流体力学与飞行力学

空中交通管制员的眼动行为与疲劳关系

  • 卜建 ,
  • 刘银鑫 ,
  • 王艳军
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  • 南京航空航天大学 民航学院 国家空管飞行流量管理技术重点实验室, 南京 211106

收稿日期: 2017-05-25

  修回日期: 2017-07-07

  网络出版日期: 2017-07-07

基金资助

国家自然科学基金(61304190);江苏省自然科学基金(BK20130818)

Relationship between air traffic controllers' eye movement and fatigue

  • BU Jian ,
  • LIU Yinxin ,
  • WANG Yanjun
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  • National Key Laboratory of Air Traffic Flow Management, College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Received date: 2017-05-25

  Revised date: 2017-07-07

  Online published: 2017-07-07

Supported by

National Natural Science Foundation of China (61304190); Natural Science Foundation of Jiangsu Province (BK20130818)

摘要

在空中交通管制工作中,管制疲劳程度度量是一项需要长期研究的重要课题。实时测量管制员的疲劳程度,对航空运输系统的安全运行有重要意义。提出以眼动行为特征指标作为反映管制员疲劳程度的依据,利用faceLAB 5.0系统记录了管制员在正常状态和疲劳状态下进行管制模拟实验的眼动数据和绩效数据,分析了管制员的绩效数据与眨眼频率和瞳孔直径两种眼动指标在不同状态下的变化规律。研究发现与正常状态相比,管制员在疲劳状态下的眨眼频率增加,瞳孔直径减小。随着任务时间的增加,被试的绩效变差,眨眼频率增加,瞳孔直径减小,表明被试的工作状态从正常状态转为疲劳状态。统计分析结果说明,眨眼频率和瞳孔直径能够有效地检测管制员的疲劳状态,充分刻画不同工作时段管制员工作状态的变化,为开发实用的疲劳监测系统提供理论基础。

本文引用格式

卜建 , 刘银鑫 , 王艳军 . 空中交通管制员的眼动行为与疲劳关系[J]. 航空学报, 2017 , 38(S1) : 721525 -721525 . DOI: 10.7527/S1000-6893.2017.721525

Abstract

The assessment of air traffic controllers' fatigue is an important research topic which needs sustainable efforts. The real-time measurement of controller's fatigue has important implications for the safe operation of air transport system. This paper proposes to use eye movements to measure air traffic controllers fatigue, in which the eye movement data in normal and fatigue states are collected using faceLAB5.0 system. The performance data, eye blink frequency, and pupil diameter of the controllers are compared and analyzed. The experiment results show that compared with normal state when controller felt fatigue (i) blink frequency is increased; (ii) the pupil diameter is reduced. With the increase of task time, the performance of the subjects deteriorate, the blink frequency increase, and the pupil diameter decrease, indicating the changing of working state from normal state to fatigue state. The study shows that blink frequency and pupil diameter can effectively indicate fatigue state of the controller and can fully depict the influence of different working periods on the working status of the controller, and thus provides a theoretical basis for developing a practical fatigue monitoring system.

参考文献

[1] GUZZETT J B. FAA's controller scheduling practices can impact human fatigue, controller performance, & agency costs[R]. Washington, D.C.: FAA, 2013.
[2] PAPE A M, WIEGMANN D A, SHAPPELL S. Air traffic control (ATC) related accidents and incidents: A human factors analysis[C]//Proceeding of 11th International Symposium on Aviation Psychology, 2001: 1-4.
[3] GANDER P. Fatigue management in air traffic control: The New Zealand approach[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2001, 4(1): 49-62.
[4] 牛清宁, 周志强, 金立生. 基于眼动特征的疲劳驾驶检测方法[J]. 哈尔滨工程大学学报, 2015, 36(3): 394-398. NIU Q N, ZHOU Z Q, JIN L S. Detection of driver fatigue based on eye movements[J]. Journal of Harbin Engineering University, 2015, 36(3): 394-398(in Chinese).
[5] KECKLUND G, AKERSTEDT T. Sleepiness in long distance truck driving: An ambulatory EEG study of night driving[J]. Ergonomics, 1993, 36(9): 1007-1017.
[6] LAL S, CRAIG A. Physiological indicators of driver fatigue[C]//Road Safely Research, Policing and Education Conference, 2000: 489-494.
[7] 杨渝书, 姚振强, 李增勇. 心电图时频域指标在驾驶疲劳评价中的有效性研究[J]. 机械设计与制造,2002(5): 94-95. YANG Y S, YAO Z Q, LI Z Y. Investigation on correlation between ECG indexes and driving fatigue[J]. Machinery Design & Manufacture, 2002(5): 94-95(in Chinese).
[8] 毛科俊, 赵晓华, 刘小明. 基于脑电分析的驾驶疲劳预报研究[J]. 人类工效学, 2009, 15(4): 25-29. MAO K J, ZHAO X H, LIU X M. The study of driver fatigue prediction based on the EGG analysis[J]. Ergonomics, 2009, 15(4): 25-29(in Chinese).
[9] STERN J A, BOYER D,SCHROEDER D. Blink rate: A possible measure of fatigue[J]. Huma Factors, 1994, 36(2): 285-297.
[10] SCHLEICHER R, GALLEY N, BRIEST S, et al. Blinks and saccades as indicators of fatigue in sleepiness warnings: Looking tired?[J]. Ergonomics, 2008, 51(7): 982-1010.
[11] IQBAL S T, BAILEY B P. Using eye gaze patterns to identify user tasks [C]//The Grace Hopper Celebration of Women in Computing, 2004: 1-6.
[12] HAISONG G, QIANG J. An automated face reader for fatigue detection[C]//2004 Proceedings Sixth IEEE International Conference on Automatic Face and Gesture Recognition. Piscataway, NJ: IEEE Press, 2004: 111-116.
[13] DI S L, MCCAMY M B, CATENA A, et al. Microsaccade and drift dynamics reflect mental fatigue[J]. European Journal of Neuroscience, 2013, 38(3): 2389-2398.
[14] VAN ORDEN K F, JUNG T P, MAKEIG S. Combined eye activity measures accurately estimate changes in sustained visual task performance[J]. Biological Psychology, 2000, 52(3): 221-240.
[15] 汪磊, 孙瑞山. 基于面部特征识别的管制员疲劳监测方法研究[J]. 中国安全科学学报, 2012, 22(7): 66-71. WANG L, SUN R S. Study on face feature recognition-based fatigue monitoring method for air traffic controller[J]. China Safety Science Journal, 2012, 22(7): 66-71(in Chinese).

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