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Man-Machine Systems, IEEE Transactions on

Issue 2 • Date June 1968

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  • [Table of contents]

    Page(s): c1
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  • IEEE Man-Machine Systems Group

    Page(s): c2
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  • Evaluating Multidimensional Situations Using a Quasi-Separable Utility Function

    Page(s): 25 - 28
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    In this paper, a method for systematically assessing multidimensional situations is developed. More precisely, the psychophysical method of "interpolation between the corners" suggested by Yntema and Torgerson is formalized. It is proven that, subject to von Neumann and Morgenstern's axioms of "rational behavior" and the quasi-separability assumptions, the utility (or worth) of a multidimensional situation may be evaluated from sums and products of the utilities of single-dimensional situations. After developing the necessary methodology, a hypothetical problem is considered in order to illustrate the use of this approach and to indicate its potential for applications. View full abstract»

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  • An Intervehicular Spacing Display for Improved Car-Following Performance

    Page(s): 29 - 35
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    A driver's inability to detect small headway changes and small relative velocities is a primary reason for his poor car-following performance. This can be greatly improved if he is given information¿headway and relative velocity¿concerning the state of a lead car. This may be provided visually, tactually, or audibly. In the study reported, a control stick with a built-in kinesthetictactile display was tested in a car-following situation. Performances with this display were compared to those obtained when no aiding was used in a similar situation. Sizable reductions in velocity variance and headway variance were obtained for the aided case relative to the unaided case. These were obtained for headways of 23 feet at 30 mi/h and 33 feet at 40 mi/h. Thus, this display can be effectively used at short headways. View full abstract»

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  • Stochastic Modeling of Human Learning Behavior

    Page(s): 36 - 46
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    A stochastic model of human learning behavior in a manual control task is described. Regulation of the state of a double integral plant to minimize the integrated absolute error is the operator's task. Subjects given this task were instructed to drive the process from an initial state to the null state using a two-position relay controller and a visual display. A subject is conceptualized in the model as a sequential data-processing system. A sensor, a decision maker, and an effector are the three serially connected components making up the system. Each element requires a finite time to either process or transmit information, and thus a delay is incurred between the reception of the visual stimulus and the execution of a motor response. Response decisions are based on the a priori estimate of the probability that the control polarity should be switched, given the current state of the plant. Patterns in the resultant phase trajectory are used as evidence by the decision maker to revise the prior estimate with an algorithm according to Bayes' theorem. Behavior of this model is compared with subject behavior in the motor skill experiment, and the model's characterization of the time-varying random nature of human learning is brought out by this comparison. Also discussed are the applications of the concept of this model to other manual control tasks. View full abstract»

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  • Contributors

    Page(s): 48
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  • Statement of editorial policy

    Page(s): 48a
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  • Information for authors

    Page(s): 48a
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  • Institutional listings

    Page(s): 48b
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