## 1 Introduction  
Urban rail transit has become one of the most crucial travel modes in metropolises due to its low energy consumption, low pollution, high safety, and reliability [1, 2, 3, 4]. Although urban rail transit brings great convenience to travelers, it also encounters many potential risks in daily operation [5, 6], such as signal interruption, equipment failure, natural disasters, terrorist attacks, and other emergencies. The signaling system is a very vulnerable part of an urban rail transit system. The disruptions of urban rail transit systems caused by signal interruptions account for the largest proportion of all emergencies [7]. Once a disruption occurs in an urban rail transit system, it affects the transit quality, increases passengers' travel times, and changes their travel behavior. Transit quality is considered to play an important role in the policy decision-making related to public transit [8, 9, 10, 11]. With the increasing complexity of the urban rail transit network and the increase in correlation between different lines, the security and quality assessment of the urban rail transit network are of significant concern. The urban rail transit network is a relatively closed system with a high population density, which makes it different from the urban road transportation system [12; 13; 14; 15]. Once rail transit disruption occurs, the impact caused by the disruption propagates along the urban rail transit lines. However, most urban rail transit operators monitor emergencies through the manual observation of video surveillance [16] and accordingly determine flow restriction strategies at certain stations. This method is too subjective and also lacks theoretical support. In order to minimize the influence of emergencies on the urban rail transit system and resume operation as soon as possible, it is necessary to analyze the influence of passenger flow and the propagation law of disruptions. Based on the real-time analysis of the influence of passenger flow and the propagation law of disruptions, urban rail transit operators can quickly determine management measures. The relevant literature on exploring the influence of emergencies on urban rail transit systems can be categorized into three directions. The first large stream of literature has paid attention to passenger behavior after emergencies. [PERSON] et al. [17] explored the possible behavior of passengers and crew after an emergency in a rail transit system. [PERSON] et al. [18] introduced the idea of statistics based on previous studies and developed a statistical method for analyzing the behavior of influenced passengers during the disruption of a section and the disruption of station operation. Furthermore, some studies have also focused on the problem of passenger route choice during emergencies. [PERSON] et al. [19] constructed an impact model of operation disruption on the travel path of passengers based on a travel time estimation model for passengers between adjacent stations and a passenger travel path decision model and realized the quantitative assessment of the influence of disruption. [PERSON] et al. [16] established multiple logistic regression models to analyze passenger travel behavior during emergencies. [PERSON] et al. [20] constructed a mixed multinomial logit model to investigate transit customers' mode choice behavior during light rail transit short-term planned service disruption. The behavior of passengers may differ depending on the property and the extent of the disruption. [PERSON] et al. [21] divided and analyzed three types of abnormal passenger flow affected by disruptions, such as passengers who left the system, passengers who took detours, and passengers who were delayed but continued their travel. In addition, due to the difficulty in obtaining real-world data on urban rail transit, some studies have used simulation methods to model and simulate passenger behavior during disruptions [22; 23]. The second large stream of literature has paid attention to the influence of emergencies on passenger flow.