A system for the assessment of human performance in concurrent verbal and manual control task

1978 ◽  
Author(s):  
Steven D. Harris ◽  
Robert A. North ◽  
Jerry M. Owens
2012 ◽  
Vol 6 (1) ◽  
pp. 57-87 ◽  
Author(s):  
Dietrich Manzey ◽  
Juliane Reichenbach ◽  
Linda Onnasch

Two experiments are reported that investigate to what extent performance consequences of automated aids are dependent on the distribution of functions between human and automation and on the experience an operator has with an aid. In the first experiment, performance consequences of three automated aids for the support of a supervisory control task were compared. Aids differed in degree of automation (DOA). Compared with a manual control condition, primary and secondary task performance improved and subjective workload decreased with automation support, with effects dependent on DOA. Performance costs include return-to-manual performance issues that emerged for the most highly automated aid and effects of complacency and automation bias, respectively, which emerged independent of DOA. The second experiment specifically addresses how automation bias develops over time and how this development is affected by prior experience with the system. Results show that automation failures entail stronger effects than positive experience (reliably working aid). Furthermore, results suggest that commission errors in interaction with automated aids can depend on three sorts of automation bias effects: (a) withdrawal of attention in terms of incomplete cross-checking of information, (b) active discounting of contradictory system information, and (c) inattentive processing of contradictory information analog to a “looking-but-not-seeing” effect.


1984 ◽  
Vol 28 (4) ◽  
pp. 398-402
Author(s):  
M. A. Montazer ◽  
Colin G. Drury

A model which describes human performance in a self-paced tracking task was developed based on the notion that human operators are intermittent-acting or sampled-data servo-mechanisms. The model had a functional form in terms of the probability of success and failure resulting from the execution of a manual control task such as drawing a line between fixed boundaries. The human operator was modelled as an optimizer, balancing costs and penalties of speeds and errors to achieve a maximum expected payoff. The performance of the model was evaluated by simulating a line drawing task on a digital computer. Model predictions obtained via simulation were compared with the data collected from human subjects performing the actual task in a laboratory setting. The predictions of the model were confirmed, suggesting that human operators can in fact be modelled as optimizers when performing a manual control task.


2011 ◽  
Author(s):  
Yukio Horiguchi ◽  
Keisuke Yasuda ◽  
Hiroaki Nakanishi ◽  
Tetsuo Sawaragi
Keyword(s):  

2018 ◽  
Vol 120 (6) ◽  
pp. 3187-3197 ◽  
Author(s):  
Marissa J. Rosenberg ◽  
Raquel C. Galvan-Garza ◽  
Torin K. Clark ◽  
David P. Sherwood ◽  
Laurence R. Young ◽  
...  

Precise motion control is critical to human survival on Earth and in space. Motion sensation is inherently imprecise, and the functional implications of this imprecision are not well understood. We studied a “vestibular” manual control task in which subjects attempted to keep themselves upright with a rotational hand controller (i.e., joystick) to null out pseudorandom, roll-tilt motion disturbances of their chair in the dark. Our first objective was to study the relationship between intersubject differences in manual control performance and sensory precision, determined by measuring vestibular perceptual thresholds. Our second objective was to examine the influence of altered gravity on manual control performance. Subjects performed the manual control task while supine during short-radius centrifugation, with roll tilts occurring relative to centripetal accelerations of 0.5, 1.0, and 1.33 GC (1 GC = 9.81 m/s2). Roll-tilt vestibular precision was quantified with roll-tilt vestibular direction-recognition perceptual thresholds, the minimum movement that one can reliably distinguish as leftward vs. rightward. A significant intersubject correlation was found between manual control performance (defined as the standard deviation of chair tilt) and thresholds, consistent with sensory imprecision negatively affecting functional precision. Furthermore, compared with 1.0 GC manual control was more precise in 1.33 GC (−18.3%, P = 0.005) and less precise in 0.5 GC (+39.6%, P < 0.001). The decrement in manual control performance observed in 0.5 GC and in subjects with high thresholds suggests potential risk factors for piloting and locomotion, both on Earth and during human exploration missions to the moon (0.16 G) and Mars (0.38 G). NEW & NOTEWORTHY The functional implications of imprecise motion sensation are not well understood. We found a significant correlation between subjects’ vestibular perceptual thresholds and performance in a manual control task (using a joystick to keep their chair upright), consistent with sensory imprecision negatively affecting functional precision. Furthermore, using an altered-gravity centrifuge configuration, we found that manual control precision was improved in “hypergravity” and degraded in “hypogravity.” These results have potential relevance for postural control, aviation, and spaceflight.


Author(s):  
Tarald O. Kvålseth

The effect of preview on human performance during a digital pursuit control task was analyzed for different preview spans and different characteristics of the reference input. The data from eight subjects revealed that the RMS error performance improved substantially from the case of no preview to that of one preview point, while the use of additional preview points did not result in any further significant performance improvement. The benefit of preview was most clearly established when the reference input was generated by a purely random process as opposed to a first-order autoregressive process (with the parameter α = 0.95). The RMS error increased when the variance of the reference input increased. The error appeared to be normally distributed with a tendency towards a negative bias.


1986 ◽  
Vol 30 (7) ◽  
pp. 684-688 ◽  
Author(s):  
K. B. Bennett ◽  
D. D. Woods ◽  
E. M. Roth ◽  
P. H. Haley

The operators of nuclear power plants are asked to perform a task that has proven to be particularly difficult: manual control of feedwater during startup. We have initiated a research and development program to address human factors issues related to this task. An analysis of cognitive aspects of the feedwater control task was used to develop a generic part-task simulator. New displays to enhance manual control performance (including a predictor display) were developed with the simulator. The test capability provided by the simulator allowed precise measurement of performance differences associated with these displays in a mixed-fidelity laboratory experiment. The results suggest that the displays reduced the complexity of the task and resulted in improved operator performance.


Author(s):  
Y. Horiguchi ◽  
K. Yasuda ◽  
H. Nakanishi ◽  
T. Sawaragi
Keyword(s):  

Author(s):  
Sang-Hwan Kim ◽  
David B. Kaber ◽  
Carlene M. Perry

The objective of this study was to assess the use of a computational cognitive model for describing human performance with an adaptively automated system, with and without advance cueing of control mode transitions. A dual-task piloting simulation was developed to collect human performance data under auditory cueing or no cueing of automated or manual control. GOMSL models for simulating user behavior were constructed based on a theory of increased memory transactions at mode transitions. The models were applied to the same task simulation and scenarios performed by the humans. Comparison of results on human and model output demonstrated the model to be generally descriptive of performance; however, it was not accurate in predicting timing of memory use in preparing for manual control. Interestingly, the human data didn't reveal differences between cued and no cue trials. A refined GOMSL model was developed by modifying assumptions on the timing and manner of memory use, and considering human parallel processing in dual-task performance. Results revealed the refined model to be more plausible for representing behavior. Computational cognitive modeling appears to be a viable approach to represent operator performance in adaptive systems.


2019 ◽  
Vol 13 (4) ◽  
pp. 295-309 ◽  
Author(s):  
Mary Cummings ◽  
Lixiao Huang ◽  
Haibei Zhu ◽  
Daniel Finkelstein ◽  
Ran Wei

A common assumption across many industries is that inserting advanced autonomy can often replace humans for low-level tasks, with cost reduction benefits. However, humans are often only partially replaced and moved into a supervisory capacity with reduced training. It is not clear how this shift from human to automation control and subsequent training reduction influences human performance, errors, and a tendency toward automation bias. To this end, a study was conducted to determine whether adding autonomy and skipping skill-based training could influence performance in a supervisory control task. In the human-in-the-loop experiment, operators performed unmanned aerial vehicle (UAV) search tasks with varying degrees of autonomy and training. At the lowest level of autonomy, operators searched images and, at the highest level, an automated target recognition algorithm presented its best estimate of a possible target, occasionally incorrectly. Results were mixed, with search time not affected by skill-based training. However, novices with skill-based training and automated target search misclassified more targets, suggesting a propensity toward automation bias. More experienced operators had significantly fewer misclassifications when the autonomy erred. A descriptive machine learning model in the form of a hidden Markov model also provided new insights for improved training protocols and interventional technologies.


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