Modeling air traffic controllers' decision making processes with relational complexity network

被引：0

作者：

Zhang, Jingyu ^{[1
]}

Ren, Jinrui ^{[2
]}

Wu, Changxu ^{[3
]}

机构：

[1] Chinese Acad Sci, Inst Psychol, Key Lab Behav Sci, Beijing 100864, Peoples R China

[2] Beijing Normal Univ, Dept Psychol, Beijing 100875, Peoples R China

[3] SUNY Buffalo, Dept Ind Engn, Buffalo, NY 14260 USA

来源：

2014 IEEE 17TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC) | 2014年

关键词：

relational complexity network; decision making; air traffic control; cognitive modeling; workload; CONFLICT DETECTION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：2663 / 2668

页数：6

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