管制员个体工作负荷多维量化研究

doi:10.16265/j.cnki.issn1003-3033.2024.06.1562

摘要/Abstract

摘要：

为提高空管系统高效运行,聚焦管制员个体工作负荷建立量化模型;首先设计试验采集一线16名区域管制员的岗前与岗后各项指标数据,根据测试数据变化,选择出敏感变量,描述个体工作负荷;其次建立包含心理感知负荷、生理反应负荷与脑力工作负荷3个维度的综合评估指标体系,构建管制员个体工作负荷指数模型;然后通过熵权-客观组合法求解个体工作负荷指数最优权重,最终得出管制员个体工作负荷量化模型;最后进一步根据管制员个体工作负荷综合指数进行K-Means聚类分析,结果表明:管制员因个体不同岗后工作负荷存在差异。依据个体工作负荷指数大小,管制员可分为3类,A类管制员数量占总人数50%,岗后个体工作负荷增长最小;B类管制员数量占总人数43.75%,岗后负荷增长居中;C类管制员数量占总人数6.25%,岗后负荷增长最大,与教员对管制员能力的评分结果一致。

关键词: 空中交通管制员, 个体工作负荷, 配对样本T检验, 熵权-客观组合法, K-Means聚类

Abstract:

In order to enhance the efficacious operation of the air traffic control system, a quantitative model was established by focusing on the individual load of controllers. Tests were designed to collect pre-service and post-service data on various indicators from 16 area controllers in the front line. Sensitive variables were selected to describe individual loads based on changes in test data. A comprehensive assessment index system was established that included three dimensions: psychological perception load, physiological reaction load, and mental workload. The controller individual load index model was developed. The optimal weights of the individual load index were determined by the the entropy-critic combination weighting method. The quantitative model of the controller's individual workload was finally derived. Further K-Means clustering analysis was performed based on the controller's individual load composite index. There were evident discrepancies in the workload changes of the controllers due to different individual postures. The results indicate that the post-post individual workload changes of the controllers could be classified into three distinct groups. The first group, comprising 50% of the total number of controllers, exhibited the smallest post-post individual workload growth. The second group, accounting for 43.75% of the total number of controllers, exhibited a moderate post-post individual workload growth. The third group, comprising 6.25% of the total number of controllers, exhibited the largest post-post individual workload increase. These findings align with the instructor's ratings of controller competence.

Key words: air traffic controller, individual workload, paired-sample T-test, entropy-critic combination weighting method, K-Means cluster analysis

中图分类号:

X949

王莉莉, 顾秋丽. 管制员个体工作负荷多维量化研究[J]. 中国安全科学学报, 2024, 34(6): 1-9.

WANG Lili, GU Qiuli. Study on multidimensional quantification of individual workload of controllers[J]. China Safety Science Journal, 2024, 34(6): 1-9.

图/表 14

图1

图2

表1

表2

图3

表3

图4

表4

脑力工作负荷指标岗前岗后配对样本T检验

认知负荷指标	配对差值					t	自由度	Sig.双尾
	平均值	标准偏差	标准误差平均值	差值 95%置信区间
	平均值	标准偏差	标准误差平均值	下限	上限
$F f ¯$	-38.017 19	28.742 92	7.185 73	-53.333 20	-22.701 17	-5.291	15	0.000
$T f ¯$	-40.115 06	63.004 32	15.751 08	-73.687 69	-6.542 42	-2.547	15	0.022
$S f ¯$	-8.097 09	8.938 15	2.234 54	-12.859 89	-3.334 29	-3.624	15	0.003

表4

表5

熵权法、客观权重法及组合法指标权重值

算法	$Δ L' P S S$	$Δ L' T L X$	$Δ β'$	$Δ K' S C L$	$Δ P' d$	$Δ F' f$	$Δ T' f$	$Δ S' f$
熵权法	0.104 8	0.073 7	0.088 8	0.112 4	0.072 7	0.153 3	0.238 8	0.155 5
CRITIC	0.126 2	0.124 6	0.139 0	0.113 4	0.100 7	0.139 5	0.120 5	0.136 1
组合算法	0.104 9	0.074 0	0.089 1	0.112 4	0.072 9	0.153 2	0.238 1	0.155 4

表5

表6

图5

图6

表7

图7

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主观量表	岗前岗后配对检验					t	自由度	Sig.双尾
	平均值	标准偏差	标准误差平均值	差值 95% 置信区间
	平均值	标准偏差	标准误差平均值	下限	上限
PSS	-2.875 00	4.814 91	1.203 73	-5.440 68	-0.309 32	-2.388	15	0.031
NASA-TLX	-14.875 00	8.196 54	2.049 14	-19.242 6	-10.507 3	-7.259	15	0.000

生理指标	配对差值					t	自由度	Sig.双尾
	平均值	标准偏差	标准误差平均值	差值 95%置信区间
	平均值	标准偏差	标准误差平均值	下限	上限
β波均值	1.896 76	2.655 50	0.663 87	0.481 75	3.311 78	2.857	15	0.012
皮肤导电均值	1.269 97	2.088 88	0.522 22	0.156 89	2.383 06	2.432	15	0.028
右眼瞳孔直径	-0.281 47	0.356 77	0.089 19	-0.471 58	-0.091 36	-3.156	15	0.007

编号	PPLI	PRIL	BWI	ILOI
01	0.074 4	0.192 7	0.203 9	0.471 0
02	0.105 4	0.163 9	0.243 1	0.512 4
03	0.138 1	0.149 6	0.089 3	0.377 0
04	0.077 3	0.144 0	0.217 4	0.438 7
05	0.044 2	0.126 7	0.252 4	0.423 2
06	0.127 5	0.186 4	0.083 0	0.396 9
07	0.108 0	0.137 0	0.227 4	0.472 4
08	0.117 7	0.086 2	0.267 1	0.471 0
09	0.115 6	0.109 0	0.128 5	0.353 1
10	0.099 5	0.146 2	0.319 8	0.565 4
11	0.096 5	0.172 3	0.233 5	0.502 3
12	0.066 3	0.124 5	0.198 5	0.389 3
13	0.062 9	0.113 2	0.238 2	0.414 4
14	0.159 8	0.174 6	0.088 4	0.422 8
15	0.107 1	0.154 3	0.468 7	0.730 2
16	0.108 0	0.130 2	0.248 7	0.486 9

编号	PPLI 占比/%	PRLI 占比/%	BWI 占比/%	ILOI	聚类种类
03	36.63	39.68	23.69	0.377 0	A
04	17.62	32.82	49.56	0.438 7	A
05	10.44	29.94	59.64	0.423 2	A
06	32.12	46.96	20.91	0.396 9	A
09	32.74	30.87	36.39	0.353 1	A
12	17.03	31.98	50.99	0.389 3	A
13	15.18	27.32	57.48	0.414 4	A
14	37.80	41.30	20.91	0.422 8	A
01	15.80	40.91	43.29	0.471 0	B
02	20.57	31.99	47.44	0.512 4	B
07	22.86	29.00	48.14	0.472 4	B
08	24.99	18.30	56.71	0.471 0	B
10	17.60	25.86	56.56	0.565 4	B
11	19.21	34.30	46.49	0.502 3	B
16	22.18	26.74	51.08	0.486 9	B
15	14.67	21.13	64.19	0.730 2	C