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At least 163 records · Page 9

Investigation of pilot's role and display requirements in automatic landings

Two experimental capabilities were developed on the PDP-12 computers. The first of these was an experimental monitor to perform experiments in the psychophysics of visual target motion prediction, discrimination, etc., and exercises the (limited) graphical capabilities of the PDP-12. The original monitor was modified to include the capability of handling more than 64 stimuli without reinitializing the program. The second experimental monitor was programmed and was used to investigate pilot decisions in low visibility approaches. The details of this experimental capability, which has great potential for exploring decisions and behavior, are described in detail.

Curry, R. E.↗

Atmospheric effects on the Space Shuttle approach and landing

The present work describes piloted simulations of Space Shuttle approach and landing where the pilot either flies the aircraft or monitors a computer-controlled flight with the option to take control. The simulated runs encompassed approach to the airport, acquisition of the glide slope and localizer, and accomplishing final flare and touchdown. The degree of difficulty associated with the flight task was imposed through modeled atmospheric winds and superimposed atmospheric turbulence. The simulator models the Orbiter vehicle with the aid of an all-digital computer complex and a fixed-base crew station. Comparison between piloted and computer-controlled responses to unexpected atmospheric conditions was obtained by recording data from instrument displays available to the pilot.

Ragsdale, W. A.↗

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↗

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↗

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↗

TPSAS-NF1676L-9785-DND

Evaluate feasibility of inferring aspects of pilot state using active (force-feedback) side-stick, including a) contact with stick (haptic monitoring), b) Desire to change automation support level, c) pilot workload, and d) stress. Conduct human-in-the loop experiment to generate database for off-line investigation of potential signals and identification methods

Ken Goodrich↗

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools II: Contextual Constraints and Information Sources

Recent advances in artificial intelligence, machine learning, data mining and sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the second of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explored fundamental issues associated with the development of such a system. In this report, we extend this work to focus on two critical aspects of these systems: 1) the constraints and conditions that drive the dynamic prioritization and presentation of data and information to the pilots, and 2) specific data and information to be accessed, monitored, integrated, and displayed in such a system.

context-sensitive↗

The Contribution of Pilots to Resilience in Normal Operations. Part II: A closer look at briefings: Anticipation and Monitoring Also Known as Planning and Coordination

Much of our knowledge about human performance in flight safety has come from the analysis of undesired events, whether accidents, incidents, or crew behaviors identified via flight exceedance monitoring or observational techniques. In recent years, there has been an acknowledgement that operational personnel are not merely sources of “human error”, but also make a unique human contribution to safe outcomes. In a few celebrated cases, this takes the form of “heroic saves”, but on many more occasions, operational personnel contribute to safety through everyday, often-unnoticed actions that turn potentially hazardous situations into non-events. An emerging approach to safety, frequently referred to as “Safety II,” proposes that the positive human contribution is an important and largely untapped source of safety information. Some airlines have successfully trained observers to identify and record the positive behaviors exhibited by the crew over the course of a flight. In other cases, flight crew are interviewed about good practices or positive behaviors. However, each of these methods are relatively limited in scale and resource intensive. A survey could provide a relatively low-cost approach to systematically gather this information on a larger scale. The primary purpose of the research was to develop and assess a surveys methodology for assessing crews' activities in normal flights and the operational perturbations encountered during normal operations. We hope that such a survey could be both a research tool as well as a safety management aid for the aviation industry. We collected responses concerning revenue flights from two groups of airline pilots (N = 25 & N= 65). The results indicated that relatively few flights proceeded exactly as in the original flight plan. Pilots routinely anticipated and adapted to changing circumstances. We will review the challenges encountered in developing the survey and summarize preliminary findings from two administrations of the survey to airline pilots.

human contribution safety↗

Multi-Agency Annual Southeastern Beach Mouse Habitat Occupancy Monitoring

The southeastern beach mouse (Peromyscus polionotus niveiventris, hereafter SEBM), a federally threatened species was identified by Merritt Island National Wildlife Refuge (MINWR) as one of the top five priorities for management. The Kennedy Space Center (KSC) Environmental Management Branch was asked to provide support in the form of population monitoring for SEBM on KSC and the surrounding properties. When we began the project, the SEBM was known to occupy sites ranging from Volusia through Brevard and Indian River Counties, but the exact distribution within the Federal lands encompassing the Cape Canaveral Barrier Island Complex (CCBIC) was not well known. The broad range of habitat conditions encompassing the species’ historical range and the diversity of sites historically known to contain SEBM required a landscape-scale approach for both monitoring the population and for investigating species habitat relationships. We designed a monitoring plan for the SEBM with the goal of estimating the habitat occupancy of beach mice annually each winter/spring throughout the entire area of suitable coastal habitat (approximately 72 km linear distance along the beach). Methods were tested in a 2008 pilot study, and during 2010-2018 we monitored the proportion of coastal habitat occupied by the SEBM on the CCBIC. Monitoring was focused on using dynamic habitat occupancy surveys with data collected with rapid assessment techniques (i.e., track tubes or live-traps) to detect SEBM occurrence at sampling stations. An important component of the study design was the use of repeated samples that provided the information needed to estimate detectability. Measuring detectability was required to account for the fact that surveys could fail to detect animals at sites at which they were actually present (Mackenzie et al., 2002). This monitoring framework is very flexible, allowing numerous hypothesis to be tested about how various factors influence beach mouse occupancy using habitat, geographic, and environmental covariates. Our survey has been the longest survey conducted for any of the seven extant beach mouse subspecies and has encompassed nearly the entire remaining range of the SEBM. Although occupancy surveys of other beach mouse subspecies via track tubes have been conducted on the Gulf coast of Florida by Florida Fish and Wildlife Conservation Commission (FWC), United States Fish and Wildlife Service (USFWS), and various universities, we expanded previous methods to fit unique aspects of the SEBM, and thus our study was very different from any of the previous studies. To achieve this specificity, we employed an adaptive approach throughout the study, with all activities aimed at providing managers with information related to environmental compliance and natural resource management on KSC and the surrounding Federal lands.

Eric Douglas Stolen↗

Legislated emergency locating transmitters and emergency position indicating radio beacons

An emergency locating transmitting (ELT) system comprising a legislated ELT modified with an interface unit and connected by a multiwire cable to a remote control monitor (RCM), typically located at the pilot position. The RCM can remotely (1) test the ELT by disabling the legislated swept tone and allowing transmission of a single tone, (2) turn the ELT "on" for the legislated ELT transmission, and (3) reset the ELT to an "armed" condition. The RCM also provides visual and audio indications for transmitter operating condition as well as ELT battery condition. Removing the RCM or shorting or opening the interface input connections will not affect traditional ELT operation.

William R Wade↗

STS-94 Day 08 Highlights

On this eighth day of the STS-94 mission, the flight crew, Cmdr. James D. Halsell, Jr., Pilot Susan L. Still, Payload Cmdr. Janice E. Voss, Mission Specialists Michael L. Gernhardt and Donald A. Thomas, and Payload Specialists Gregory T. Linteris and Roger K. Crouch conduct status checks and perform video documentation of some of the Microgravity Science Laboratory experiments and activities in the Spacelab. The first part of Pilot Susan Still's day involves monitoring orbiter systems and working an in-flight maintenance procedure with the Shuttle Amateur Radio Experiment (SAREX).

Source record↗

Evaluating a CRT map predictor for airborne use

Six airline pilots participated in a fixed-base simulator experiment designed to study the advantages and disadvantages of incorporating a simple horizontal flight-path predictor on both fixed and rotating electronic CRT map displays. The pilots were asked to fly a modified 'figure eight' ground track while attempting to maintain constant altitude. All flight information was displayed on one 17-in. (43-cm) CRT monitor. The controlled variables were the map orientation, pilots, presence or absence of crosswinds, presence or absence of wind gusts, and presence or absence of predictor. Error scores were recorded as deviations from the commanded ground track and altitude. It was found that the predictor reduced deviations from the commanded ground track, narrowed performance differences among pilots, narrowed the error differences found with and without crosswinds, and decreased pilot work load.

Baty, D. L.↗

Visual/motion cue mismatch during a coordinated roll maneuver

The effect of a performance mismatch between the simulator visual and motion display systems on pilot performance while engaged in a compensatory tracking task, and the effect of a reduction in simulator motion scaling while maintaining constant visual scaling on pilot performance for this same task were investigated. A jet transport aircraft with motion in the roll and lateral simulator axes was used as a test vehicle for a computer simulation. The aircraft was disturbed by moderate levels of turbulence which resulted in flight path deviations in the roll and lateral axes. The task of the pilot was to maintain flight formation behind the aircraft in front of him as displayed by a video monitor located in the simulator cockpit. Experimental data consisting of pilot describing functions and pilot performance scores are presented and discussed as they relate to experimental evidence.

Shirachi, D. K.↗

Evaluation of a takeoff performance monitoring system

A takeoff performance monitoring system (TOPMS) has been developed to provide the pilot with graphic/numeric information pertinent to his decision to continue or abort a takeoff. The TOPMS instrument display consists primarily of a runway graphic overlaid with symbolic status, predictive, and advisory information including: (1) current position and airspeed, (2) predicted locations for reaching decision speed and rotation speed, (3) groundroll limit for reaching the rotation speed, (4) predicted stop point for an aborted takeoff from current conditions, (5) engine-failure flags, and (6) an overall situation advisory flag which recommends continuation or rejection of the takeoff. In this study, over 30 experienced multiengine pilots evaluated the TOPMS display on the Langley B-737 real-time research simulator. The display was judged to be easy to monitor and comprehend.

Middleton, David B.↗

Engine monitoring display study

The current study is part of a larger NASA effort to develop displays for an engine-monitoring system to enable the crew to monitor engine parameter trends more effectively. The objective was to evaluate the operational utility of adding three types of information to the basic Boeing Engine Indicating and Crew Alerting System (EICAS) display formats: alphanumeric alerting messages for engine parameters whose values exceed caution or warning limits; alphanumeric messages to monitor engine parameters that deviate from expected values; and a graphic depiction of the range of expected values for current conditions. Ten training and line pilots each flew 15 simulated flight scenarios with five variants of the basic EICAS format; these variants included different combinations of the added information. The pilots detected engine problems more quickly when engine alerting messages were included in the display; adding a graphic depiction of the range of expected values did not affect detection speed. The pilots rated both types of alphanumeric messages (alert and monitor parameter) as more useful and easier to interpret than the graphic depiction. Integrating engine parameter messages into the EICAS alerting system appears to be both useful and preferred.

Hornsby, Mary E.↗

Incorporating Data Link Messaging into a Multi-function Display for General Aviation Aircraft

One objective of the Small Aircraft Transportation System (SATS) Project is to increase the capacity and utilization of small non-towered, non-radar equipped airports by transferring traffic management activities to an automated system and separation responsibilities to general aviation (GA) pilots. This paper describes the development of a research multi-function display (MFD) to support the interaction between pilots and an automated Airport Management Module (AMM). Preliminary results of simulation and flight tests indicate that adding the responsibility of monitoring other traffic for self-separation does not increase pilots subjective workload levels. Pilots preferred using the enhanced MFD to execute flight procedures, reporting improved situation awareness over conventional instrument flight rules (IFR) procedures.

Adams, Catherine A.↗

Remotely piloted LTA vehicle for surveillance

Various aspects of a remotely piloted mini-LTA vehicle for surveillance, monitoring and measurement for civilian and military applications are considered. Applications, operations and economics are discussed.

Seemann, G. R.↗

A Flight Evaluation of an Airborne Physiological Instrumentation System, Including Preliminary Results Under Conditions of Varying Accelerations

A physiological instrumentation system capable of recording the electrocardiogram, pulse rate, respiration rate, and systolic and diastolic blood pressures during flight has been developed. This instrumentation system was designed for use during control studies at varied levels of acceleration in order to monitor the well-being of the pilot and at the same time to obtain data for study of the relationships between his various physiological functions and his performance capability. Flights, made in a T-33 aircraft, demonstrated the ability of the system to obtain the desired physiological data in flight. The data obtained in these flights, although limited in nature, indicate a slowing of the pulse rate under the subgravity conditions of brief duration. There appeared to be a proportional nearly in-phase relationship between pulse rate and acceleration. A decrease in diastolic blood pressure together with an increase in pulse pressure was noted during subgravity conditions and an elevation of the diastolic pressure together with a decrease in pulse pressure du-ring increased accelerations. No change worthy of note was seen in the records of the systolic blood pressure, the respiration rate, or the electrocardiogram over the range of acceleration studied (0 to 3 g).

Smedal, Harald A.↗