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Some of the issues and equations involved in predicting closed-loop man machine performance for situations in which the human operators' knowledge of the system and/or environment are imperfect are presented and discussed. Several examples to demonstrate some of the effects to be expected when such is the case are then given.
Rapid transportation of human crews to destinations throughout the solar system will require propulsion systems having not only very high exhaust velocities (i.e., I(sub sp) >= 10(exp 4) to 10(exp 5) sec) but also extremely low mass-power ratios (i.e., alpha <= 10(exp -2) kg/kW). These criteria are difficult to meet with electric propulsion and other power-limited systems, but may be achievable with propulsion concepts that use onboard power to produce a net gain in energy via fusion or some other nuclear process. This paper compares the fundamental performance of these gain-limited systems with that of power-limited systems, and determines from a generic power balance the gains required for ambitious planetary missions ranging up to 100 AU. Results show that energy gain reduces the required effective mass-power ratio of the system, thus enabling shorter trip times than those of power-limited concepts.
The primary purpose of the multiPOST tool is to enable the execution of much larger sets of vehicle cases to allow for broader trade space exploration. However, this exploration is not achieved solely with the increased case throughput. The multiPOST tool is applied to carry out a Design of Experiments (DOE), which is a set of cases that have been structured to capture a maximum amount of information about the design space with minimal computational effort. The results of the DOE are then used to fit a surrogate model, ultimately enabling parametric design space exploration. The approach used for the MAV study includes both DOE and surrogate modeling. First, the primary design considerations for the vehicle were used to develop the variables and ranges for the multiPOST DOE. The final set of DOE variables were carefully selected in order to capture the desired vehicle trades and take into account any special considerations for surrogate modeling. Next, the DOE sets were executed through multiPOST. Following successful completion of the DOE cases, a manual verification trial was performed. The trial involved randomly selecting cases from the DOE set and running them by hand. The results from the human analyst's run and multiPOST were then compared to ensure that the automated runs were being executed properly. Completion of the verification trials was then followed by surrogate model fitting. After fits to the multiPOST data were successfully created, the surrogate models were used as a stand-in for POST2 to carry out the desired MAV trades. Using the surrogate models in lieu of POST2 allowed for visualization of vehicle sensitivities to the input variables as well as rapid evaluation of vehicle performance. Although the models introduce some error into the output of the trade study, they were very effective at identifying areas of interest within the trade space for further refinement by human analysts. The next section will cover all of the ground rules and assumptions associated with DOE setup and multiPOST execution. Section 3.1 gives the final DOE variables and ranges, while section 3.2 addresses the POST2 specific assumptions. The results of the verification trials are given in section 4. Section 5 gives the surrogate model fitting results, including the goodness-of-fit metrics for each fit. Finally, the MAV specific results are discussed in section 6.
The use of fuzzy sets in modeling the human expert for certain Space Shuttle navigation problems is discussed with particular reference to onboard and ground console data monitoring tasks traditionally performed by astronauts and engineers. Specific problems include determining the quality of sensor data and of the filter state. The results obtained in this study indicate that fuzzy sets can be successfully used in modeling human reaction to rules in decision-making processes. They can also be used within software systems where guidelines have traditionally been used to set strict tolerances.
Turbulence modeling in human-in-the-loop simulation is important to assessing aircraft handling qualities and pilot performance and to provide additional realism for pilot training. In the simulation community, the Dryden turbulence spectra is a popular choice for modeling the linear turbulent gusts because its rational form is efficiently reproduced by passing white noise through linear filters. The MIL-F-8785 gust gradients similarly use additional linear filters to model the gradient of the turbulent gust over the wing, and it represents the gust gradients as perturbations to the air-relative rotational rates. The Cockpit Motion Facility at NASA Langley Research Center (LaRC) models continuous random turbulence using the Dryden one-dimensional spectra and MIL-F-8785 gust gradient. The facility recently reviewed and updated its verification of these models as part of an initiative to improve motion cueing under turbulence. This exercise introduced improved methods for verifying the turbulence models and led to rediscovery of model assumptions that informed improvements to implementation.
Dynamic model for effects of random scanning and sampling on human operator tracking performance
Odetics is investigating the use of the intensity dependent spread (IDS) model for determining color constancy. Object segmentation is performed effortlessly by the human visual systems, but creating computer vision that takes an image as input and performs object identification on the basis of color has some difficulties. The unknown aspects of the light illuminating a scene in space or anywhere can seriously interfere with the use of color for object identification. The color of an image depends not only on the physical characteristics of the object, but also on the wavelength composition of the incident illumination. IDS processing provides the extraction of edges and of reflectance changes across edges, independent of variations in scene illumination. IDS depends solely on the ratio of the reflectances on the two sides of the edge. Researchers are in the process of using IDS to recover the reflectance image.
The results of several experiments were disseminated during this semiannual period. This publication and each of these presented papers represent investigations of the continuity in psychological processes between monkeys and humans. Thus, each serves to support the animal model of behavior and performance research.
The results of several experiments were disseminated during this semiannual period. These publications and presented papers represent investigations of the continuity in psychological processes between monkeys and humans. Thus, each serves to support the animal model of behavior and performance research.
This report presents tile results of an experimental and analytical study of human performance in uncoupled and coupled control systems. Human pilot performance in single and two-axis systems was mathematically modeled by linear second-order describing functions. Model parameters were determined using model matching techniques. Analysis of the models showed that the amplitude ratio and phase lead of the describing function increased with training indicating an increase in open loop bandwidth. The phase margin also decreased with training. Increasing the plant lag time constant resulted in an increase in the model lead time constant and a decrease in the zero frequency gain. No significant difference was found to exist in the normalized tracking error per axis between the two-axis tasks and the single-axis tasks. However tile model lead time constant was significantly greater in two-axis tracking. Manual tracking of two-axis systems with cross-coupling was studied experimentally and analytically. Approximate methods for modeling two-axis performance were developed and checked using a precise spectral analysis approach. Coupled and uncoupled, symmetrical and asymmetrical two-axis performance was compared. The results show that modeling of cross-coupled systems is feasible and that trained subjects are capable of decoupling the axes of some systems. A methodology study compared the identification performance of continuous, iterative, and extrapolation model matching techniques. An iterative technique employing sensitivity equations for the generation of influence coefficients was found to be the best technique due to its excellent identification accuracy and ease of implementation. Convergence in iterative techniques can be improved substantially by equalizing the parameter adjustment rates and limiting the maximum correction per iteration.
With the increase in the amount of time spent EVA that is necessary to complete the construction and subsequent maintenance of ISS, it will become increasingly important for ground support personnel to accurately characterize the radiation exposures incurred by EVA crewmembers. Since exposure measurements cannot be taken within the organs of interest, it is necessary to estimate these exposures by calculation. To validate the methods and tools used to develop these estimates, it is necessary to model experiments performed in a controlled environment. This work is such an effort. A human phantom was outfitted with detector equipment and then placed in American EMU and Orlan-M EVA space suits. The suited phantom was irradiated at the LLUPTF with proton beams of known energies. Absorbed dose measurements were made by the spaceflight operational dosimetrist from JSC at multiple sites in the skin, eye, brain, stomach, and small intestine locations in the phantom. These exposures are then modeled using the BRYNTRN radiation transport code developed at the NASA Langley Research Center, and the CAM (computerized anatomical male) human geometry model of Billings and Yucker. Comparisons of absorbed dose calculations with measurements show excellent agreement. This suggests that there is reason to be confident in the ability of both the transport code and the human body model to estimate proton exposure in ground-based laboratory experiments.
Conference report contains compilation of papers relating to interactions between humans and machines from perspectives of telepresence and sensorimotor adaptation, measurement and evaluation of performance, and design principles and predictive models. Topics discussed include neural networks, sensory technology, display, and feedback controls. Covers state of art of remote sensing and control by humans for space or other operations.
The Anthropometry and Biomechanics Laboratory (ABL) at JSC conducts multi-disciplinary research focusing on maximizing astronaut intravehicular (IVA) and extravehicular (EVA) capabilities to provide the most effective work conditions for manned space flight and exploration missions. Biomechanics involves the measurement and modeling of the strength characteristics of the human body. Current research for the Space Shuttle Program includes the measurement of torque wrench capability during weightlessness, optimization of foot restraint, and hand hold placement, measurements of the strength and dexterity of the pressure gloved hand to improve glove design, quantification of the ability to move and manipulate heavy masses (6672 N or 1500 lb) in weightlessness, and verification of the capability of EVA crewmembers to perform Hubble Space Telescope repair tasks. Anthropometry is the measurement and modeling of the dimensions of the human body. Current research for the Space Shuttle Program includes the measurement of 14 anthropometric parameters of every astronaut candidate, identification of EVA finger entrapment hazards by measuring the dimensions of the gloved hand, definition of flight deck reach envelopes during launch and landing accelerations, and measurement of anthropometric design parameters for the recumbent seat system required for the Shuttle/Mir mission (STS-71, Spacelab M) scheduled for Jun. 1995.
This paper describes the human engineering analysis performed on the Materials Science Research Rack-1 and Quench Module Insert (MSRR-1/QMI) using Transom Jack (Jack) software. The Jack software was used to model a virtual environment consisting of the MSRR-1/QMI hardware configuration and human figures representing the 95th percentile male and 5th percentile female. The purpose of the simulation was to assess the human interfaces in the design for their ability to meet the requirements of the Pressurized Payloads Interface Requirements Document - International Space Program, Revision C (SSP 57000). Jack was used in the evaluation because of its ability to correctly model anthropometric body measurements and the physical behavior of astronauts working in microgravity, which is referred to as the neutral body posture. The Jack model allows evaluation of crewmember interaction with hardware through task simulation including but not limited to collision avoidance behaviors, hand/eye coordination, reach path planning, and automatic grasping to part contours. Specifically, this virtual simulation depicts the human figures performing the QMI installation and check-out, sample cartridge insertion and removal, and gas bottle drawer removal. These tasks were evaluated in terms of adequate clearance in reach envelopes, adequate accessibility in work envelopes, appropriate line of sight in visual envelopes, and accommodation of full size range for male and female stature maneuverability. The results of the human engineering analysis virtual simulation indicate that most of the associated requirements of SSP 57000 were met. However, some hardware design considerations and crew procedures modifications are recommended to improve accessibility, provide an adequate work envelope, reduce awkward body posture, and eliminate permanent protrusions.
The development of models to represent human characteristics and behaviors in human factors is broad and general. The term "model" can refer to any metaphor to represent any aspect of the human; it is generally used in research to mean a mathematical tool for the simulation (often in software, which makes the simulation digital) of some aspect of human performance and for the prediction of future outcomes. This section is restricted to the application of human models in physical design, e.g., in human factors engineering. This design effort is typically human interface design, and the digital models used are anthropometric. That is, they are visual models that are the physical shape of humans and that have the capabilities and constraints of humans of a selected population. They are distinct from the avatars used in the entertainment industry (movies, video games, and the like) in precisely that regard: as models, they are created through the application of data on humans, and they are used to predict human response; body stresses workspaces. DHM enable iterative evaluation of a large number of concepts and support rapid analysis, as compared with use of physical mockups. They can be used to evaluate feasibility of escape of a suited astronaut from a damaged vehicle, before launch or after an abort (England, et al., 2012). Throughout most of human spaceflight, little attention has been paid to worksite design for ground workers. As a result of repeated damage to the Space Shuttle which adversely affected flight safety, DHM analyses of ground assembly and maintenance have been developed over the last five years for the design of new flight systems (Stambolian, 2012, Dischinger and Dunn Jackson, 2014). The intent of these analyses is to assure the design supports the work of the ground crew personnel and thereby protect the launch vehicle. They help the analyst address basic human factors engineering questions: can a worker reach the task site from the work platform provided; can she or he see the task site; can she or he control tools, which, if dropped, might damage the system? Figure 7.3.1 provides an example of such analysis for a future NASA launch vehicle. [figure 7.3.1 here] In-space systems for operation by astronauts have long been targets for DHM analysis, given the focus on mission success and concerns for astronaut safety. Figure 7.3.2 illustrates the analysis of the design to support astronaut tasks for an International Space Station glovebox. [Figure 7.3.2 here] Use by
Finite-state machines and evolutionary programming for representing and analyzing performance of human operator in control of dynamic systems
The study of distributed information processing and decision making is presently hampered by two factors: (1) The inherent complexity of the mathematical formulation of decentralized problems has prevented the development of models that could be used to predict performance in a distributed environment; and (2) The lack of comprehensive scientific empirical data on human team decision making has hindered the development of significant descriptive models. As a part of a comprehensive effort to find a new framework for multihuman decision making problems, a novel experimental research paradigm was developed involving human terms in decision making tasks. Attempts to construct parts of an integrated model with ideas from queueing networks, team theory, distributed estimation and decentralized resource management are described.
Human performance in visual detection, discrimination, identification, and search tasks typically improves with practice. Psychophysical studies suggest that perceptual learning is mediated by an enhancement in the coding of the signal, and physiological studies suggest that it might be related to the plasticity in the weighting or selection of sensory units coding task relevant information (learning through attention optimization). We propose an experimental paradigm (optimal perceptual learning paradigm) to systematically study the dynamics of perceptual learning in humans by allowing comparisons to that of an optimal Bayesian algorithm and a number of suboptimal learning models. We measured improvement in human localization (eight-alternative forced-choice with feedback) performance of a target randomly sampled from four elongated Gaussian targets with different orientations and polarities and kept as a target for a block of four trials. The results suggest that the human perceptual learning can occur within a lapse of four trials (<1 min) but that human learning is slower and incomplete with respect to the optimal algorithm (23.3% reduction in human efficiency from the 1st-to-4th learning trials). The greatest improvement in human performance, occurring from the 1st-to-2nd learning trial, was also present in the optimal observer, and, thus reflects a property inherent to the visual task and not a property particular to the human perceptual learning mechanism. One notable source of human inefficiency is that, unlike the ideal observer, human learning relies more heavily on previous decisions than on the provided feedback, resulting in no human learning on trials following a previous incorrect localization decision. Finally, the proposed theory and paradigm provide a flexible framework for future studies to evaluate the optimality of human learning of other visual cues and/or sensory modalities.