Urban rail transit (URT) systems are exposed to risks of natural disasters and man-made disruptions, which not only cause train delays and overcrowding of platforms, but can even lead to serious safety incidents. Therefore, it is crucial to design a resilient URT system that provides commuters with as reliable a service as possible. This study first proposes to assess the resilience of URT systems with the emerging virtual coupling technologies, which allow trains to be coupled/decoupled dynamically. In contrast to the existing studies, where the system resilience is usually quantified through a resilience triangle that reflects the recovery of system performance, our study proposes a novel resilience assessment metric of URT from the perspective of passengers, which depicts the quick evacuation of delayed crowds in case of disruptions. To further enhance the system resilience, we focus on utilizing train platoons to transport the delayed passengers and we construct a mixed integer programming (MIP) model to optimize the rescheduling decisions of train platoons. Considering different types of disruptions in practice (e.g., different occurrence time of disruptions, disrupted sections), we develop a two-step simulation-optimization approach to solve the MIP model, which simulates the influences of random disruptions on passengers and then optimizes the rescheduling decision of train platoons in an iterative scheme. Finally, the proposed approach is validated using real-world data from the Beijing Metro. Through quantifying for a large set of disruptions, the simulation results demonstrate that the involvement of train platoons can effectively enhance the system resilience of URT against unexpected disruptions.