终端区是民航运输中极易发生不安全事件的区域，终端区管制系统作为空中交通管制系统中至关重要的一部分，对其运行过程进行安全风险研究至关重要。针对终端区管制系统安全风险耦合性强、传统分析方法难以量化风险之间交互效应的问题，提出一种将系统理论过程分析（system-theoretic process analysis, STPA）与交叉影响分析-解释结构模型（cross impact analysis and interpretive structure model, CIA-ISM）相结合的风险分析方法。首先利用STPA识别出系统中的20个安全风险因素；其次，采用皮尔逊（Pearson）相关系数法替代传统德尔菲法以消除主观偏差，结合200起历史事故数据量化风险因素间的影响强度，构建交叉影响矩阵；最后，通过ISM模型划分风险层级并推演终端区管制系统运行时的不安全状态对事故发生概率的影响程度，从而分析终端区管制系统的关键风险因素。并以青岛终端区管制系统为例，通过情景推演揭示多因素耦合下发生事故概率趋近1的动态机制，验证该模型的有效性。结果表明，管制班组配合不当等5类直接致因对不安全事件影响概率达84%，管制班组配合不当，和相邻管制室的协调、移交、配合有问题，管制员公布情报数据有误是对终端区管制系统安全运行影响最大的3个直接风险致因。

The terminal area is a region in civil aviation transportation where unsafe incidents are highly prone to occur. The terminal area control system, as a crucial part of the air traffic control system, is essential for conducting safety risk research on its operational processes. A risk analysis method combining system theoretical process analysis (STPA) with cross impact analysis and interpretive structure model (CIA-ISM) was proposed to address the strong coupling of security risks in terminal area control systems and the difficulty of quantifying the interaction effects between risks using traditional analysis methods. Firstly, STPA was used to identify 20 safety risk factors within the system. Secondly, the Pearson correlation coefficient method was employed instead of the traditional Delphi method to eliminate subjective biases, and the impact intensity between risk factors was quantified using 200 historical accident data to construct a cross-impact matrix. Finally, through the ISM model, risk levels were divided and the influence of unsafe states during the operation of the terminal area control system on the probability of accidents was deduced, thereby analyzing the key risk factors of the terminal area control system. Taking a specific terminal area control system as an example, scenario deduction reveals the dynamic mechanism by which the probability of accidents approaches 1 under multi-factor coupling, verifying the effectiveness of the model. The results show that improper coordination among control teams and other direct causes account for 84% of the accident probability, with improper coordination among control teams, coordination issues with adjacent control rooms, handover problems, and errors in intelligence data published by controllers being the three most significant direct risk causes affecting the safe operation of the terminal area control system.