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考虑自动化信任的矿工人机安全协作机制研究

Research on the mechanism of human-machine security collaboration of miners considering automation trust.

作者信息

Yang Juan, Yang Xue, Chai Shan, Ni Likun, Wang Xiao, Pan Langxuan

机构信息

School of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, China.

School of Management, Henan University of Urban Construction, Pingdingshan, China.

出版信息

Heliyon. 2024 Oct 16;10(23):e39456. doi: 10.1016/j.heliyon.2024.e39456. eCollection 2024 Dec 15.

Abstract

Safety in the coal mining industry is a long-standing issue. With the implementation of intelligent construction in coal mines, humans-machine collaboration is critical to accident prevention. We investigate the psychological dynamics among miners during intelligent construction by developing distinct evolutionary game models for miner security collaboration mechanisms, while also considering the level of trust in automation. We explore the impact of changes in automation trust on the human-machine security collaboration behaviour among miners as well as the regulatory strategies adopted by coal mining enterprises. Evidently, the current level of automation trust among miners is insufficient to ensure safety, and the safety management systems of coal mining enterprises are yet to reach a stable state. Examination of the relevant parameters using specific examples reveals that the optimal range for the level of automation trust among miners lies between 0.7 and 0.9, indicating a favourable coal mine safety production system. These conclusions provide a scientific foundation for effectively enhancing safety management in the context of intelligent construction in coal mines.

摘要

煤矿行业的安全是一个长期存在的问题。随着煤矿智能化建设的推进,人机协作对于事故预防至关重要。我们通过为矿工安全协作机制开发不同的演化博弈模型来研究智能化建设过程中矿工的心理动态,同时考虑对自动化的信任程度。我们探讨自动化信任度的变化对矿工人机安全协作行为以及煤矿企业所采取监管策略的影响。显然,当前矿工的自动化信任水平不足以确保安全,煤矿企业的安全管理系统尚未达到稳定状态。通过具体实例对相关参数进行检验表明,矿工自动化信任水平的最佳范围在0.7至0.9之间,这表明煤矿安全生产系统良好。这些结论为在煤矿智能化建设背景下有效加强安全管理提供了科学依据。

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