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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Effects of False Tilt Cues on the Training of Manual Roll Control Skills

This paper describes a transfer-of-training study performed in the NASA Ames Vertica lMotion Simulator. The purpose of the study was to investigate the effect of false tilt cues on training and transfer of training of manual roll control skills. Of specific interest were the skills needed to control unstable roll dynamics of a mid-size transport aircraft close to the stall point. Nineteen general aviation pilots trained on a roll control task with one of three motion conditions: no motion, roll motion only, or reduced coordinated roll motion. All pilots transferred to full coordinated roll motion in the transfer session. A novel multimodal pilot model identification technique was successfully applied to characterize how pilots' use of visual and motion cues changed over the course of training and after transfer. Pilots who trained with uncoordinated roll motion had significantly higher performance during training and after transfer, even though they experienced the false tilt cues. Furthermore, pilot control behavior significantly changed during the two sessions, as indicated by increasing visual and motion gains, and decreasing lead time constants. Pilots training without motion showed higher learning rates after transfer to the full coordinated roll motion case.

simulators↗
NASA NTRS1991

Identifying tacit strategies in aircraft maneuvers

Two machine-learning methods are presently used to characterize the avoidance strategies used by skilled pilots in simulated aircraft encounters, and a general framework for the characterization of the strategic components of skilled behavior via qualitative representation of situations and responses is presented. Descriptions of pilot maneuvers that were 'conceptually equivalent' were ascertained by a concept-learning algorithm in conjunction with a classifier system that employed a generic algorithm; satisficing and 'buggy' strategies were thereby revealed.

Lewis, Charles M.↗
NASA NTRS2004

Accessing FMS Functionality: The Impact of Design on Learning

In modern commercial and military aircraft, the Flight Management System (FMS) lies at the heart of the functionality of the airplane. The nature of the FMS has also caused great difficulties learning and accessing this functionality. This study examines actual Air Force pilots who were qualified on the newly introduced advanced FMS and shows that the design of the system itself is a primary source of difficulty learning the system. Twenty representative tasks were selected which the pilots could be expected to accomplish on an ' actual flight. These tasks were analyzed using the RAFIV stage model (Sherry, Polson, et al. 2002). This analysis demonstrates that a great burden is placed on remembering complex reformulation of the task to function mapping. 65% of the tasks required retaining one access steps in memory to accomplish the task, 20% required two memorized access steps, and 15% required zero memorized access steps. The probability that a participant would make an access error on the tasks was: two memorized access steps - 74%, one memorized access step - 13%, and zero memorized access steps - 6%. Other factors were analyzed as well, including experience with the system and frequency of use. This completed the picture of a system with many memorized steps causing difficulty with the new system, especially when trying to fine where to access the correct function.

Fennell, Karl↗
NASA NTRS1979

Meteorological Input to General Aviation Pilot Training

The meteorological education of general aviation pilots is discussed in terms of the definitions and concepts of learning and good educational procedures. The effectiveness of the metoeorological program in the training of general aviations pilots is questioned. It is suggested that flight instructors provide real experience during low ceilings and visibilities, and that every pilot receiving an instrument rating should experience real instrument flight.

Colomy, J. R.↗
NASA NTRS1984

Early Air Force Flight Test Center (AFFTC) experience with Peripheral Vision Horizon Displays (PVHD)

Three separate Air Force Flight Test Center (AFFTC) tests were conducted in 1980 and 1981 on two models of the peripheral vision horizon displays (PVHD) (Malcolm Horizon). A fixed base simulator test was conducted with twenty test pilot subjects using the Flight Simulator Demonstration Model which incorporated a Helium Neon laser as the light bar medium. Two separate flight tests were conducted by the Test Pilot School classes 80A and 80B in a Twin Otter commuter aircraft using the Stage A Model PVHD. The Xenon lighted A Model was tested in its original configuration by class 80A. Class 80B used a modified configuration which incorporated an AFFTC designed and manufactured hood. With the hood, the PVHD projected a thinner, distinct light bar. Only a few general remarks concerning the tests and unrestricted, overall conclusions reached by the author are presented. The conclusions of all three AFFTC evaluations of the PVHD concept were that it has not yet been adequately evaluated. There seems to be a significant learning curve associated with the PVHD and the project pilots for Test Pilot School Class 80B only got a good start on the learning curve. A lengthy learning curve for the PVHD should be anticipated in view of the training period required for the attitude display indicator (ADI). This does seem to point out that the PVHD, in its present form, is simply not as compelling as the natural horizon. It can also be concluded that any attempt at a valid evaluation of the PVHD concept can be done only under instrument meteorological conditions (IMC) or validly simulated IMC conditions. The knee in the learning curve, however, may be reached without full IMC, although it may take much longer to reach.

Schofield, B. L.↗
NASA NTRS2003

Learning About Cockpit Automation: From Piston Trainer to Jet Transport

Two experiments explored the idea of providing cockpit automation training to airline-bound student pilots using cockpit automation equipment commonly found in small training airplanes. In a first experiment, pilots mastered a set of tasks and maneuvers using a GPS navigation computer, autopilot, and flight director system installed in a small training airplane Students were then tested on their ability to complete a similar set of tasks using the cockpit automation system found in a popular jet transport aircraft. Pilot were able to successfully complete 77% of all tasks in the jet transport on their first attempt. An analysis of a control group suggests that the pilot's success was attributable to the application of automation principles they had learned in the small airplane. A second experiment looked at two different ways of delivering small-aeroplane cockpit automation training: a self-study method, and a dual instruction method. The results showed a slight advantage for the self-study method. Overall, the results of the two studies cast a strong vote for the incorporation of cockpit automation training in curricula designed for pilot who will later transition to the jet fleet.

Casner, Stephen M.↗
NASA NTRS2008

Autonomous Formation Flight: Project Overview

Objectives: a) Map the vortex effects; b) Formation Auto-Pilot Requirements. Two NASA F/A-18 aircraft in formation: a) NASA 845 Systems Research Aircraft; b) NASA 847 Support Aircraft. Flight Conditions: M = 0.56, 25000 feet (Subsonic condition); b) M = 0.86, 36000 feet (Transonic condition). Nose-To-Tail (N2T) Distances: 20, 55, 110 and 190 feet. Lessons learned: a) Controllable flight in vortex is possible with pilot feedback (displays); b) Position hold at best C(sub D), is attainable; c) Best drag location is close to max rolling moment; e) Drag reductions demonstrated up to 22% (WFE up to 20%); f) Induced drag results compare favorably with simple prediction model; g) "Sweet Spot" (lateral & vertical area > 25%) is larger than predicted; h) Larger wing overlaps result in sign reversals in roll, yaw; i) As predicted, favorable effects degrade gradually with increased nose-to-tail distances after peaking at 3 span lengths aft; and j) Demonstrated - over 100 N mi (>15%) range improvement and 650 lbs (14%) fuel savings on actual simulated F/A-18 cruise mission.

Cole, Jennifer↗
NASA NTRS1995

Liftoff to learning: Assignment space

The crew of the STS-58 Space Shuttle Columbia -- Commander John Blaha, Pilot Richard Searfoss, Payload Commander Rhea Seddon, Mission Specialist Shannon Lucid, Mission Specialist David Wolf, and Payload Specialist William McArthur host this educational video (part of the Liftoff to Learning series). The Astronauts help students to understand the importance of safety procedures on Earth as well as in space. They also discuss the effects of microgravity on various experiments in space.

Source record↗
NASA NTRS1982

Simulator study of a pictorial display for general aviation instrument flight

A simulation study of a computer drawn pictorial display involved a flight task that included an en route segment, terminal area maneuvering, a final approach, a missed approach, and a hold. The pictorial display consists of the drawing of boxes which either move along the desired path or are fixed at designated way points. Two boxes may be shown at all times, one related to the active way point and the other related to the standby way point. Ground tracks and vertical profiles of the flights, time histories of the final approach, and comments were obtained from time pilots. The results demonstrate the accuracy and consistency with which the segments of the flight are executed. The pilots found that the display is easy to learn and to use; that it provides good situation awareness, and that it could improve the safety of flight. The small size of the display, the lack of numerical information on pitch, roll, and heading angles, and the lack of definition of the boundaries of the conventional glide slope and localizer areas were criticized.

Adams, J. J.↗
NASA NTRS2008

Health and Environment Linked for Information Exchange (HELIX)-Atlanta: A CDC-NASA Joint Environmental Public Health Tracking Collaborative Project

HELIX-Atlanta was developed to support current and future state and local EPHT programs to implement data linking demonstration projects which could be part of the CDC EPHT Network. HELIX-Atlanta is a pilot linking project in Atlanta for CDC to learn about the challenges the states will encounter. NASA/MSFC and the CDC are partners in linking environmental and health data to enhance public health surveillance. ~ The use of NASA technology creates value added geospatial products from existing environmental data sources to facilitate public health linkages. Proving the feasibility of the approach is the main objective

Al-Hamdan, Mohammad↗
NASA NTRS2008

Remote Sensing, Air Quality, and Public Health

HELIX-Atlanta was developed to support current and future state and local EPHT programs to implement data linking demonstratio'n projects which could be part of the EPHT Network. HELIX-Atlanta is a pilot linking project in Atlanta for CDC to learn about the challenges the states will encounter. NASA/MSFC and the CDC are partners in linking environmental and health data to enhance public health surveillance. The use of NASA technology creates value - added geospatial products from existing environmental data sources to facilitate public health linkages. Proving the feasibility of the approach is the main objective

Quattrochi, Dale A.↗
NASA NTRS2001

Quality Training and Learning in Aviation: Problems of Alignment

The challenge of producing training programs that lead to quality learning outcomes is ever present in aviation, especially when economic and regulatory pressures are brought into the equation. Previous research by Telfer & Moore (1997) indicates the importance of appropriate alignment of beliefs about learning across all levels of an organization from the managerial level, through the instructor/check and training level, to the pilots and other crew. This paper argues for a central focus on approaches to learning and training that encourage understanding, problem solving and application. Recent research in the area is emphasized as are methods and techniques for enhancing deeper learning.

Moore, Phillip J.↗
NASA NTRS1984

Synthesized speech rate and pitch effects on intelligibility of warning messages for pilots

In civilian and military operations, a future threat-warning system with a voice display could warn pilots of other traffic, obstacles in the flight path, and/or terrain during low-altitude helicopter flights. The present study was conducted to learn whether speech rate and voice pitch of phoneme-synthesized speech affects pilot accuracy and response time to typical threat-warning messages. Helicopter pilots engaged in an attention-demanding flying task and listened for voice threat warnings presented in a background of simulated helicopter cockpit noise. Performance was measured by flying-task performance, threat-warning intelligibility, and response time. Pilot ratings were elicited for the different voice pitches and speech rates. Significant effects were obtained only for response time and for pilot ratings, both as a function of speech rate. For the few cases when pilots forgot to respond to a voice message, they remembered 90 percent of the messages accurately when queried for their response 8 to 10 sec later.

Simpson, C. A.↗
NASA NTRS2014

Usability of EFBs for Viewing NOTAMs and AIS/MET Data Link Messages

Electronic Flight Bags (EFB) are increasingly integral to flight deck information management. A piloted simulation study was conducted at NASA Langley Research Center, one aspect of which was to evaluate the usability and acceptability of EFBs for viewing and managing Notices to Airmen (NOTAMs) and data linked aeronautical information services (AIS) and meteorological information (MET). The study simulated approaches and landings at Memphis International Airport (KMEM) using various flight scenarios and weather conditions. Ten two-pilot commercial airline crews participated, utilizing the Cockpit Motion Facility's Research Flight Deck (CMF/RFD) simulator. Each crew completed approximately two dozen flights over a two day period. Two EFBs were installed, one for each pilot. Study data were collected in the form of questionnaire/interview responses, audio/video recordings, oculometer recordings, and aircraft/system state data. Preliminary usability results are reported primarily based on pilot interviews and responses to questions focused on ease of learning, ease of use, usefulness, satisfaction, and acceptability. Analysis of the data from the other objective measures (e.g., oculometer) is ongoing and will be reported in a future publication. This paper covers how the EFB functionality was set up for the study; the NOTAM, AIS/MET data link, and weather messages that were presented; questionnaire results; selected pilot observations; and conclusions.

Evans, Emory T.↗
NASA NTRS2013

Human Factors in Accidents Involving Remotely Piloted Aircraft

This presentation examines human factors that contribute to RPA mishaps and provides analysis of lessons learned. RPA accident data from U.S. military and government agencies were reviewed and analyzed to identify human factors issues. Common contributors to RPA mishaps fell into several major categories: cognitive factors (pilot workload), physiological factors (fatigue and stress), environmental factors (situational awareness), staffing factors (training and crew coordination), and design factors (human machine interface).

Merlin, Peter William↗
NASA NTRS2019

Air Traffic Management Technology Demonstration-1 (ATD-1) Avionics Phase 2 Flight Test Training for Interval Management

Prior to the successful flight test validation of a new avionics prototype, participants from Boeing, Honeywell, and United Airlines underwent group training at NASA Langley Research Center. New prototype software for an algorithm which enables greater efficiency in high-density airspace, called Interval Management, was to be incorporated into Electronic Flight Bags and placed in the cockpit for pilot usage. The goals of the training were to teach the flight test pilots how to operate the new software, establish techniques to simultaneously position three aircraft prior to each test scenario, and ensure a common communication protocol among team members when coordinating the position of aircraft for the next scenario. The multi-tiered interactive training regimen consisted of a process that continually built upon previous foundational material. The primary learning elements were 1) a portable computer-based trainer that was provided to the pilots prior to classroom training sessions, 2) classroom learning, 3) full mock-up simulator training, and 4) refresher training just prior to the flight test. Each part of the regimen was designed to repeat and build upon the previous element. The purpose of this Technical Memorandum is to inform the aviation industry how flight training for Interval Management was conducted at Langley Research Center in order to reduce overall development costs of future Interval Management training programs. Secondly, the paper provides insight regarding the decision-making process when attempting to conduct a flight test.

Roper, Roy D.↗
NASA NTRS2021

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal (<90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Machine Learning↗
NASA NTRS2015

Reinforcement Learning with Autonomous Small Unmanned Aerial Vehicles in Cluttered Environments

We present ongoing work in the Autonomy Incubator at NASA Langley Research Center (LaRC) exploring the efficacy of a data set aggregation approach to reinforcement learning for small unmanned aerial vehicle (sUAV) flight in dense and cluttered environments with reactive obstacle avoidance. The goal is to learn an autonomous flight model using training experiences from a human piloting a sUAV around static obstacles. The training approach uses video data from a forward-facing camera that records the human pilot's flight. Various computer vision based features are extracted from the video relating to edge and gradient information. The recorded human-controlled inputs are used to train an autonomous control model that correlates the extracted feature vector to a yaw command. As part of the reinforcement learning approach, the autonomous control model is iteratively updated with feedback from a human agent who corrects undesired model output. This data driven approach to autonomous obstacle avoidance is explored for simulated forest environments furthering autonomous flight under the tree canopy research. This enables flight in previously inaccessible environments which are of interest to NASA researchers in Earth and Atmospheric sciences.

Tran, Loc↗