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隧道建设(中英文) ›› 2023, Vol. 43 ›› Issue (8): 1269-1281.DOI: 10.3973/j.issn.2096-4498.2023.08.002

• 综述 • 上一篇    下一篇

面向智能盾构施工的人因研究综述

杜娟1, 2, 张静怡1, 2, 胡珉1, 2, 甘丽凝1, 2   

  1. (1.上海大学悉尼工商学院, 上海 201208 2. 上海大学-上海城建集团建筑产业化研究中心, 上海 200072)
  • 出版日期:2023-08-20 发布日期:2023-09-10
  • 作者简介:杜娟(1981—),女,山西阳泉人,2014年毕业于上海财经大学,管理科学与工程专业,博士,副教授,主要从事工程管理、知识决策系统等方面的研究工作。Email: ritadu@shu.edu.cn。

Literature Review on Human Factors Involved in Intelligent Shield Construction

DU Juan1, 2, ZHANG Jingyi1, 2, HU Min1, 2, GAN Lining1, 2   

  1. (1. SILC Business School, Shanghai University, Shanghai 201208, China; 2. SHU-SUCG Research Centre for Building Industrialization, Shanghai University, Shanghai 200072, China)
  • Online:2023-08-20 Published:2023-09-10

摘要: 为提高盾构司机对智能盾构的接受度和适应性、实现人机协同,以智能化、人因工程和工程建造为主题进行关键词检索。通过文献分析软件VOSviewer178篇文献的关键词进行共现分析,形成人机信任、人因风险和人因设计3个研究维度,并对3个主题下的文献进行综述; 通过对主题关键词的引用时间进行归纳总结,发现人机协同是人与智能施工机械交互的重要研究趋势。在此基础上得到智能盾构人因研究启示,根据实际项目数据分析发现,解释性是提高人对智能盾构接受度的关键,同时提出从完善人工作负荷测量、应用数字化技术等方面增强人的适应性; 从人机智能融合、人机功能分配、工作模式设计等方面实现人机协同。

关键词: 智能盾构, 人因工程, 人机协同, 人工智能AI

Abstract: To address the issues of acceptance, adaptability, and humanmachine collaboration of shield tunneling drivers for intelligent shield tunneling, research on the unification of three fields, namely intelligence, human factors, and engineering construction, is summarized. Moreover, the cooccurrence of certain keywords in 178 articles is analyzed using VOSviewer software, and three research dimensions, namely trust in automation, risk related to human factors, and design considering human factors, are identified. Based on the citation frequency of the theme keywords, humanmachine collaboration is identified as an important research trend in studying the interaction between humans and intelligent construction machinery. On this basis, insights for future research on human factors in intelligent shield tunneling are discussed. Further, the key to improving operator acceptance of intelligent shield tunneling machines is interpretability, as determined by analyzing data from actual projects. Additionally, an analysis of practical project data reveals the need to improve the adaptability of drivers by improving workload determination and implementing digital technologies. Humanmachine collaboration can be achieved by integrating humanmachine intelligence, allocating humanmachine functions, and designing different work modes.

Key words: intelligent shield, human factors, humanmachine collaboration, artificial intelligence