Time Prediction Model for Multi-vehicle Collaborative Information Processing Operations for Armored Vehicle Crews

WANG Rulan; LIU Shuang; WANYAN Xiaoru; FENG Chuanyan; XIE Fang; ZHOU Yue; MIN Yuchen

doi:10.19554/j.cnki.1001-3563.2026.14.013

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Packaging Engineering ›› 2026, Vol. 47 ›› Issue (14) : 142-152. DOI: 10.19554/j.cnki.1001-3563.2026.14.013

Industrial Design

Time Prediction Model for Multi-vehicle Collaborative Information Processing Operations for Armored Vehicle Crews

WANG Rulan¹, LIU Shuang¹, WANYAN Xiaoru^1,*, FENG Chuanyan^1,2, XIE Fang³, ZHOU Yue³, MIN Yuchen¹

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Abstract

The performance modeling of crew tasks in typical multi-vehicle collaborative task scenarios is crucial for maximizing operation efficiency of systems. Based on the basic framework of GOMS model, the characteristics of multi-vehicle collaborative information processing operation of armored vehicles were analyzed to extract and adaptively optimize the operation units from two dimensions of human-human interaction and human-machine interaction, thus constructing a task completion time-based prediction model for multi-vehicle collaborative information processing tasks. In order to verify the validity of the model, typical dual-vehicle cooperative operation task scenarios were designed and ergonomic experiments were carried out based on the high-fidelity dual-vehicle cooperative operation task simulation experimental platform for armored vehicles, collecting performance data through the operation performance recording system and video-audio assisted analysis recording. The model validation was carried out with 16 collaborative task segments, and the model calculation results were generally consistent with the experimentally measured trends, showing a significantly high correlation and then the validity of the model was preliminarily verified. The model constructed in this work can predict and analyze the task completion time of multi-vehicle collaborative information processing operations performed by armored vehicle crew members, as well as detect and analyze potential human-machine interaction operation risk points, thereby providing theoretical methods for the optimized design of display and control interfaces and operation.

Key words

multi-vehicle collaboration / information processing operation / time prediction model / task performance / ergonomics

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WANG Rulan, LIU Shuang, WANYAN Xiaoru, FENG Chuanyan, XIE Fang, ZHOU Yue, MIN Yuchen. Time Prediction Model for Multi-vehicle Collaborative Information Processing Operations for Armored Vehicle Crews[J]. Packaging Engineering. 2026, 47(14): 142-152 https://doi.org/10.19554/j.cnki.1001-3563.2026.14.013

References

[1] 周孙夏, 刘双, 完颜笑如, 等. 噪声环境下告警冗余设计模式对装甲车乘员响应操作绩效的影响[J]. 北京航空航天大学学报, 2023: 1-10.
ZHOU S X, LIU S, WANYAN X R, et al.Influences of multimodal redundant alarm design mode on reaction performanceof armored vehicle crew under noise environment[J]. Journal of Beijing University of Aeronautics and Astronautics, 2023: 1-10.
[2] HUANG Q, SUN H, WEI Y, et al.Comprehensive assessment of mental workload of armored vehicle operators based on SVM and DS evidence theory[J]. Cognition, Technology & Work, 2025, 27(1-2): 137-157.
[3] 汪国胜, 曹宇, 张伟杰, 等. 装甲车防爆座椅抗爆指标合理性研究与建议(军用车辆乘载员防地雷爆炸减振抗爆座椅设计研究系列二)[J]. 兵器装备工程学报, 2022, 43(12): 22-28.
WANG G S, CAO Y, ZHANG W J, et al.Research and suggestion on rationality of anti-explosionindex of armored vehicle anti-explosion seats[J]. Journal of Ordnance Equipment Engineering, 2022, 43(12): 22-28.
[4] AHMADI K D, RASHIDI A J, MOGHRI A M.Design and simulation of autonomous military vehicle control system based on machine vision and ensemble movement approach[J]. The Journal of Supercomputing, 2022, 78(15): 17309-17347.
[5] HUANG Q, GUO M, WEI Y, et al.A Real-time Assessment System for Cognitive Performances of Armored Vehicle Crews Based upon the Multi-source Information Fusion[J]. International Journal of Human-Computer Interaction, 2025, 41(2): 932-950.
[6] NAPOLI N J, STEPHENS C L, KENNEDY K D, et al.NAPS Fusion: A framework to overcome experimental data limitations to predict human performance and cognitive task outcomes[J]. Information Fusion, 2023, 91: 15-30.
[7] WANG Z, LIU S, WANYAN X, et al.Pilot workload measurement model based on task complexity analysis[J]. International Journal of Industrial Ergonomics, 2024, 104: 103637.
[8] 薛红军, 庞俊锋, 栾义春, 等. 驾驶舱飞行员认知行为一体化仿真建模[J]. 计算机工程与应用, 2013, 49(23): 266-270.
XUE H J, PANG J F, LUAN Y C, et al.Cockpit pilot cognitive behavioral integration simulation modeling[J]. Computer Engineering and Applications, 2013, 49(23): 266-270.
[9] 聂俊峰, 刘维平, 傅斌贺, 等. 面向装甲车辆乘员信息处理的作业时间预测模型研究[J]. 兵工学报, 2017, 38(2): 233-239.
NIE J F, LIU W P, FU B H, et al.Predictive operation time model for information processing task of crew in armored vehicle[J]. Acta Armamentarii, 2017, 38(2): 233-239.
[10] XIE Y, ZHOU R, QU J.Fitts’ law on the flight deck: evaluating touchscreens for aircraft tasks in actual flight scenarios[J]. Ergonomics, 2023, 66(4): 506-523.
[11] SAHA S, SENAPATI A, MAITY R.An approach to predict the task efficiency of web pages[J]. Multimedia Tools and Applications, 2023, 82(16): 25217-25233.
[12] AL-MEGREN S, KHABTI J, AL-KHALIFA H S. A Systematic Review of Modifications and Validation Methods for the Extension of the Keystroke-Level Model[J]. Advances in Human-Computer Interaction, 2018, 2018: 1-26.
[13] SETTHAWONG P, SETTHAWONG R.Updated Goals Operators Methods and Selection Rules (GOMS) with touch screen operations for quantitative analysis of user interfaces[J]. Int. J. Adv. Sci. Eng. Inf. Technol, 2019, 9(1): 258.
[14] PARK J, WOZNIAK D, ZAHABI M.Modeling novice law enforcement officers’ interaction with in-vehicle technology[J]. Applied Ergonomics, 2024, 114: 104154.
[15] XUE P, PI D, WAN C, et al.Collaborative planning and control of heterogeneous multi-ground unmanned platforms[J]. Engineering Applications of Artificial Intelligence, 2024, 136: 108968.
[16] 郑梦月, 解闵涵. 振动环境下界面复杂度对视觉认知的影响研究[J]. 包装工程, 2025, 46(8): 115-123.
ZHENG M Y, XIE M H.Effect of Interface Complexity on Visual Cognition in Vibration Environment[J]. Packaging Engineering, 2025, 46(8): 115-123.
[17] PEI Z, ZHAO W, HU L, et al.Factors affecting the situational awareness of armored vehicle occupants[J]. Sensors, 2024, 24(11): 3688.
[18] MARLOW S L, LACERENZA C N, PAOLETTI J, et al.Does team communication represent a one-size-fits-all approach : A meta-analysis of team communication and performance[J]. Organizational Behavior and Human Decision Processes, 2018, 144: 145-170.
[19] ZHOU J, WU X, LV Y, et al.Recent progress on the study of multi-vehicle coordination in cooperative attack and defense: an overview[J]. Asian Journal of Control, 2022, 24(2): 794-809.
[20] 苏畅, 周垚, 袁晓芳. 基于GOMS模型的网上购物流程设计优化研究[J] 包装工程, 2021, 42(6): 113-119.
SU C, ZHOU Y, YUAN X F.Design and Optimization of Online Shopping Process Based on GOMS Model[J]. Packaging Engineering, 2021, 42(6): 113-119.
[21] JORRITSMA W, HAGA P J, CNOSSEN F, et al.Predicting human performance differences on multiple interface alternatives: KLM, GOMS and CogTool are unreliable[J]. Procedia Manufacturing, 2015, 3: 3725-3731.
[22] BURNS L R, NEMBHARD I M, SHORTELL S M.Integrating network theory into the study of integrated healthcare[J]. Social Science & Medicine, 2022, 296: 114664.
[23] 孟国. 汉语语速与对外汉语听力教学[J]. 世界汉语教学, 2006(2): 129-137, 4.
MENG G.Speed of utterance and the teaching of Chinese listening to foreign students[J]. Chinese Teaching in the World, 2006(2): 129-137.
[24] RIEGER T, MANZEY D.Understanding the Impact of Time Pressure and Automation Support in a Visual Search Task[J]. Human Factors: The Journal of the Human Factors and Ergonomics Society, 2024, 66(3): 770-786.
[25] 廖建桥, 张万山. 论中文的阅读速度[J]. 人类工效学, 1996(1): 38-41, 70.
LIAO J Q, ZHANG W S.On the Reading Speed of Chinese[J]. Chinese Journal of Ergonomics, 1996(1): 38-41.
[26] 栾可迪, 郭保桥, 魏中亮, 等. 装甲车辆多模态交互和环境负荷对乘员任务绩效的影响[J]. 兵工学报, 2025, 46(4): 344-358.
LUAN K D, GUO B Q, WEI Z L, et al.Effects of Armored Vehicle Multi-modal Interactions and Environmental Load on Mission Performance of Occupant[J]. Acta Armamentarii, 2025, 46(4): 344-358.
[27] 赵子俊, 陈士涛, 贺维艳, 等. 有人/无人机协同作战效能智能评估方法[J]. 航空学报, 2025: 1-10.
ZHAO Z J, CHEN S T, HE W Y, et al.Intelligent Assessment Method for MAV/UAV Collaborative Combat Effectiveness[J]. Acta Aeronautica et Astronautica Sinica, 2025: 1-10.