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Complex coordinator, consisting of operator control console, recorder, subject display panel, and limb controls, measures human performance by testing perceptual and motor skills. Device measures psychophysiological functions in drug and environmental studies, and is applicable to early detection of psychophysiological body changes.
Measuring human performance in a microgravity environment will aid in identifying the design requirements, human capabilities, safety, and productivity of future astronauts. The preliminary understanding of the microgravity effects on human performance can be achieved through evaluations conducted onboard NASA's KC-135 aircraft. These evaluations can be performed in relation to hardware performance, human-hardware interface, and hardware integration. Measuring human performance in the KC-135 simulated environment will contribute to the efforts of optimizing the human-machine interfaces for future and existing space vehicles. However, there are limitations, such as limited number of qualified subjects, unexpected hardware problems, and miscellaneous plane movements which must be taken into consideration. Examples for these evaluations, the results, and their implications are discussed in the paper.
Current planning and scheduling software tools for International Space Station (ISS) support different flight controller teams as they plan daily space operations. Planning and scheduling tools capabilities include integrating digitized ISS state inputs, evaluating their expected future states, and propagating them over time. Extensive, custom-made computational models of operations, of objectives, and of operational constraints help ISS flight controllers identify where scheduled events violate constraints. Based on the current capabilities of these tools, this paper proposes how human performance measures could be better integrated into planning and scheduling tools for space mission operations. Future integration of human performance measures could be applied to state inputs (in this case, the astronaut’s state) and to modeling human performance operational constraints & operational objectives (i.e., assigned activities) with parameters that are relevant to human performance measures. Gaps between the state-of-the-art for human performance modeling and planning tools for future exploration missions are identified.
Continuous parameter tracking system for measuring human performance in compensatory control system
As telescience systems become more and more complex, autonomous, and opaque to their operators it becomes increasingly difficult to determine whether the total system is performing as it should. Some of the complex and interrelated human performance measurement issues are addressed as they relate to total system validation. The assumption is made that human interaction with the automated system will be required well into the Space Station Freedom era. Candidate human performance measurement-validation techniques are discussed for selected ground-to-space-to-ground and space-to-space situations. Most of these measures may be used in conjunction with an information throughput model presented elsewhere (Haines, 1990). Teleoperations, teleanalysis, teleplanning, teledesign, and teledocumentation are considered, as are selected illustrative examples of space related telescience activities.
A wide variety of secondary payloads have flown on the Space Transportation System (STS) since its first flight in the 1980's. These experiments have typically addressed specific issues unique to the zero-gravity environment. Additionally, the experiments use the experience and skills of the mission and payload specialist crew members to facilitate data collection and ensure successful completion. This paper presents the results of the Terra Scout experiment, which flew aboard STS-44 in November 1991. This unique Earth Observation experiment specifically required a career imagery analyst to operate the Spaceborne Direct-View Optical System (SpaDVOS), a folded optical path telescope system designed to mount inside the shuttle on the overhead aft flight deck windows. Binoculars and a small telescope were used as backup optics. Using his imagery background, coupled with extensive target and equipment training, the payload specialist was tasked with documenting the following: (1) the utility of the equipment; (2) his ability to acquire and track ground targets; (3) the level of detail he could discern; (4) the atmospheric conditions; and (5) other in-situ elements which contributed to or detracted from his ability to analyze targets. Special emphasis was placed on the utility of a manned platform for research and development of future spaceborne sensors. The results and lessons learned from Terra Scout will be addressed including human performance and equipment design issues.
The need for a standardized battery of human performance tests to measure the effects of various treatments is pointed out. Progress in such a program is reported. Three batteries are available which differ in length and the number of tests in the battery. All tests are implemented on a portable, lap held, briefcase size microprocessor. Performances measured include: information processing, memory, visual perception, reasoning, and motor skills, programs to determine norms, reliabilities, stabilities, factor structure of tests, comparisons with marker tests, apparatus suitability. Rationale for the battery is provided.
This study focuses on investigating students' learning effects and performance trends over a certain period using the Rancor Microworld Simulator. Specifically, it aims to determine the training required to collect HRA data from non-experts (i.e., students) using Rancor Microworld and the differences in human performance measures between students and professional operators. A longitudinal experiment is conducted with sixteen undergraduate students, using four Rancor Microworld scenarios in each of the four experiment trials. The study considers four human performance measurements workload, situation awareness, time, and error. Finally, the trend of students' performance is compared with operator data collected from the previous experiment. Overall, this research complements previous studies by providing insights into how much training is required to collect HRA data from non-experts and the differences in human performance measures between students and professional operators.
A need exists for a standardized battery of human performance tests in order to measure the effects of various treatments. The present paper reports on progress in such a program, funded jointly by NASA and the Navy. Three batteries are available which differ in length (7.5, 15, and 30 minutes), and number of tests in the battery (3, 10, and 15). All tests are implemented on a portable, lap-held, briefcase-sized microprocessor (NEC PC 8201A). Performances measured include information processing, memory, visual perception, reasoning, motor skills, etc. Current programs are underway to determine norms, reliabilities, stabilities, factor structure of tests, comparisons with marker tests, apparatus suitability, etc.
Usefulness of transinformation as measure of human tracking performance
NASA's telerobotics technology program is described as well as the process for the transfer of this technology to the Space Station, and some of the implications of the technology for station design and operations, including those for international cooperation. A diagram is presented of the NASREM control heirarchy with the Office of Aeronautics and Space Technology telerobot testbed architecture superimposed. In telerobotics, the following areas were identified as possible subjects for developing data to support international standards: (1) task boards, (2) system performance measures on task boards, (3) human performance measures on task boards with teleoperation, and (4) autonomous-telerobotic-teleoperated performance comparisons.
As automated space systems become more complex, autonomous, and opaque to the flight crew, it becomes increasingly difficult to determine whether the total system is performing as it should. Some of the complex and interrelated human performance measurement issues are addressed that are related to total system validation. An evaluative throughput model is presented which can be used to generate a human operator-related benchmark or figure of merit for a given system which involves humans at the input and output ends as well as other automated intelligent agents. The concept of sustained and accurate command/control data information transfer is introduced. The first two input parameters of the model involve nominal and off-nominal predicted events. The first of these calls for a detailed task analysis while the second is for a contingency event assessment. The last two required input parameters involving actual (measured) events, namely human performance and continuous semi-automated system performance. An expression combining these four parameters was found using digital simulations and identical, representative, random data to yield the smallest variance.
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Securing enough data has been a main challenge in human reliability analysis (HRA). Many researchers and institutes have made a lot of efforts for collecting HRA data to produce reasonable human error probabilities (HEPs) as well as reduce the uncertainty of HRA quantification. Representatively, U.S. Nuclear Regulatory Commission (U.S. NRC), Korea Atomic Energy Research Institute (KAERI) and Idaho National Laboratory (INL) have led lots of empirical research regarding the HRA data collection. The U.S. NRC and KAERI have mainly carried out full-scope simulator research collecting HRA data through experiments using full-scope simulators with actual operators. In contrast, INL has experimentally collected the data using simplified simulators and student operators. INL has proposed the Simplified Human Error Experimental Program (SHEEP) framework to complement full-scope data collection efforts by suggesting a way to infer full-scope data based on experimental data collected from students operating simplified simulators, specifically the Rancor Microworld Simulator (Rancor) and the Compact Nuclear Simulator (CNS). The aim of the SHEEP framework is to lower the entry point for collecting useful HRA data by securing large sample sizes at a reasonable amount of cost and labor while also guaranteeing a high degree of freedom when designing experiments. The authors’ previous research investigated whether data collected from the SHEEP framework could support a representative full-scope study. Besides, human performance differences between professional and student operators when using Rancor and CNS have been analyzed to understand the lack of fidelity of the simplified simulators and student operators within the SHEEP study. As a follow up research, this study experimentally investigates students’ learning effects and the performance trends over a certain period when using Rancor. This study aims to find out 1) how much training or education is required to collect HRA data from non-experts (i.e., students) when using Rancor and 2) how much differences there are in human performance measures between students and professional operators. In this study, a longitudinal experiment is developed. The four experiment trials with two weeks interval are carried out for sixteen undergraduate students majoring nuclear engineering at Chosun University. Totally four scenarios randomly selected from ten Rancor scenarios are used in each experiment trial. Four human performance measurements (i.e., workload, situation awareness, time and error) are considered in the experiment. Lastly, the trend of students’ performance is compared with operator data having been collected from the previous experiment.
This study, as a previous study of the SHEEP project, aims to identify differences in human performance data through experiments with students and operators using CNS (Compact Nuclear Simulator). To achieve this goal, this experiment seeks to analyze the correlation of measured human performance between students and operators through a randomized factorial experiment design. Five human performances are measured. In addition, several scenarios and related procedures have been developed for the CNS experiments.
Human reliability analysis (HRA) evaluates human errors and provides human error probabilities (HEPs) for application in probabilistic safety assessment (PSA), which is a comprehensive safety assessment method for nuclear power plants (NPPs). Generally, HRA methods estimate HEPs based on human reliability data collected from actual historical measurement, simulator experiments, or expert judgement. Most recent HRA data collection studies focus on collecting data via full-scope main control room (MCR) simulators with actual licensed reactor operators. Contrary to this, Idaho National Laboratory (INL) has adopted a different approach, which attempts to collect HRA data based on experiment using simplified simulators and student participants by following the Simplified Human Error Experimental Program (SHEEP). This approach has a couple of advantages compared to full-scope data collection. Representatively, it has relatively low entry point for collecting HRA data, and secures large sample sizes with reasonable cost and labor. In the previous studies, we developed the SHEEP framework, then verified whether the data collected through the framework could support a representative full-scope data collection study, i.e., the Human Reliability Data Extraction (HuREX) study. Also, we analyzed human performance measurements depending on participant type (i.e., student vs. operator). In this paper, we analyze human performance data collected from an experiment comparing operator expertise and simulator complexity when using the more simplified simulator developed by INL, i.e., Rancor Microworld and the less simplified simulator, i.e., Compact Nuclear Simulator (CNS) developed by Korea Atomic Energy Research Institute (KAERI). Analysis of variance (ANOVA) tests and correlation analysis are used for analyzing the experimental data.
Digital readout of code transformation task to measure human performance in man machine systems