## 2 Related Work  
### Emergency Evacuation Evaluation of Stations  
Emergency evacuation assessment methods for stations include simulation models (social force models, cellular automata models), AHP, fuzzy comprehensive evaluation methods, and agent-based simulations. For example, [PERSON] et al. [5] combined a social force model with passenger evacuation behavior to simulate the evacuation process in a metro station under various scenarios. [PERSON] et al. [6] proposed a modified social force model that adjusted the social force parameters for different categories of pedestrians to simulate the behavior of different types of pedestrians during evacuation in a metro station. [PERSON] et al. [7] used a modified cellular automata model to simulate and analyze evacuation processes in subway stations and incorporate different guidance strategies to evaluate their impact on evacuation efficiency and safety. [PERSON] et al. [8] employed the AHP to evaluate and prioritize different evacuation factors by structuring them into a hierarchical model, determining the relative importance of various criteria affecting evacuation, such as exit availability, crowd density, and guidance systems. [PERSON] et al. [9] designed a fuzzy decision-making approach to evaluate the emergency evacuation capacity of urban metro stations, ranking and selecting optimal evacuation strategies by analyzing multiple criteria under fuzzy conditions. [PERSON] et al. [10] integrated multiple risk factors, such as environmental, human, and management-related risks, into a multi-dimensional framework, evaluated the overall evacuation risk by handling uncertainties and imprecise data, providing a comprehensive risk assessment that can inform emergency planning and management strategies in subway stations. [PERSON] et al. [11] used agent-based models to simulate the evacuation process of metro stations. Agent-based models are computationally intensive and often require extensive data for calibration. Cellular automata models oversimplify individual behaviors and interactions, leading to less realistic outcomes. Social force models require precise parameter tuning and may not scale well for extremely large environments. Classical fuzzy decision-making methods may lack the granularity needed to model complex spatial and temporal dynamics.  
The advantages of the fuzzy comprehensive evaluation method in assessing station emergency evacuation capacity are presented as follows. Firstly, it is ideal for handling uncertainty: the fuzzy comprehensive evaluation method effectively manages uncertainty and ambiguity, making it suitable for dealing with complex, variable, and incomplete information. In the assessment of station emergency evacuation capacity, real-life scenarios often involve uncertainty, such as the unpredictability of passenger behavior [12]. Secondly, it has a comprehensive nature: this method integrates various factors and indicators, combining quantitative data with qualitative judgments to provide a comprehensive evaluation result. This comprehensive approach helps in performing a thorough assessment of the station's evacuation capacity [13]. Thirdly, it has high flexibility: the fuzzy comprehensive evaluation method allows for adjustments to the evaluation criteria and weights based on actual needs, accommodating different assessment goals and situations. Fourthly, it considers subjective factors: this method incorporates expert opinions and subjective judgments into the evaluation process, which is especially important for factors that are difficult to quantify, such as passengers' psychological states.  
Overall, the fuzzy comprehensive evaluation method, by considering a range of factors and managing uncertainty, provides a flexible and comprehensive assessment tool suitable for evaluating station emergency evacuation capacity.