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停留时间与飞行方向对飞行员警觉性的影响

李敬强 胡超 张希凝 张璐 刘安南

李敬强,胡超,张希凝,等. 停留时间与飞行方向对飞行员警觉性的影响[J]. 北京航空航天大学学报,2024,50(10):3054-3061 doi: 10.13700/j.bh.1001-5965.2022.0777
引用本文: 李敬强,胡超,张希凝,等. 停留时间与飞行方向对飞行员警觉性的影响[J]. 北京航空航天大学学报,2024,50(10):3054-3061 doi: 10.13700/j.bh.1001-5965.2022.0777
LI J Q,HU C,ZHANG X N,et al. Influence of layover length and flight direction on pilots’ alertness[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(10):3054-3061 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0777
Citation: LI J Q,HU C,ZHANG X N,et al. Influence of layover length and flight direction on pilots’ alertness[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(10):3054-3061 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0777

停留时间与飞行方向对飞行员警觉性的影响

doi: 10.13700/j.bh.1001-5965.2022.0777
基金项目: 国家自然科学基金与民航局联合基金(U1933122); 中央高校基本科研业务费专项资金(3122019186)
详细信息
    通讯作者:

    E-mail:jqli@cauc.edu.cn

  • 中图分类号: X949

Influence of layover length and flight direction on pilots’ alertness

Funds: The Civil Aviation Administration Joint Funds of the National Natural Science Foundation of China (U1933122); The Fundamental Research Funds for the Central Universities (3122019186)
More Information
  • 摘要:

    基于疲劳风险管理系统的应用正在全球航空业中迅速展开,在防疫豁免期间,收集实际运行模式下64名国际豁免航班飞行员在不同中转停留时间下的主观自评、客观测试和睡眠信息等数据。运用SPSS27.0统计学软件,利用相关性分析和重复测量方差分析的方法,深入地分析不同中转停留时间及飞行方向对国际豁免航班飞行员警觉性的影响,并用Origin软件绘制相关性系数图和半小提琴图。结果表明:停留时间为1~2 h时,国际豁免航班飞行员的警觉性水平明显较低,向东飞行的飞行员要比向西飞行的警觉性水平更低。这些发现有助于航空公司在防疫豁免运行环境中监测和分析国际豁免航班飞行员的警觉性,为加强中转航班过站保障措施提供借鉴。

     

  • 图 1  ActiLife软件界面

    Figure 1.  Interface of ActiLife software

    图 2  安全性能指标之间的相关系数

    Figure 2.  Correlation coefficient of safety performance indicators

    图 3  不同停留时间的KSS自评评分

    Figure 3.  KSS ratings under different layover lengths

    图 4  不同停留时间的SP自评评分

    Figure 4.  SP ratings under different layover lengths

    图 5  不同停留时间的PVT fastest 10% of responses

    Figure 5.  Fastest 10% of responses of PVT under different layover lengths

    图 6  不同停留时间的PVT slowest 10% of responses

    Figure 6.  Slowest 10% of responses of PVT under different layover lengths

    图 7  不同停留时间的TST in 24 h

    Figure 7.  TST in 24 h under different layover lengths

    表  1  航班信息汇总

    Table  1.   Summary of flight informations

    航班 停留时间/h 飞行员人次 飞行方向 飞行时间/h 值勤时间/h 跨越时区/h
    洛杉矶−北京 1~2 6 西飞 12.81 ± 1.77 13.53 ± 1.61 −16
    洛杉矶−北京 2~3 12 西飞 13.60 ± 1.55 13.82 ± 1.59 −16
    洛杉矶−北京 3~4 9 西飞 13.17 ± 1.90 13.81 ± 2.19 −16
    洛杉矶−北京 4~5 5 西飞 13.04 ± 1.57 14.32 ± 2.27 −16
    阿姆斯特丹−北京 1~2 6 东飞 11.54 ± 0.61 11.62 ± 0.68 +7
    阿姆斯特丹−北京 2~3 9 东飞 11.46 ± 0.65 12.08 ± 0.69 +7
    阿姆斯特丹−北京 3~4 10 东飞 11.40 ± 0.43 11.94 ± 0.53 +7
    阿姆斯特丹−北京 4~5 7 东飞 12.15 ± 0.16 13.01 ± 0.35 +7
    下载: 导出CSV

    表  2  KSS与SP相关性分析

    Table  2.   Correlation analysis of KSS and SP

    指标 相关系数R 显著性p
    KSS SP KSS SP
    KSS 1.000 0.874 0.000 0.000
    SP 0.874 1.000 0.000 0.000
    下载: 导出CSV

    表  3  主观自评与客观测试指标间的相关性分析

    Table  3.   Correlation analysis of subjective rating and objective test indicators

    指标类型 相关系数R 显著性p
    KSS SP KSS SP
    fastest 10% of responses 0.262 0.253 0.013 0.016
    slowest 10% of responses 0.227 0.240 0.032 0.023
    TST in 24 h −0.240 −0.326 0.023 0.002
    下载: 导出CSV

    表  4  双因素方差分析表

    Table  4.   Two-factor analysis of variance

    方差来源 平方和 自由度 均方 方差 效应量
    因素A $ {S_{ \mathrm{A}}} $ $ r - 1 $ $ {\overline {S} _{ \mathrm{A}}} = \dfrac{{{S_{ \mathrm{A}}}}}{{r - 1}} $ $ {F_{ \mathrm{A}}} = \dfrac{{{{\overline {S} }_{ \mathrm{A}}}}}{{{S_{ \mathrm{E}}}}} $ $ \eta _A^2 = \dfrac{{{S_{ \mathrm{A}}}}}{{{S_{ \mathrm{T}}} - {S_{ \mathrm{B}}} - {S_{{ \mathrm{A}} \times {\mathrm{B}}}}}} $
    因素B $ {S_{ \mathrm{B}}} $ $ s - 1 $ $ {\overline {S} _{ \mathrm{B}}} = \dfrac{{{S_{ \mathrm{B}}}}}{{s - 1}} $ $ {F_B} = \dfrac{{{{\overline {S} }_{ \mathrm{B}}}}}{{{S_{ \mathrm{E}}}}} $ $ \eta _B^2 = \dfrac{{{S_{ \mathrm{B}}}}}{{{S_{\mathrm{T}}} - {S_{ \mathrm{A}}} - {S_{{ \mathrm{A}} \times {\mathrm{B}}}}}} $
    交互作用A×B $ {S_{{ \mathrm{A}} \times {\mathrm{B}}}} $ $ \left( {r - 1} \right)\left( {s - 1} \right) $ $ {\overline {S} _{{ \mathrm{A}} \times {\mathrm{B}}}} = \dfrac{{{S_{{ \mathrm{A}} \times {\mathrm{B}}}}}}{{\left( {r - 1} \right)\left( {s - 1} \right)}} $ $ {F_{{ \mathrm{A}} \times {\mathrm{B}}}} = \dfrac{{{{\overline {S} }_{{ \mathrm{A}} \times {\mathrm{B}}}}}}{{{S_{ \mathrm{E}}}}} $ $ \eta _{{ \mathrm{A}} \times {\mathrm{B}}}^2 = \dfrac{{{S_{{ \mathrm{A}} \times {\mathrm{B}}}}}}{{{S_{ \mathrm{T}}} - {S_{ \mathrm{A}}} - {S_{ \mathrm{B}}}}} $
    误差 $ {S_{ \mathrm{E}}} $ $ rs\left( {t - 1} \right) $ $ {\overline {S} _{ \mathrm{E}}} = \dfrac{{{S_{ \mathrm{E}}}}}{{rs\left( {t - 1} \right)}} $
    总和 $ {S_{ \mathrm{T}}} $ $ rst - 1 $
    下载: 导出CSV

    表  5  方差分析结果

    Table  5.   Results from analysis of variance

    安全性能指标 F p η2
    飞行方向 停留时间 飞行方向与
    停留时间
    飞行方向 停留时间 飞行方向与
    停留时间
    飞行方向 停留时间 飞行方向与
    停留时间
    KSS 19.656 7.221 0.872 0.000 0.000 0.403 0.169 0.126 0.012
    SP 2.640 5.794 0.714 0.015 0.001 0.545 0.067 0.092 0.008
    fastest 10% of responses 11.302 2.751 0.522 0.001 0.043 0.667 0.141 0.063 0.006
    slowest 10% of responses 7.602 6.798 0.487 0.006 0.003 0.692 0.118 0.109 0.005
    TST in 24 h 6.224 2.524 0.679 0.013 0.045 0.613 0.105 0.062 0.007
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-09-14
  • 录用日期:  2022-12-04
  • 网络出版日期:  2022-12-27
  • 整期出版日期:  2024-10-31

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