School of Civil Engineering, Suzhou University of Science and Technology, Suzhou 215009, China.
School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, China.
Int J Environ Res Public Health. 2023 Feb 15;20(4):3386. doi: 10.3390/ijerph20043386.
Subway operation safety management has become increasingly important due to the severe consequences of accidents and interruptions. As the causative factors and accidents exhibit a complex and dynamic interrelationship, the proposed subway operation accident causation network (SOACN) could represent the actual scenario in a better way. This study used the SOACN to explore subway operation safety risks and provide suggestions for promoting safety management. The SOACN model was built under 13 accident types, 29 causations and their 84 relationships based on the literature review, grounded theory and association rule analysis, respectively. Based on the network theory, topological features were obtained to showcase different roles of an accident or causation in the SOACN, including degree distribution, betweenness centrality, clustering coefficient, network diameter, and average path length. The SOACN exhibits both small-world network and scale-free features, implying that propagation in the SOACN is fast. Vulnerability evaluation was conducted under network efficiency, and its results indicated that safety management should focus more on fire accident and passenger falling off the rail. This study is beneficial for capturing the complex accident safety-risk-causation relationship in subway operations. It offers suggestions regarding safety-related decision optimization and measures for causation reduction and accident control with high efficiency.
由于事故和中断造成的严重后果，地铁运营安全管理变得越来越重要。由于致因因素和事故之间存在复杂和动态的相互关系，因此提出的地铁运营事故因果网络（SOACN）可以更好地代表实际情况。本研究使用 SOACN 来探索地铁运营安全风险，并为促进安全管理提供建议。基于文献综述、扎根理论和关联规则分析，在 13 种事故类型、29 种致因及其 84 种关系的基础上，建立了 SOACN 模型。基于网络理论，获得了拓扑特征，以展示事故或致因在 SOACN 中的不同作用，包括度分布、中间中心性、聚类系数、网络直径和平均路径长度。SOACN 具有小世界网络和无标度特征，这意味着在 SOACN 中的传播速度很快。在网络效率下进行了脆弱性评估，其结果表明，安全管理应更加关注火灾事故和乘客坠轨。本研究有助于捕捉地铁运营中复杂的事故安全风险因果关系。它为安全相关决策优化以及针对致因减少和事故控制的高效措施提供了建议。
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