prediction including expected and actual departure time, fix/waypoint crossing times, and arrival time. These comparisons would be integrated as part of SFCs that redefine and inform new safety margin. An increased safety margin improves management of operational risks while reducing the potential for anomalies. An increased safety margin also has implications for operator confidence in the certainty of its operations and trust in automation. Technology trends in research could be used to refine existing SFCs and define needs for additional SFCs that provide safety improvements to the design and operation of vehicles, airspace design, and operator performance requirements. NASA is developing innovative approaches to safeguard against major accidents and incidents that have occurred in the NAS and those anticipated with the inclusion of envisioned AAM operations. The innovations use operational performance data to monitor, detect, and predict flight variations exceeding safe nominal patterns, such as would be caused by navigational error, severe weather complications, or hijacking of UAS controls. These innovative approaches have high potential to prevent accidents and incidents in the new AAM era. It is anticipated that elements of the innovations will evolve into SFCs for the IASMS. Voluntary safety reports can be monitored to identify anomalies related to design or operational performance risks. Reports could be periodically monitored and assessed for specific topics. Reports might serve as weak signals or precursors indicative of emergent risk such as when combined with other safety information. The architecture could include SFCs that are based on voluntary safety reports recognizing the periodic temporal nature of data analysis. As previously mentioned, aviation accidents with their causal and contributing precursors can inform the need for SFCs in the IASMS. Accidents and incidents at San Francisco International Airport such as Asiana 214 and Air Canada 759 illustrate how combinations of different factors lead to increased risk. These types of precursors and different factors have implications on the types of SFCs that could be needed to monitor and manage different sources and types of design and operational risk. Continuing to assure the safety of AAM as designs and operations gain in complexity can be accompanied by defining SFCs that also increase in complexity. These SFCs can leverage information from findings and recommendations synthesized across on-going research, voluntary safety reports, and accident and incident reports. These SFCs can serve to refine accuracy of algorithms and resolve limitations with current practices. The IASMS architecture represents the framework for the SFCs and their critical role in safety assurance.

In-Time Aviation Safety Management System↗
NASA NTRS2001

A Synthetic Vision Preliminary Integrated Safety Analysis

This report documents efforts to analyze a sample of aviation safety programs, using the LMI-developed integrated safety analysis tool to determine the change in system risk resulting from Aviation Safety Program (AvSP) technology implementation. Specifically, we have worked to modify existing system safety tools to address the safety impact of synthetic vision (SV) technology. Safety metrics include reliability, availability, and resultant hazard. This analysis of SV technology is intended to be part of a larger effort to develop a model that is capable of "providing further support to the product design and development team as additional information becomes available". The reliability analysis portion of the effort is complete and is fully documented in this report. The simulation analysis is still underway; it will be documented in a subsequent report. The specific goal of this effort is to apply the integrated safety analysis to SV technology. This report also contains a brief discussion of data necessary to expand the human performance capability of the model, as well as a discussion of human behavior and its implications for system risk assessment in this modeling environment.

Hemm, Robert↗
NASA NTRS2019

A Summary of Results from Technologies for Aircraft State Awareness Safety Enhancement 210 Output 2

In 2014, the Commercial Aviation Safety Team produced a report describing the results of an analysis intended to understand and mitigate airplane incidents and accidents associated with flight crew loss of attitude or energy state awareness. That report described several "Safety Enhancements" including a new category of "Research Safety Enhancements". This paper focuses on Safety Enhancement (SE) 210 Output 2, investigating improvements in design methods and guidelines to "assess flight crew performance in situations associated with loss of energy and/or attitude state awareness".

Feary, Michael S.↗
NASA NTRS2003

Aviation Data Integration System

During the analysis of flight data and safety reports done in ASAP and FOQA programs, airline personnel are not able to access relevant aviation data for a variety of reasons. We have developed the Aviation Data Integration System (ADIS), a software system that provides integrated heterogeneous data to support safety analysis. Types of data available in ADIS include weather, D-ATIS, RVR, radar data, and Jeppesen charts, and flight data. We developed three versions of ADIS to support airlines. The first version has been developed to support ASAP teams. A second version supports FOQA teams, and it integrates aviation data with flight data while keeping identification information inaccessible. Finally, we developed a prototype that demonstrates the integration of aviation data into flight data analysis programs. The initial feedback from airlines is that ADIS is very useful in FOQA and ASAP analysis.

Kulkarni, Deepak↗
NASA NTRS2003

Probabilistic Causal Analysis for System Safety Risk Assessments in Commercial Air Transport

Aviation is one of the critical modes of our national transportation system. As such, it is essential that new technologies be continually developed to ensure that a safe mode of transportation becomes even safer in the future. The NASA Aviation Safety Program (AvSP) is managing the development of new technologies and interventions aimed at reducing the fatal aviation accident rate by a factor of 5 by year 2007 and by a factor of 10 by year 2022. A portfolio assessment is currently being conducted to determine the projected impact that the new technologies and/or interventions may have on reducing aviation safety system risk. This paper reports on advanced risk analytics that combine the use of a human error taxonomy, probabilistic Bayesian Belief Networks, and case-based scenarios to assess a relative risk intensity metric. A sample case is used for illustrative purposes.

Luxhoj, James T.↗
NASA NTRS2010

Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Sensor Validation and Verification on National Oceanographic and Atmospheric Administration (NOAA) Lockheed WP-3D Aircraft

As part of the National Aeronautics and Space Administration's Aviation Safety and Security Program, the Tropospheric Airborne Meteorological Data Reporting project (TAMDAR) developed a low-cost sensor for aircraft flying in the lower troposphere. This activity was a joint effort with support from Federal Aviation Administration, National Oceanic and Atmospheric Administration, and industry. This paper reports the TAMDAR sensor performance validation and verification, as flown on board NOAA Lockheed WP-3D aircraft. These flight tests were conducted to assess the performance of the TAMDAR sensor for measurements of temperature, relative humidity, and wind parameters. The ultimate goal was to develop a small low-cost sensor, collect useful meteorological data, downlink the data in near real time, and use the data to improve weather forecasts. The envisioned system will initially be used on regional and package carrier aircraft. The ultimate users of the data are National Centers for Environmental Prediction forecast modelers. Other users include air traffic controllers, flight service stations, and airline weather centers. NASA worked with an industry partner to develop the sensor. Prototype sensors were subjected to numerous tests in ground and flight facilities. As a result of these earlier tests, many design improvements were made to the sensor. The results of tests on a final version of the sensor are the subject of this report. The sensor is capable of measuring temperature, relative humidity, pressure, and icing. It can compute pressure altitude, indicated air speed, true air speed, ice presence, wind speed and direction, and eddy dissipation rate. Summary results from the flight test are presented along with corroborative data from aircraft instruments.

Tsoucalas, George↗