Urban Rail Transit (URT) system is often disturbed by various types of security incidents during operation. Therefore, effective utilization of passenger in-transit information to dynamically assess the URT system’s abilities to maintain and resume normal operation under disturbances (operational resilience) is the key and prerequisite for URT safety management and emergency response. Based on typical operational disruption scenario, this paper study the multimodal data-driven URT operational resilience and its evaluation methods. The main contributions of this research includes: capturing key information about passengers in the travel process based on historical data, and quantifying the system’s service capabilities; proposing the concept of operational resilience oriented towards URT emergency management based on service level; employing the resilience curve to analyze the evolutionary patterns of URT service levels during safety events, and emphasizing the relativity and dynamism of operational resilience; constructing a two-stage “disruption-recovery” URT operational resilience evaluation model and taking Hangzhou URT as an example to verify the effectiveness of the model through experiments. The results provide a good reference for URT safety status assessment and emergency response. Note to Practitioners—With the expansion of urban rail transit scale, the passenger flow it undertakes is also increasing. Frequent security incidents can seriously disrupt the operation of urban rail transit, causing significant economic losses and even threatening the safety of passengers. If the ability of urban rail transit to resist safety incidents and restore normal operation can be understood in advance, it will help operation managers make reasonable judgments and emergency decisions. Therefore, this paper proposed an evaluation method for operational resilience with the service level of urban rail transit as the key.