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Aviation safety reports that relate to loss of control in flight, problems that occur as a result of similar sounding alphanumerics, and pilot incapacitation are presented. Problems related to the go around maneuver in air carrier operations, and bulletins (and FAA responses to them) that pertain to air traffic control systems and procedures are included.
The Aviation Safety Reporting System (ASRS) in a partnership between the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), participating carriers, and labor organizations. It is designed to improve the National Airspace System by collecting and studying reports detailing unsafe conditions and events in the aviation industry. Employees are able to report safety issues or concerns with confidentiality and without fear of discipline.
The aviation safety reporting system, an accident reporting system, is presented. The system identifies deficiencies and discrepancies and the data it provides are used for long term identification of problems. Data for planning and policy making are provided. The system offers training in safety education to pilots. Data and information are drawn from the available data bases.
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Context: The NASA Aviation Safety Reporting System (ASRS) is a voluntary confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants and other involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts and a short descriptive synopsis is written to describe the safety issue. The de-identified reports are then disseminated to the aviation community in a number of ways including entry into an online database, Safety Alert Bulletins and For Your Information Notices, and the CALLBACK newsletter. Key to these publications are the timely processing (de-identification, coding and summarization) of new reports, which is currently done by ASRS expert safety analysts. Thus, we believe topic modelling could decrease effort in ASRS, if topics are comprehensible. Aim: We propose a methodology to evaluate whether automated topic finding using topic modelling provides meaningful and useful topics. Method: We extend the total error survey methodology to evaluate user topic comprehension of machine learning outputs. To accomplish this we performed a literature review to identify existing methods and define a construct for topic comprehension, utilizing existing ASRS synopsis writing practices to more precisely define meaningfulness and usefulness. Results: A survey protocol was created that addresses the limitations of other survey protocols found in the literature review, which we found lacking in rationale and clear protocol definition. Conclusion: The surveying of user understanding in machine learning outputs presents challenges due to the explosion of parameters to control for and the lack of systematic approach presented in the literature. More reproducible work and survey protocols are needed in the literature and our work is one step towards that direction.
The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 900,000 reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 5,500 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides de-identified report information through the online ASRS Database at http://asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation \vill discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.
The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 1.4 million reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 6,000 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides selected de-identified report information through the online ASRS Database at http:asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation will discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.
The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 1.4 M reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 6,000 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides selected de-identified report information through the online ASRS Database at http:asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation will discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.
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.
The Aviation Safety Reporting System (ASRS) was established in 1976 under an agreement between the Federal Aviation Administration (FAA) and the National Aeronautics and Space Administration (NASA). This cooperative safety program invites pilots, air traffic controllers, flight attendants, maintenance personnel, and others to voluntarily report to NASA any aviation incident or safety hazard. The FAA provides most of the program funding. NASA administers the program, sets its policies in consultation with the FAA and aviation community, and receives the reports submitted to the program. The FAA offers those who use the ASRS program two important reporting guarantees: confidentiality and limited immunity. Reports sent to ASRS are held in strict confidence. More than 350,000 reports have been submitted since the program's beginning without a single reporter's identity being revealed. ASRS removes all personal names and other potentially identifying information before entering reports into its database. This system is a very successful, proof-of-concept for gathering safety data in order to provide timely information about safety issues. The ASRS information is crucial to aviation safety efforts both nationally and internationally. It can be utilized as the first step in safety by providing the direction and content to informed policies, procedures, and research, especially human factors. The ASRS process and procedures will be presented as one model of safety reporting feedback systems.
The NASA Aviation Safety Reporting System (ASRS) is a voluntary, confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants, and others involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts, and a short descriptive synopsis is written to describe the safety issue. The de-identified reports are then disseminated to the aviation community in many ways, including via an online database, Safety Alert Bulletins, For Your Information Notices, and the CALLBACK newsletter. In this work, we consider whether we can improve the grouping, linking, and understanding of safety concerns through topic modeling. Specifically, we use topic modeling as a building block to identify emerging safety threats over time. This unsupervised approach, we argue, offers the flexibility to identify new emerging themes in this large dataset by constructing different timelines based on the content similarity of ASRS report narratives. This method's unsupervised nature improves upon related research, which is limited to pre-defined labels and therefore can not fully capture emerging safety threats. We apply our method to all ASRS reports in 2020 to assess if the generated timelines can highlight COVID-19 as it is emerging as a safety threat in incoming ASRS reports. We perform both a quantitative and qualitative evaluation of the automatically constructed timelines. The qualitative evaluation is performed by describing the evolution of top terms in the timelines, generated by our method, which we found explicitly convey the themes of COVID-19. Separately, we use a set of 1,213 COVID-19 reports from 2020 that were manually identified by ASRS analysts to quantitatively evaluate the COVID-19 reports distribution across the timelines. Our results have shown that COVID-19 emergence can be identified using the top terms that were generated by topic modeling. The top terms in topic modeling therefore can serve as a summary alternative to manually inspecting reports. Moreover, leveraging the manually identified COVID-19 reports, we found the manually identified timelines accounted for over 70% of the COVID-19 reports curated by the ASRS analysts, which demonstrates the potential of this approach for facilitating the understanding of safety concerns as they emerge and evolve. This method shows great potential to understand aerospace safety threats and other narrative- driven incident report databases.
The NASA Aviation Safety Reporting System (ASRS) is a voluntary, confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants, and others involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts, and a short descriptive synopsis is written to describe the safety issue. The de-identified reports are then disseminated to the aviation community in many ways, including via an online database, Safety Alert Bulletins, For Your Information Notices, and the CALLBACK newsletter. In this work, we consider whether we can improve the grouping, linking, and understanding of safety concerns through topic modeling. Specifically, we use topic modeling as a building block to identify emerging safety threats over time. This unsupervised approach, we argue, offers the flexibility to identify new emerging themes in this large dataset by constructing different timelines based on the content similarity of ASRS report narratives. This method's unsupervised nature improves upon related research, which is limited to pre-defined labels and therefore can not fully capture emerging safety threats. We apply our method to all ASRS reports in 2020 to assess if the generated timelines can highlight COVID-19 as it is emerging as a safety threat in incoming ASRS reports. We perform both a quantitative and qualitative evaluation of the automatically constructed timelines. The qualitative evaluation is performed by describing the evolution of top terms in the timelines, generated by our method, which we found explicitly convey the themes of COVID-19. Separately, we use a set of 1,213 COVID-19 reports from 2020 that were manually identified by ASRS analysts to quantitatively evaluate the COVID-19 reports distribution across the timelines. Our results have shown that COVID-19 emergence can be identified using the top terms that were generated by topic modeling. The top terms in topic modeling therefore can serve as a summary alternative to manually inspecting reports. Moreover, leveraging the manually identified COVID-19 reports, we found the manually identified timelines accounted for over 70% of the COVID-19 reports curated by the ASRS analysts, which demonstrates the potential of this approach for facilitating the understanding of safety concerns as they emerge and evolve. This method shows great potential to understand aerospace safety threats and other narrative- driven incident report databases.
Data obtained from the NASA Aviation Safety Reporting System (ASRS) data base were used to determine problems in general aviation single pilot IFR operations. The data examined consisted of incident reports involving flight safety in the National Aviation System. Only those incidents involving general aviation fixed wing aircraft flying under IFR in instrument meteorological conditions were analyzed. The data were cataloged into one of five major problem areas: (1) controller judgement and response problems; (2) pilot judgement and response problems; (3) air traffic control intrafacility and interfacility conflicts; (4) ATC and pilot communications problems; and (5) IFR-VFR conflicts. The significance of the related problems, and the various underlying elements associated with each are discussed. Previous ASRS reports covering several areas of analysis are reviewed.
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.
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.
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.
This presentation presents an overview of NASA's Aviation Safety Reporting System including report processing metrics and outreach activities.
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.