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An Observer/Predictor-Based Model of the User for Attaining Situation Awareness

机译:基于观察者/预测变量的用户模型以实现态势感知

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摘要

Situation awareness (SA) is essential for the safe operation of systems involving human-automation interaction. In this paper, using the theory of functional observers, we model SA for the user interacting with a continuous-time linear time-invariant dynamical system. For systems under human control or shared control, we use the proposed model to determine the required information to be displayed in the user interface for achieving SA. The user interface provides the user with the ability to observe the continuous-time outputs of the system, as well as the ability to enter continuous-time control inputs. In some systems, due to inadequacy of the displayed information, the user may not be able to accomplish the desired task. To determine the required information to be displayed and the necessary states to be tracked, we propose a model of attaining SA for the users by modeling the user as a specific type of estimator (i.e., the extended delayed functional observer/predictor). We then evaluate what information is needed for such an estimator and how the desired functional of the states have to be expanded so that the user can precisely reconstruct and accurately predict the desired task. As an application example, we investigate the problem of controlling the depth of anesthesia during surgery and determine whether there exists a feasible combination of the expanded task and the displayed information that allows the anesthetist to precisely predict the depth of anesthesia of the patient.
机译:态势感知(SA)对于涉及人与自动化交互的系统的安全运行至关重要。在本文中,使用功能观察者理论,我们为用户与连续时间线性时不变动力系统交互的SA建模。对于在人为控制或共享控制下的系统,我们使用提议的模型来确定要在用户界面中显示以实现SA所需的信息。用户界面使用户能够观察系统的连续时间输出,以及输入连续时间控制输入的能力。在某些系统中,由于所显示信息的不足,用户可能无法完成所需的任务。为了确定要显示的必需信息和要跟踪的必要状态,我们提出了一种通过将用户建模为特定类型的估算器(即扩展的延迟功能观察器/预测器)来为用户获得SA的模型。然后,我们评估这种估计器需要哪些信息,以及如何扩展状态的期望功能,以便用户可以精确地重建和准确预测期望的任务。作为一个应用示例,我们研究了在手术过程中控制麻醉深度的问题,并确定是否存在扩展任务与显示信息的可行组合,以使麻醉师能够准确预测患者的麻醉深度。

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