基于视觉因素的地铁调度人机界面优化设计评价

doi:10.11996/JG.j.2095-302X.2025010200

图学学报 ›› 2025, Vol. 46 ›› Issue (1): 200-210.DOI: 10.11996/JG.j.2095-302X.2025010200

基于视觉因素的地铁调度人机界面优化设计评价

李博¹(), 宣金鸽¹, 薛艳敏¹, 余隋怀¹^,², 王娟¹

1.西安理工大学艺术与设计学院，陕西西安 710054
2.西北工业大学工业设计与人机工效工业和信息化部重点实验室，陕西西安 710072

收稿日期:2024-05-22 接受日期:2024-09-14 出版日期:2025-02-28 发布日期:2025-02-14
第一作者:李博(1983-)，男，副教授，博士。主要研究方向为人机工效与交互设计、产品情感化设计与智能计算。E-mail：libo1983@xaut.edu.cn
基金资助:
国家社会科学基金一般项目(22BSH122);西安市科技计划项目(22GXFW0079);西安市软科学研究项目(23RKYJ0054)

Evaluation of optimal design of human-machine interface for subway dispatching based on visual factors

LI Bo¹(), XUAN Jinge¹, XUE Yanmin¹, YU Suihuai¹^,², WANG Juan¹

1. Faculty of Art and Design, Xi'an University of Technology, Xi'an Shaanxi 710054, China
2. Key Laboratory of Industrial Design and Ergonomics, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi'an Shaanxi 710072, China

Received:2024-05-22 Accepted:2024-09-14 Published:2025-02-28 Online:2025-02-14
First author：LI Bo (1983-), associate professor, Ph.D. His main research interests cover ergonomics and interaction, product emotional design and intelligent computing. E-mail：libo1983@xaut.edu.cn
Supported by:
National Social Science Foundation of China(22BSH122);Xi'an Science and Technology Project(22GXFW0079);Xi'an Soft Science Research Program(23RKYJ0054)

摘要/Abstract

摘要：

为了优化地铁调度员的任务绩效。以CATIA构建虚拟人体模型并进行视域等级划分，将调度界面和视域进行栅格化处理并构建人机布局优化模型，调度界面进行模块化处理并分析各模块的重要程度，以粒子群算法为基础引入惯性权重得出最优布局方案。以人机界面信息显示优化策略为准则，对人机界面的色彩、字体、图标进行优化设计，搭建眼动实验平台，选用AOI首次注视时间、AOI注视持续时间、AOI注视次数和AOI平均反应时及热点图作为人机界面任务绩效的判断指标。得到结果为：①人机布局优化模型布局设计将调度员注意力提升52%；②AOI首次注视时间、AOI注视持续时间和AOI平均反应时P值均小于0.05，具有显著性差异；优化后的调度界面AOI平均反应时提升50%；③AOI注视次数虽P值大于0.05，在统计学上无意义，但数据对比分析具有现实意义；④热点图符合视域的等级划分，眼动轨迹主要集中在最佳视域区域。通过构建的人机布局优化模型得出的布局方案和信息显示优化策略进行人机界面设计，有助于促使调度员注意力合理分配，提升调度员的任务绩效，为人机界面优化设计提供参考。

关键词: 地铁调度员, 人机界面, 眼动实验, 粒子群算法

Abstract:

To optimize the task performance of subway dispatchers, the method was to construct a virtual human model using CATIA and divide the view level. The scheduling interface and view were rasterized, and a human-machine layout optimization model was constructed. The scheduling interface was modularized, and the importance of each module was analyzed. Based on the particle swarm optimization algorithm, inertia weight was introduced to obtain the optimal layout plan. Based on the optimization strategy for human-machine interface information display, the color, font, and icon of the human-machine interface were optimized and designed. An eye-tracking experimental platform was built, with AOI first fixation time, AOI fixation duration, AOI fixation frequency, AOI average reaction time, and hotspot map selected as evaluation indicators for human-machine interface task performance. The results demonstrated that: ① The layout design obtained from the human-machine layout optimization model increased the dispatcher's attention by 52%. ② The first fixation time, AOI fixation duration, and AOI average reaction time all had P-values less than 0.05, indicating significant differences; the optimized scheduling interface achieved a 50% increase in average AOI response time. ③ Although the P-value of AOI fixation frequency was greater than 0.05 and lacked statistical significance, data comparison analysis revealed its practical significance. ④ The hotspot map conformed to the level divisions of the field of view, and eye tracking was mainly concentrated within the optimal field of view area. The layout scheme and information display optimization strategy derived from the constructed human-machine layout optimization model for human-machine interface design can facilitate the rational allocation of attention among dispatchers, enhance their task performance, and provide reference for optimizing human-machine interface design.

Key words: subway dispatcher, human machine interface, eye movement experiment, particle swarm algorithm

中图分类号:

李博, 宣金鸽, 薛艳敏, 余隋怀, 王娟. 基于视觉因素的地铁调度人机界面优化设计评价[J]. 图学学报, 2025, 46(1): 200-210.

LI Bo, XUAN Jinge, XUE Yanmin, YU Suihuai, WANG Juan. Evaluation of optimal design of human-machine interface for subway dispatching based on visual factors[J]. Journal of Graphics, 2025, 46(1): 200-210.

图/表 26

图1 调度员视野范围仿真

Fig. 1 Simulation of the dispatcher's field of view

图2 人的水平视野范围

Fig. 2 Horizontal visual field of a person

图3 人机界面划分示意图

Fig. 3 Schematic diagram of human-machine interface division

图4 人机界面各目标模块化

Fig. 4 Each object of the human-machine interface is modularized

表1 层次分析法1~9级标度表

Table 1 Scale table 1~9 levels of analytic hierarchy process

因素i比因素j	量化值
同等重要	1
稍微重要	3
较强重要	5
强烈重要	7
极端重要	9
两相邻判断的中间值	2，4，6，8

表2 随机一致性指标

Table 2 Random consistency index

矩阵阶数	R_I
1	0.00
2	0.00
3	0.58
4	0.90
5	1.12
6	1.24
7	1.32
8	1.41
9	1.45

图5 调度人机界面

Fig. 5 Scheduling man-machine interface

表3 优化前各模块在不同区域的单元数

Table 3 The number of units of each module in different areas before optimization

区域	模块								合计
区域	a	b	c	d	e	f	g	h	合计
A区	0	3	11	1	6	6	1	2	30
B区	0	3	8	6	0	0	6	2	25
C区	9	1	0	0	0	0	0	10	20
合计	9	7	19	7	6	6	7	14	75

表4 各模块重要度

Table 4 Importance of each module

参数	模块
参数	a	b	c	d	e	f	g	h
权重	0.127 3	0.219 3	0.171 8	0.307 2	0.174 5	0.174 5	0.307 2	0.171 8

表5 一致性检验结果

Table 5 Consistency test results

检验项目	结果
C_I值	0.024
R_I值	1.120
C_R值	0.021
一致性检验结果	通过

表6 优化后各模块在不同区域的单元数

Table 6 The number of units of each module in different areas after optimization

区域	模块								合计
区域	a	b	c	d	e	f	g	h	合计
A区	1	2	16	14	0	0	11	4	48
B区	2	4	14	1	10	10	1	2	44
C区	12	2	0	0	0	0	0	8	22
合计	15	8	30	15	10	10	12	14	114

图6 优化后的人机界面布局

Fig. 6 Optimized human-machine interface layout

表7 不同色彩组合的易见度

Table 7 Visibility of different color combinations

背景色	目标色优先选择顺序
黑	白>黄>橙黄>橙>红>绿>蓝
白	黑>红>紫>紫红>蓝>绿>黄
蓝	白>黄>橙黄>橙>红>黑>绿
黄	黑>红>蓝>蓝紫>黄绿>绿>白
绿	白>黄>红>黑>橙黄>蓝>紫
紫	白>黄>橙黄>橙>绿>蓝>黑>红
灰	黄>黄绿>橙>紫>蓝>黑

图7 界面整体配色

Fig. 7 Overall color matching of the interface

图8 字体样式

Fig. 8 Font style

图9 图标样式

Fig. 9 Icon style

图10 屏蔽门界面展示

Fig. 10 Screen door interface display

图11 屏蔽门报警信息展示

Fig. 11 Screen door alarm information display

图12 优化前调度界面兴趣区划分

Fig. 12 Division of interest area in scheduling interface before optimization

图13 优化后调度界面兴趣区划分

Fig. 13 Division of interest area in optimized scheduling interface

表8 调度界面优化前后的首次注视时间

Table 8 First fixation time before and after scheduling interface optimization

界面	兴趣区域				均值	标准差
界面	AOI1	AOI2	AOI3	AOI4	均值	标准差
优化前	44.70	45.88	45.77	47.74	46.02	0.98
优化后	30.77	23.99	26.08	36.45	29.32	4.79

表9 调度界面优化前后的注视持续时间

Table 9 Fixation duration before and after scheduling interface optimization

界面	兴趣区域				均值	标准差
界面	AOI1	AOI2	AOI3	AOI4	均值	标准差
优化前	6.56	12.81	14.59	8.62	10.65	3.20
优化后	2.51	5.57	6.73	4.41	4.81	1.59

表10 调度界面优化前后的注视次数

Table 10 Fixation times before and after scheduling interface optimization

界面	兴趣区域				均值	标准差
界面	AOI1	AOI2	AOI3	AOI4	均值	标准差
优化前	11	25	25	15	19	6.16
优化后	13	43	38	10	26	14.65

表11 调度界面优化前后的平均反应时

Table 11 Average reaction time before and after scheduling interface optimization

界面	兴趣区域				均值	标准差
界面	AOI1	AOI2	AOI3	AOI4	均值	标准差
优化前	0.43	1.02	1.08	0.97	0.88	0.26
优化后	0.19	0.46	0.52	0.59	0.44	0.15

图14 优化后屏蔽门眼动总热点图

Fig. 14 Total hot spot of eye movement of the optimized screen door

图15 优化后屏蔽门眼动热点地图

Fig. 15 Eye movement hotspot map of the optimized screen door

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基于视觉因素的地铁调度人机界面优化设计评价

Evaluation of optimal design of human-machine interface for subway dispatching based on visual factors

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