鉴于现有地铁系统韧性研究中对地铁牵引电网特性考虑不足的问题，该文提出了一种基于网络耦合特性的地铁网络韧性评估方法。通过捕捉地铁牵引电网与地铁网络之间的多对一和一对多耦合特性，该方法定量分析了地铁牵引电网失效对地铁网络运营性能的动态影响。采用考虑客流加权和出行时间阻抗的网络效率作为韧性评估的基础，并运用Monte Carlo方法模拟地铁牵引电网的恢复过程，定量化评估地铁系统在牵引电网部分及完全失效故障情境下的韧性能力。以西安市地铁网络为例，进行了牵引电网不同失效场景的仿真模拟。研究结果表明，考虑牵引电网的多对一冗余特性，地铁网络韧性提升幅度约为6.8%~14.4%；然而，未考虑牵引电网的一对多特性会过高评估地铁网络的韧性，因为未能充分考虑失效带来的连锁效应。高客流区域受影响后网络效率损失最高可达50.2%，网络韧性损失达到36.1%。通过对比不同失效场景下的韧性曲线演化特征，发现当失效设施较为集中且恢复目标明确时，韧性曲线的上升速率显著加快，提升近2倍。

Objective: The metro system, as a crucial component of modern urban transportation, relies heavily on the reliability of its traction power network to maintain stable operations. However, existing research on metro system resilience assessment often overlooks the complex coupling characteristics between the traction power network and the metro network. In particular, the many-to-one and one-to-many coupling characteristics of the traction power network significantly influence metro system resilience but remain underexplored. This study proposes a resilience assessment method for metro networks based on the network coupling characteristics, focusing on quantitatively evaluating the dynamic impact of traction power network failures on metro network operational performance under both partial and complete failure scenarios. Methods: This research constructs separate models for the traction power network and the metro network. Building on these foundational models, it incorporates the many-to-one and one-to-many power supply characteristics of the traction power network, establishing a coupling model that integrates both systems. Network efficiency, which considers passenger flow weighting and travel time impedance, forms the basis for assessing resilience. The Monte Carlo method is used to model the recovery process of the metro traction power network. Using the Xi'an metro network as a case study, different failure scenarios are simulated, enabling a comprehensive evaluation of the metro system's service capacity and resilience changes under various fault conditions. Results: The results of this study are as follows: (1) The many-to-one redundancy characteristic of the traction power network enhances metro network resilience by 6.8%-14.4%. However, ignoring the one-to-many characteristics of the traction power network may lead to an overestimation of resilience, as cascading failure effects are inadequately accounted for. (2) Traction power network failures in high passenger flow areas can cause efficiency losses of up to 50.2%, with corresponding resilience losses reaching 36.1%. (3) Resilience performance varies across metro stations and the overall network depending on the complexity of failure scenarios. More complex scenarios involve a greater number and broader distribution of repair targets, increasing the intricacy and time demand of recovery processes. Conclusions: The proposed metro network resilience assessment method based on network coupling characteristics provides a more accurate evaluation of the impact of traction power network failures. By accounting for both many-to-one and one-to-many coupling characteristics, the method realistically reflects the redundancy supply effect of the system and the cascading failure process. The study emphasizes that while adopting a decentralized layout, metro system operation and planning need to strengthen the redundancy design of traction substations and supply section networks. Furthermore, a coordinated emergency response across multiple departments is recommended to ensure rapid mobilization of repair resources and shuttle capacity, minimizing disruptions to passenger travel during emergencies. The findings of this study provide theoretical guidance for developing emergency response and recovery strategies in metro systems under power facility failure scenarios. Future research will expand the resilience assessment framework to multi-modal transportation systems, further improving the universality and practicality of the model.