With rapid population growth, increasing congestion and pollution resulting from rising transportation demand have drawn the attention of governments in both developed and developing countries. As a form of large-scale public transportation, urban transit systems (UTS) offer advantages such as high capacity, operational efficiency, and reduced emissions. These characteristics make them an effective solution for alleviating pressure on conventional transportation networks [1]. However, the UTS is a complex network composed of numerous interconnected elements, activities, and events. The high level of interdependency among system components makes metro operations vulnerable to various disaster risks and cascading failures [2]. Therefore, developing effective methods for modeling and assessing system vulnerability is essential for disaster risk reduction.