TY - JOUR
T1 - 基于视觉因素的地铁调度人机界面优化设计评价
AU - Li, Bo
AU - Xuan, Jinge
AU - Xue, Yanmin
AU - Yu, Suihuai
AU - Wang, Juan
N1 - Publisher Copyright:
© 2025 Editorial of Board of Journal of Graphics. All rights reserved.
PY - 2025/2/28
Y1 - 2025/2/28
N2 - 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.
AB - 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.
KW - eye movement experiment
KW - human machine interface
KW - particle swarm algorithm
KW - subway dispatcher
UR - http://www.scopus.com/inward/record.url?scp=85217651847&partnerID=8YFLogxK
U2 - 10.11996/JG.j.2095-302X.2025010200
DO - 10.11996/JG.j.2095-302X.2025010200
M3 - 文章
AN - SCOPUS:85217651847
SN - 2095-302X
VL - 46
SP - 200
EP - 210
JO - Journal of Graphics
JF - Journal of Graphics
IS - 1
ER -