Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

Yanhao Sun, Tao Zhang, Shuxin Ding, Zhiming Yuan, Shengliang Yang
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Abstract

PurposeIn order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.Design/methodology/approachFirst, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.FindingsThe cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/valueThis study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.
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基于改进博弈论和云模型的高速铁路 CTC 系统风险评估
为了解决风险评估过程中指标权重计算不准确、指标评估的主观性和不确定性等问题,本研究旨在提出一种科学合理的集中交通控制(CTC)系统风险评估方法。然后,为了提高权重计算的准确性,采用模糊分析层次过程(FAHP)、模糊决策试验与评价实验室(FDEMATEL)和熵权法计算各指标的主观权重、相对权重和客观权重。利用博弈论将这三种权重结合起来,得出每个指标的综合权重。为减少评估过程中的主观性和不确定性,利用后向云生成器法获得各指标云模型的数字特征(NC)。然后对各指标的 NC 进行加权,得出用于 CTC 系统风险评估的综合云。该云模型用于获得 CTC 系统的综合风险评估。该模型的相似度测量方法可衡量综合风险评估云与风险标准云之间的相似度。结果云模型可以很好地处理风险评估过程中的主观性和模糊性。基于云模型的风险评估方法被应用于某铁路集团的 CTC 系统风险评估,并取得了良好的效果。原创性/价值本研究提供了一种基于云模型的 CTC 系统风险评估方法,该方法能准确计算风险指标的权重,并利用云模型减少评估中的不确定性和主观性,实现对 CTC 系统的有效风险评估。它可以为 CTC 系统的风险管理提供参考和理论依据。
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