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At least 37 records · Page 2
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NASA NTRS1977

NASA aviation safety reporting system

During the third quarter of operation of the Aviation Safety Reporting System (ASRS), 1429 reports concerning aviation safety were received from pilots, air traffic controllers, and others in the national aviation system. Details of the administration and results of the program are discussed. The design and construction of the ASRS data base are briefly presented. Altitude deviations and potential aircraft conflicts associated with misunderstood clearances were studied and the results are discussed. Summary data regarding alert bulletins, examples of alert bulletins and responses to them, and a sample of deidentified ASRS reports are provided.

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NASA NTRSDate not supplied

Aviation Safety Reporting System (ASRS)

This overview of the NASA Aviation Safety Reporting System (ASRS) will describe the genesis of the program, report processing procedures, and safety products that are produced from the ASRS data.

aviation safety reporting↗
NASA NTRS1983

Analysis of general aviation single-pilot IFR incident data obtained from the NASA Aviation Safety Reporting System

An analysis of incident data obtained from the NASA Aviation Safety Reporting System (ASRS) has been made to determine the problem areas in general aviation single-pilot IFR (SPIFR) operations. The Aviation Safety Reporting System data base is a compilation of voluntary reports of incidents from any person who has observed or been involved in an occurrence which was believed to have posed a threat to flight safety. This paper examines only those reported incidents specifically related to general aviation single-pilot IFR operations. The frequency of occurrence of factors related to the incidents was the criterion used to define significant problem areas and, hence, to suggest where research is needed. The data was cataloged into one of five major problem areas: (1) controller judgment and response problems, (2) pilot judgment and response problems, (3) air traffic control (ATC) intrafacility and interfacility conflicts, (4) ATC and pilot communication problems, and (5) IFR-VFR conflicts. In addition, several points common to all or most of the problems were observed and reported. These included human error, communications, procedures and rules, and work load.

Bergeron, H. P.↗
NASA NTRS1976

NASA aviation safety reporting system

During the second quarter of the Aviation Safety Reporting System (ASRS) operation, 1,497 reports were received from pilots, controllers, and others in the national aviation system. Details of the administration and results of the program to date are presented. Examples of alert bulletins disseminated to the aviation community are presented together with responses to those bulletins. Several reports received by ASRS are also presented to illustrate the diversity of topics covered by reports to the system.

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NASA NTRS2015

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.↗
NASA NTRS1976

NASA aviation safety reporting system

The origins and development of the NASA Aviation Safety Reporting System (ASRS) are briefly reviewed. The results of the first quarter's activity are summarized and discussed. Examples are given of bulletins describing potential air safety hazards, and the disposition of these bulletins. During the first quarter of operation, the ASRS received 1464 reports; 1407 provided data relevant to air safety. All reports are being processed for entry into the ASRS data base. During the reporting period, 130 alert bulletins describing possible problems in the aviation system were generated and disseminated. Responses were received from FAA and others regarding 108 of the alert bulletins. Action was being taken with respect to 70 of the 108 responses received. Further studies are planned of a number of areas, including human factors problems related to automation of the ground and airborne portions of the national aviation system.

Billings, C. E.↗
NASA NTRSDate not supplied

Augmenting Topic Finding in the NASA Aviation Safety Reporting System using Topic Modeling

Context: The NASA Aviation and Safety Reporting System (ASRS) provides various publications to the aviation community (including individual anonymous reports, Callback, Database Search Requests, Directline, and Alerting Messages). Key to these publications are the timely processing of new reports, which is currently done mostly manually by ASRS staff, and which the volume increases yearly. Aim: We investigate whether existing topic modelling techniques are suitable to ease some of the manual effort, and to enhance it with additional visual cues regarding the process of grouping, sense making and labeling incoming (and previous) reports. Method: We evaluate the applicability of WarpLDA topic modelling results combined with three visualization tools, the first two of which have been extended by us in this work for ASRS: Termite, TopicFlow, and LDAVis. Based on the identified limitations in these tools, we propose a methodology for improving them, and evaluate their outputs using ASRS as our test dataset. Results: The user interfaces of Termite, Topicflow and LDAVis were found insufficient for sense-making of the narratives. Moreover, concerns regarding the stability of results due to the inherent randomness of topic modelling, and the lack of a measurable approach for evaluation against the existing ASRS manual workflow were also noted. Conclusion: While many tools to topic modeling and visualization have been proposed, more work is necessary before they can be applied in practical situations to improve existing manual workflows. The methodology presented and applied in this work contribute towards this effort.

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NASA NTRS1979

NASA aviation safety reporting system

The human factors frequency considered a cause of or contributor to hazardous events onboard air carriers are examined with emphasis on distractions. Safety reports that have been analyzed, processed, and entered into the aviation safety reporting system data base are discussed. A sampling of alert bulletins and responses to them is also presented.

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NASA NTRS2014

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.↗
NASA NTRS1983

The NASA Aviation Safety Reporting System

This is the fourteenth in a series of reports based on safety-related incidents submitted to the NASA Aviation Safety Reporting System by pilots, controllers, and, occasionally, other participants in the National Aviation System (refs. 1-13). ASRS operates under a memorandum of agreement between the National Aviation and Space Administration and the Federal Aviation Administration. The report contains, first, a special study prepared by the ASRS Office Staff, of pilot- and controller-submitted reports related to the perceived operation of the ATC system since the 1981 walkout of the controllers' labor organization. Next is a research paper analyzing incidents occurring while single-pilot crews were conducting IFR flights. A third section presents a selection of Alert Bulletins issued by ASRS, with the responses they have elicited from FAA and others concerned. Finally, the report contains a list of publications produced by ASRS with instructions for obtaining them.

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NASA NTRS1994

Pre-Departure Clearance (PDC): An Analysis of Aviation Safety Reporting System Reports Concerning PDC Related Errors

Airlines operating in the United States are required to operate under instrument flight rules (EFR). Typically, a clearance is issued via voice transmission from clearance delivery at the departing airport. In 1990, the Federal Aviation Administration (FAA) began deployment of the Pre-Departure Clearance (PDC) system at 30 U.S. airports. The PDC system utilizes aeronautical datalink and Aircraft Communication and Reporting System (ACARS) to transmit departure clearances directly to the pilot. An objective of the PDC system is to provide an immediate reduction in voice congestion over the clearance delivery frequency. Participating airports report that this objective has been met. However, preliminary analysis of 42 Aviation Safety Reporting System (ASRS) reports has revealed problems in PDC procedures and formatting which have caused errors in the proper execution of the clearance. It must be acknowledged that this technology, along with other advancements on the flightdeck, is adding more responsibility to the crew and increasing the opportunity for error. The present study uses these findings as a basis for further coding and analysis of an additional 82 reports obtained from an ASRS database search. These reports indicate that clearances are often amended or exceptions are added in order to accommodate local ATC facilities. However, the onboard ACARS is limited in its ability to emphasize or highlight these changes which has resulted in altitude and heading deviations along with increases in ATC workload. Furthermore, few participating airports require any type of PDC receipt confirmation. In fact, 35% of all ASRS reports dealing with PDC's include failure to acquire the PDC at all. Consequently, this study examines pilots' suggestions contained in ASRS reports in order to develop recommendations to airlines and ATC facilities to help reduce the amount of incidents that occur.

Montalyo, Michael L.↗
NASA NTRSDate not supplied

Kaona: Deep Searching and Curating Aviation Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given in augmenting existing processes of safety reporting systems. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety reporting systems activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using all public NASA's ASRS narratives and another using all public C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

asrs↗
NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗