Human activity under high pressure: A case study on fluctuation scaling of air traffic controller's communication behaviors
Human activity under high pressure: A case study on fluctuation scaling of air traffic controller's communication behaviors
复制标题
高压下的人类活动：空中交通管制员通信行为波动尺度的案例研究
DOI：
10.1016/j.physa.2015.08.040
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发表时间：
2016-01-01
影响因子：
3.3
通讯作者：
Vu Duong
中科院分区：
文献类型：
--
作者：
Wang, Yanjun;Zhang, Qiqian;Vu Duong
最近的人类动力学研究揭示了惊人的统计特征，如人类日常活动中的缩放行为。然而，对管理特定任务活动的一般机制知之甚少。特别是，在高压下人类活动是否存在标度律仍然是一个悬而未决的问题。在空中交通管理系统中，安全是空中交通管制员最关心的问题，他们总是在高压力下工作，这为研究人类活动提供了一个独特的平台。本文将波动尺度法推广到空中交通管制员的沟通行为研究中，并通过两个经验性的沟通数据集进行了实证分析。以控制航班的数量作为大小参数，我们表明，在两个数据集的平均通信活动和它的标准差之间的关系可以很好地描述泰勒的幂律，与标度指数α近似为0.77 +/- 0.01的真实的操作数据和α近似为0.54 +/- 0.01的实时训练数据。指数之间的差异表明，压力下的人类动力学更可能由外源力主导。我们的发现可能会导致对人类行为的进一步理解。(C)2015 Elsevier B. V.版权所有。
Recent human dynamics research has unmasked astonishing statistical characteristics such as scaling behaviors in human daily activities. However, less is known about the general mechanism that governs the task-specific activities. In particular, whether scaling law exists in human activities under high pressure remains an open question. In air traffic management system, safety is the most important factor to be concerned by air traffic controllers who always work under high pressure, which provides a unique platform to study human activity. Here we extend fluctuation scaling method to study air traffic controller's communication activity by investigating two empirical communication datasets. Taken the number of controlled flights as the size-like parameter, we show that the relationships between the average communication activity and its standard deviation in both datasets can be well described by Taylor's power law, with scaling exponent alpha approximate to 0.77 +/- 0.01 for the real operational data and alpha approximate to 0.54 +/- 0.01 for the real-time training data. The difference between the exponents suggests that human dynamics under pressure is more likely dominated by the exogenous force. Our findings may lead to.further understanding of human behavior. (C) 2015 Elsevier B.V. All rights reserved.