Modeling air traffic controllers' decision making processes with relational complexity network
Modeling air traffic controllers' decision making processes with relational complexity network
复制标题
DOI：
10.1109/itsc.2014.6958116
复制
发表时间：
2014-10
期刊：
影响因子：
--
通讯作者：
Jingyu Zhang;Jinrui Ren;Changxu Wu
中科院分区：
文献类型：
--
作者：
Jingyu Zhang;Jinrui Ren;Changxu Wu
量化飞机交互复杂性和空中交通管制员决策过程之间的联系有助于开发合理的认知模型和有效的智能支持工具。本文从网络理论和认知机制出发，提出了一个新的关系复杂性网络框架，用以解释空中交通管制任务决策过程中的一些关键问题。在验证实验中，我们操纵了不同的飞机交互模式，发现管制员的工作量排序、冲突检测率、干预决策和任务完成时间都受到单机或飞机对在关系复杂性网络中的位置的显著影响。理论和实践的贡献进行了讨论。
Quantifying the link between aircraft interaction complexity and the decision making process of air traffic controllers can help developing sound cognitive models and effective intelligent supportive tools. In this paper, we introduced a new relational complexity network framework derived from network theory and cognitive mechanisms to explain some key aspects in the decisional processes of air traffic control tasks. In the validating experiment, we manipulated different aircraft interaction patterns and found that controllers' workload ranking, conflict detection rate, intervention decision and task completion time were significantly influenced by positions of single aircraft or aircraft pairs in the relational complexity network. Theoretical and practical contributions are discussed.