Situational awareness evaluation of flight trainees based on combined weighting cloud model

doi:10.16265/j.cnki.issn1003-3033.2025.10.0243

Abstract

Abstract:

In order to enhance the flight training capabilities of trainees, identify and evaluate flight trainees' situational awareness, an index system for evaluating flight trainees' situational awareness was established based on grounded theory. The combined weights were calculated using game theory to integrate subjective weights, which were determined by the G1 method, and objective weights, which were derived from the criteria importance through intercriteria correlation(CRITIC) method improved by the coefficient of variation method. Subsequently, a combined weighting cloud model was proposed: the digital characteristic values of the evaluation indices were input into a cloud generator to obtain situational awareness ratings, and the model was verified for the use of an example to evaluate the situation awareness of a flight trainee. The results indicate that the cloud model can comprehensively evaluate the situational awareness of flight trainees. The overall situational awareness of Trainee A was rated as excellent. Among the indicators, the flight discipline metric yielded the best evaluation result, contributing significantly to the maintenance of situational awareness. The flight operation skills metric was rated between the best and the poorest, while the professional knowledge indicator received the lowest score. Major deficiencies were identified in two primary evaluation indicators, emergency handling capability and adaptability to operational environments, which were found to adversely affect the maintenance of situational awareness.

Key words: flight trainee, situational awareness assessment, combination weighting, cloud model, flight training

CLC Number:

X949
V328.1

HAO Hongxun, ZHAO Zehai, HUANG Cheng, XU Jiahui. Situational awareness evaluation of flight trainees based on combined weighting cloud model[J]. China Safety Science Journal, 2025, 35(10): 36-43.

Figures/Tables 11

Table 1

Table 2

Table 3

Index system of factors influencing flight trainees' situational awareness

一级指标	二级指标
专业知识 $B 1$	知识储备与理解 $B 11$
	特情处理 $B 12$
	飞行经验 $B 13$
飞行操作 $B 2$	复杂信息处理 $B 21$
	多任务管理 $B 22$
	应急决策与执行 $B 23$
	沟通协作 $B 24$
	运行环境适应力 $B 25$
	飞行操作熟练度 $B 26$
	飞行状态监控 $B 27$
飞行作风 $B 3$	规章遵守及应用 $B 31$
	心理复原力 $B 32$
	注意力管理 $B 33$
	危机意识 $B 34$
	个性特征 $B 35$

Table 3

Table 4

Secondary indicator weighting values

指标	$η k$	$σ j$	组合权重
$B 11$	0.049 0	0.101 7	0.069 3
$B 12$	0.062 2	0.076 7	0.067 7
$B 13$	0.125 0	0.036 2	0.090 9
$B 21$	0.033 6	0.048 3	0.039 4
$B 22$	0.053 7	0.077 6	0.063 2
$B 23$	0.088 6	0.062 9	0.079 0
$B 24$	0.047 8	0.048 3	0.048 0
$B 25$	0.036 2	0.045 7	0.039 8
$B 26$	0.062 2	0.054 8	0.059 3
$B 27$	0.043 5	0.064 2	0.051 0
$B 31$	0.106 4	0.069 7	0.092 2
$B 32$	0.083 3	0.073 8	0.079 6
$B 33$	0.087 1	0.068 0	0.079 7
$B 34$	0.062 2	0.069 7	0.065 1
$B 35$	0.059 1	0.102 5	0.075 5
$B 1$	0.257 3	0.318 7	0.282 5
$B 2$	0.401 3	0.284 4	0.353 4
$B 3$	0.341 4	0.396 9	0.364 1

Table 4

Table 5

Evaluation class interval division and standard cloudy numerical features

等级	区间划分	$E x c$	$E n c$	$H e c$
优秀 $V 1$	(8.0,10.0]	10.00	1.031	0.183
较好 $V 2$	(6.0,8.0]	6.91	0.637	0.113
中等 $V 3$	(4.0,6.0]	5.00	0.394	0.070
较差 $V 4$	(2.0,4.0]	3.09	0.637	0.113
极差 $V 5$	(0,2.0]	0.00	1.031	0.183

Table 5

Table 6

Values of cloud digital eigenvalue for secondary indicators

二级指标	$E x h 2$	$E n h 2$	$H e h 2$	排序结果
$B 11$	8.016 7	0.292 4	0.127 9	5
$B 12$	7.794 4	0.188 7	0.163 8	3
$B 13$	8.188 9	0.297 1	0.110 6	8
$B 21$	8.205 6	0.338 9	0.126 8	9
$B 22$	8.166 7	0.408 5	0.096 8	7
$B 23$	8.477 8	0.372 9	0.151 3	11
$B 24$	8.122 2	0.337 3	0.114 4	6
$B 25$	7.655 6	0.329 6	0.040 7	2
$B 26$	7.966 7	0.441 0	0.109 4	4
$B 27$	8.772 2	0.623 6	0.061 2	14
$B 31$	8.483 3	0.506 0	0.064 3	12
$B 32$	7.594 4	0.190 3	0.068 4	1
$B 33$	8.438 9	0.280 1	0.125 7	10
$B 34$	8.605 5	0.312 6	0.044 3	13
$B 35$	8.783 3	0.529 2	0.106 2	15

Table 6

Table 7

Values of cloud digital eigenvalue for first-level indicators

一级指标	$E x h 1$	$E n h 1$	$H e h 1$
$B 1$	8.019 3	0.267 7	0.090 8
$B 2$	8.226 3	0.411 0	0.110 1
$B 3$	8.371 9	0.513 9	0.113 6

Table 7

Fig.1

Fig.2

Fig.3

Table 8

References 21

[1]	PARMAR S, THOMAS R P. Effects of probabilistic risk situation awareness tool (RSAT) on aeronautical weather-hazard decision making[J]. Frontiers in Psychology, 2020, 11:DOI:10.3389/FPSYG.2020.566780.
[2]	WEI Hengyang, ZHUANG Damin, WANYAN Xiaoru, et al. An experimental analysis of situation awareness for cockpit display interface evaluation based on flight simulation[J]. Chinese Journal of Aeronautics, 2013, 26(4): 884-889. doi: 10.1016/j.cja.2013.04.053
[3]	ENDSLEY M R. Situation awareness misconceptions and misunderstandings[J]. Journal of Cognitive Engineering & Decision Making, 2015, 9(1):4-32.
[4]	ENDSLEY M R. Measurement of situation awareness in dynamic systems[J]. Human Factors, 1995, 37(1):65-84. doi: 10.1518/001872095779049499
[5]	ENDSLEY M R. Toward a theory of situation awareness in dynamic systems[J]. Human Factors, 1995, 37(1):32-64. doi: 10.1518/001872095779049543
[6]	ENDSLEY M R, RADWIN R G. A systematic review and meta-analysis of direct objective measures of situation awareness: a comparison of SAGAT and SPAM[J]. Human Factors: The Journal of Human Factors and Ergonomics Society, 2021, 63(1):124-150. doi: 10.1177/0018720819875376
[7]	DURSO F T, HACKWORTH C A, TRUITT T R, et al. Situation awareness as a predictor of performance in en route air traffic controllers[J]. Air Traffic Control Quarterly, 1998, 6(1):1-20. doi: 10.2514/atcq.6.1.1
[8]	黄圣. 情景意识在飞行教学和训练中的重要性[J]. 中国高新区, 2017(2):74.
[9]	李秀易, 张荣昊, 陈曦. 民航飞行员情景意识理解偏差影响因素分析[J]. 中国民航飞行学院学报, 2024, 35(3):5-9,15.
	LI Xiuyi, ZHANG Ronghao, CHEN Xi. Analysis on the factors influencing the deviation of civil aviation pilots' situational awareness understanding[J]. Journal of Civil Aviation Flight University of China, 2024, 35(3):5-9,15.
[10]	MUEHLETHALER C M, KNECHT C P. Situation awareness training for general aviation pilots using eye tracking[J]. IFAC-PapersOnLine, 2016, 49(19): 66-71.
[11]	丁松滨, 谷倩倩. 航空公司飞行安全综合评估方法研究[J]. 航空工程进展, 2017, 8(4):381-387.
	DING Songbin, GU Qianqian. Research on comprehensive evaluation method of airline flight safety[J]. Advances in Aeronautical Science and Engineering, 2017, 8(4):381-387.
[12]	SAUS E, JOHNSEN H B, EID J, et al. Who benefits from simulator training: personality and heart rate variability in relation to situation awareness during navigation training[J]. Computers in Human Behavior, 2012, 28(4):1262-1268. doi: 10.1016/j.chb.2012.02.009
[13]	陈琳, 米永胜. 民航飞行学员核心胜任力模型构建研究[J]. 综合运输, 2022, 44(6):58-63.
	CHEN Lin, MI Yongsheng. Research on the construction of core competency model of civil aviation flight cadets[J]. China Transportation Review, 2022, 44(6):58-63.
[14]	罗凤娥, 赵琪, 齐放, 等. 基于CBTA的签派员岗位胜任力模型的构建研究[J]. 综合运输, 2021, 43(4):88-94,116.
	LUO Feng'e, ZHAO Qi, QI Fang, et al. Construction of dispatcher post competency model based on CBTA.[J]. China Transportation Review, 2021, 43(4):88-94,116.
[15]	郑秀梅, 田晓康, 罗茜, 等. 地方政府交通运输安全生产政策注意力研究[J]. 中国安全科学学报, 2023, 33(5):74-80. doi: 10.16265/j.cnki.issn1003-3033.2023.05.1778
	ZHENG Xiumei, TIAN Xiaokang, LUO Qian, et al. Research on attention of local government's transportation work safety policy[J]. China Safety Science Journal, 2023, 33(5):74-80. doi: 10.16265/j.cnki.issn1003-3033.2023.05.1778
[16]	陈双赢, 邬晓光, 韩伟, 等. 基于最小二乘的AHP-CRITIC组合赋权的砼梁桥技术状况指标权重确定[J]. 沈阳大学学报:自然科学版, 2024, 36(2):171-178.
	CHEN Shuangying, WU Xiaoguang, HAN Wei, et al. Determination of weights of concrete girder bridge technical condition indicators based on least squares AHP-CRITIC combination assignment[J]. Journal of Shenyang University:Natural Science, 2024, 36(2):171-178.
[17]	ZHOU Zhiyong, KIZIL M, CHEN Zhong, et al. A new approach for selecting best development face ventilation mode based on G1-coefficient of variation method[J]. Journal of Central South University, 2018, 25(10): 2462-2471. doi: 10.1007/s11771-018-3929-y
[18]	聂兴信, 高赵祥, 刘哲伟, 等. 基于组合赋权法-云模型的采矿工作面热湿度风险等级评定[J]. 安全与环境学报, 2022, 22(4):1957-1969.
	NIE Xingxin, GAO Zhaoxiang, LIU Zhewei, et al. Study on evaluation of heat and humidity risk level of mining face based on combination weighting method and cloud model[J]. Journal of Safety and Environment, 2022, 22(4):1957-1969.
[19]	毕娟, 李希建. 基于博弈论组合赋权灰靶模型的煤矿安全综合评价[J]. 中国安全生产科学技术, 2019, 15(7):113-118.
	BI Juan, LI Xijian. Comprehensive evaluation of coal mine safety based on grey target model with combination weighting of game theory[J]. Journal of Safety Science and Technology, 2019, 15(7):113-118.
[20]	田延飞, 周欣蔚, 陈立家, 等. 水上通航环境危险度云模型及其应用[J]. 浙江海洋大学学报:自然科学版, 2021, 40(6):547-554.
	TIAN Yanfei, ZHOU Xinwei, CHEN Lijia, et al. Risk cloud model and an application for evaluation of nautical navigational environment[J]. Journal of Zhejiang Ocean University:Natural Science, 2021, 40(6):547-554.
[21]	钟虹, 何沙. 基于贝叶斯网络的连续管作业人因失误风险因素评价分析[J]. 中国安全生产科学技术, 2023, 19(5):144-150.
	ZHONG Hong, HE Sha. Evaluation and analysis on risk factors of human error in coiled tubing operation based on Bayesian network[J]. Journal of Safety Science and Technology, 2023, 19(5):144-150.

原始编码材料	基本概念	基本范畴
B-9518号飞机起飞后发动机转速下降,机组意识到发动机异常。因一边跑道施工,且发动机未完全失去动力,机组决定提前转弯试图尽早返场或寻找更合适迫降场地	处在飞机发动机失效、跑道环境复杂情况下的进近决策失误	特情决策能力
本次事故发生的直接原因为飞行教员在实施夜间目视返场过程,机组未对山区地形保持有效目视,未采取安全的越障飞行动作	对关键任务没有保持有效关注	注意力分配
︙	︙	︙

二级评价指标	基本范畴
特情处理能力	特情决策能力;特情处理及时性;特情评价正确性
复杂信息处理能力	复杂信息整合;未来状况预判
运行环境适应力	外界天气情况;特殊天气处置;非常规环境
飞行操作熟练度	操作准确程度;持续培训;非期望航空器状态
个性特征	粗心大意;过于主观
危机意识程度	安全意识薄弱;警觉意识
心理复原力	不良心态;操作压力;精神压力;自信心建立
注意力管理	注意力分配合理性;注意力集中程度
飞行知识储备与理解	专业知识积累;飞行知识覆盖广
机组沟通协作能力	有效沟通;团队协作;沟通受阻
规章遵守及应用	严格执行SOP;交叉检查;标准程序执行准确性;飞行前准备工作
飞行经验累积程度	操作经验少;飞行经验少
飞行状态监控能力	飞行状态掌握情况;机械故障;飞行状态动态调节
多任务管理能力	多任务并行操作;工作分配不当
应急决策能力	错误决策;犹豫不决