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海军舰艇控制中心的认知任务负荷:从识别到预测

Cognitive task load in a naval ship control centre: from identification to prediction.

作者信息

Grootjen M, Neerincx M A, Veltman J A

机构信息

Defence Materiel Organization, Directorate Materiel Royal Netherlands Navy, Department of Naval Architecture and Marine Engineering, The Hague, The Netherlands.

出版信息

Ergonomics. 2006;49(12-13):1238-64. doi: 10.1080/00140130600612705.

Abstract

Deployment of information and communication technology will lead to further automation of control centre tasks and an increasing amount of information to be processed. A method for establishing adequate levels of cognitive task load for the operators in such complex environments has been developed. It is based on a model distinguishing three load factors: time occupied, task-set switching, and level of information processing. Application of the method resulted in eight scenarios for eight extremes of task load (i.e. low and high values for each load factor). These scenarios were performed by 13 teams in a high-fidelity control centre simulator of the Royal Netherlands Navy. The results show that the method provides good prediction of the task load that will actually appear in the simulator. The model allowed identification of under- and overload situations showing negative effects on operator performance corresponding to controlled experiments in a less realistic task environment. Tools proposed to keep the operator at an optimum task load are (adaptive) task allocation and interface support.

摘要

信息与通信技术的部署将导致控制中心任务的进一步自动化以及需要处理的信息量不断增加。已开发出一种方法,用于在此类复杂环境中为操作员建立适当水平的认知任务负荷。该方法基于一个区分三个负荷因素的模型:占用时间、任务集切换和信息处理水平。该方法的应用产生了针对八种极端任务负荷情况(即每个负荷因素的低值和高值)的八个场景。这些场景由13个团队在荷兰皇家海军的高保真控制中心模拟器中执行。结果表明,该方法能很好地预测模拟器中实际出现的任务负荷。该模型能够识别对操作员绩效产生负面影响的负荷不足和过载情况,这与在不太现实的任务环境中进行的对照实验相对应。建议用于使操作员保持最佳任务负荷的工具是(自适应)任务分配和界面支持。

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