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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Man-machine Integration Design and Analysis System (MIDAS) Task Loading Model (TLM) experimental and software detailed design report

This is the experimental and software detailed design report for the prototype task loading model (TLM) developed as part of the man-machine integration design and analysis system (MIDAS), as implemented and tested in phase 6 of the Army-NASA Aircrew/Aircraft Integration (A3I) Program. The A3I program is an exploratory development effort to advance the capabilities and use of computational representations of human performance and behavior in the design, synthesis, and analysis of manned systems. The MIDAS TLM computationally models the demands designs impose on operators to aide engineers in the conceptual design of aircraft crewstations. This report describes TLM and the results of a series of experiments which were run this phase to test its capabilities as a predictive task demand modeling tool. Specifically, it includes discussions of: the inputs and outputs of TLM, the theories underlying it, the results of the test experiments, the use of the TLM as both stand alone tool and part of a complete human operator simulation, and a brief introduction to the TLM software design.

Staveland, Lowell↗
NASA NTRS1970

Human Factors Systems SRT

Man machine concepts for remote control of unmanned planetary and lunar roving vehicles

Source record↗
NASA NTRS1983

Compensation for time delay in flight simulator visual-display systems

A piloted aircraft can be viewed as a closed-loop, man-machine control system. When a simulator pilot is performing a precision maneuver, a delay in the visual display of aircraft response to pilot-control input decreases the stability of the pilot-aircraft system. The less stable system is more difficult to control precisely. Pilot dynamic response and performance change as the pilot attempts to compensate for the decrease in system stability, and these changes bias the simulation results by influencing the pilot's rating of the handling qualities of the simulated aircraft. Delay compensation, designed to restore pilot-aircraft system stability, was evaluated in several studies which are reported here. The studies range from single-axis, tracking-task experiments (with sufficient subjects and trials to establish statistical significance of the results) to a brief evaluation of compensation of a computer-generated-imagery (CGI) visual display system in a full six-degree-of-freedom simulation. The compensation was effective - improvements in pilot performance and workload or aircraft handling-qualities rating (HQR) were observed. Results from recent aircraft handling-qualities research literature which support the compensation design approach are also reviewed.

Crane, D. F.↗
NASA NTRS1980

Intelligence control systems

The evolution of ideas of intelligent controls and their application to high level man machine interactive systems like general purpose manipulators, industrial robots, prosthetic devices for amputees, and orthotic devices for paralyzed persons are discussed. Some case studies are presented to demonstrate the feasibility of the approach.

Saridis, G. N.↗
DOE OSTI2023

A Human-Machine Shared Control Framework Considering Time-Varying Driver Characteristics

The uncertainties of driver's behavior seriously affect road safety and bring significant challenges to the human-machine cooperative control. Here, this paper proposes a human-machine shared control framework considering driver's time-varying characteristics to improve the co-driving cooperation performance. Firstly, the driving intention is introduced to describe the driver's involvement level through using Gauss-Bernoulli restricted Boltzmann machine method. And the index of driving ability is proposed to evaluate driver skills based on path-tracking errors. Then, a novel human-machine authority allocation strategy is designed by combining the two driving behavior characteristics and used to construct the driver-vehicle interaction system. Subsequently, a T-S fuzzy robust state-feedback shared control system is developed considering time-varying driver behaviors and vehicle states. Finally, the proposed shared steering system is validated by the driver-in-the-loop test bench. The results show that the proposed control method can reduce human-machine conflicts and has obvious superiority in improving performance of driving comfort, path tracking, and vehicle stability for the co-driving vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2003

A new method to evaluate human-robot system performance

One of the key issues in space exploration is that of deciding what space tasks are best done with humans, with robots, or a suitable combination of each. In general, human and robot skills are complementary. Humans provide as yet unmatched capabilities to perceive, think, and act when faced with anomalies and unforeseen events, but there can be huge potential risks to human safety in getting these benefits. Robots provide complementary skills in being able to work in extremely risky environments, but their ability to perceive, think, and act by themselves is currently not error-free, although these capabilities are continually improving with the emergence of new technologies. Substantial past experience validates these generally qualitative notions. However, there is a need for more rigorously systematic evaluation of human and robot roles, in order to optimize the design and performance of human-robot system architectures using well-defined performance evaluation metrics. This article summarizes a new analytical method to conduct such quantitative evaluations. While the article focuses on evaluating human-robot systems, the method is generally applicable to a much broader class of systems whose performance needs to be evaluated.

Space Flight/instrumentation↗
NASA NTRS1994

Crew systems: integrating human and technical subsystems for the exploration of space

Space exploration missions will require combining human and technical subsystems into overall "crew systems" capable of performing under the rigorous conditions of outer space. This report describes substantive and conceptual relationships among humans, intelligent machines, and communication systems, and explores how these components may be combined to complement and strengthen one another. We identify key research issues in the combination of humans and technology and examine the role of individual differences, group processes, and environmental conditions. We conclude that a crew system is, in effect, a social cyborg, a living system consisting of multiple individuals whose capabilities are extended by advanced technology.

NASA Discipline Space Human Factors↗
NASA NTRS1996

Effects of adaptive task allocation on monitoring of automated systems

The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.

Task Performance and Analysis↗