摘要
管制疲劳已成为影响民航安全运行的重要影响因素。为实时检测管制疲劳,积极进行疲劳预警,应用多元回归方法建立了眼动指标与疲劳的预测模型。通过利用眼动仪采集模拟管制实验中被试分别在正常与疲劳状态下的各项实验数据,并记录其主观疲劳程度。实验结果表明,被试的扫视速度、闪光临界融合频率(CFF)、眼闭合时间比例和瞳孔直径在疲劳前后存在显著差异,且与疲劳均呈较强相关;所建立的多元线性回归模型对管制疲劳的预测准确率为68.75%。本研究可以作为管制疲劳的检测和预警的技术储备措施,对保障民航安全具有重要意义。
Air traffic controllers fatigue has become a major factor affecting the safety of civil aviation.In order to detect air traffic controllers fatigue real time and carry out fatigue early warning,a prediction model of eye movement index and air traffic controllers fatigue based on multiple regression method were built.The experimental data of subjects in the normal and fatigue state were collected by using the eye tracker,and the subjective degree of fatigue of subjects was recorded.The experimental results show that the saccade speed,the CFF,the percentage of eyelid closure time and the pupil diameter of subjects in the normal and fatigue state are significantly different and each index has a strong correlation with fatigue.The accuracy of the multiple linear regression model is 75%.This study can be used as technical method to detect and early warn fatigue,which is of great significance to the security of civil aviation.
作者
陈斌
朱国蕾
靳慧斌
CHEN Bin;ZHU Guo-lei;JIN Hui-bin(The Flight Technology College,Civil Aviation University of China,Tianjin 300300,China;The General Aviation College,Civil Aviation University of China,Tianjin 300300,China)
出处
《科学技术与工程》
北大核心
2018年第25期300-304,共5页
Science Technology and Engineering
基金
中央高校基金(3122016F003)资助
关键词
空中交通管制
疲劳检测
眼动
多元回归分析
air traffic control
fatigue detection
eye movement
multiple regression analysis
