From trees to forest: relational complexity network and workload of air traffic controllers

From trees to forest: relational complexity network and workload of air traffic controllers
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从树木到森林:关系复杂性网络和空中交通管制员的工作量

DOI:
10.1080/00140139.2015.1009498
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发表时间:
2015-02
期刊:
影响因子:
2.4
通讯作者:
Wu, Changxu
Wu, Changxu
中科院分区:
工程技术3区
文献类型:
--
作者:
Zhang, Jingyu;Yang, Jiazhong;Wu, Changxu

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在本文中,我们提出了一种基于 RC 度量和网络理论的关系复杂性(RC)网络框架,以对控制器在冲突检测和解决中的工作量进行建模。我们建议,在部门层面,呈现集中式网络模式的空中交通可以在视觉搜索和分辨率决策方面提供认知优势,从而减少工作量。我们发现,除了其他飞机级和配对级因素外,网络集中化指数可以在静态冲突检测任务(研究 1)和动态冲突检测任务(研究 2)中解释预测感知工作负载和任务完成时间的更多差异。这一发现表明,飞机级或二元级信息的线性组合可能不够,基于全局模式的索引是必要的。讨论了使用该框架改进未来工作负载建模和管理的理论和实践意义。从业者总结:我们提出了一个 RC 网络框架来模拟空中交通管制员的工作量。在静态冲突检测任务和动态冲突检测任务中检查了网络集中化的效果。与其他控制变量相比,网络集中化可以预测感知的工作负载和任务完成时间。
In this paper, we propose a relational complexity (RC) network framework based on RC metric and network theory to model controllers' workload in conflict detection and resolution. We suggest that, at the sector level, air traffic showing a centralised network pattern can provide cognitive benefits in visual search and resolution decision which will in turn result in lower workload. We found that the network centralisation index can account for more variance in predicting perceived workload and task completion time in both a static conflict detection task (Study 1) and a dynamic one (Study 2) in addition to other aircraft-level and pair-level factors. This finding suggests that linear combination of aircraft-level or dyad-level information may not be adequate and the global-pattern-based index is necessary. Theoretical and practical implications of using this framework to improve future workload modelling and management are discussed. Practitioner Summary: We propose a RC network framework to model the workload of air traffic controllers. The effect of network centralisation was examined in both a static conflict detection task and a dynamic one. Network centralisation was predictive of perceived workload and task completion time over and above other control variables.
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发表时间: 2001-06-01
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