## 1 Introduction  
In recent years, many major cities, such as Beijing, Shanghai, and Guangzhou, have put high-speed railway stations (HSRSs) into operation. China's high-speed railway network is the largest in the world, carrying over 4.3 billion passengers annually (as of 2024). During peak travel periods, such as the Chinese New Year, daily passenger volumes can exceed 12 million (as of 2025). Major HSRSs, such as Beijing South Railway Station and Shanghai Hongqiao Railway Station, handle an average of 200,000 to 500,000 passengers per day, with peak daily volumes reaching up to 1 million passengers. These large transportation hubs combine multiple modes of transportation, leading to high population density [1]. Large HSRSs in China often cover extensive areas, with some stations exceeding 1 million square meters in total floor space. For example, Beijing South Railway Station spans approximately 320,000 square meters, and Shanghai Hongqiao Railway Station covers around 1.3 million square meters, including integrated transportation hubs. In the event of an emergency, such as an operational accident or a terrorist attack, the consequences can be severe, especially if evacuation management is poor or safety design is inadequate [2,3]. Improving the emergency evacuation capacity of these HSRSs and developing effective emergency management and evacuation plans are crucial issues that need to be addressed by safety and operational departments. The emergency evacuation of passengers in large HSRSs is a complex and challenging task [4]. First, passengers' behavior in emergencies is unpredictable; panic can lead to chaotic situations where individuals may not follow instructions, resulting in escalating risks. Second, evacuation guidance, management methods, and adopted evacuation plans greatly influence the evacuation capacity, and these factors are difficult to quantify. Third, the evacuation process is dynamic, involving large numbers of people whose behavior is hard to quantify. Using reasonable evaluation metrics to assess the emergency evacuation capacity of large railway passenger hubs can provide effective suggestions and improvement measures for the design of evacuation facilities, management methods, and evacuation plans. It also serves as a theoretical foundation for developing emergency evacuation simulation models, contributing significantly to the theoretical and practical enhancement of emergency evacuation capacity in HSRSs. The challenges in current evacuation strategies are as follows: first, dynamic passenger flow: the unpredictable nature of passenger movement during emergencies makes it difficult to design effective evacuation plans; second, complex station layouts: multi-level structures, interconnected spaces, and diverse exit points complicate the identification of optimal evacuation routes; third, limited real-time data: the lack of real-time monitoring and data integration hinders the ability to adapt evacuation strategies during emergencies; fourth, inadequate evaluation metrics: current metrics often fail to capture the complexity of evacuation processes, such as the impact of congestion, behavioral responses, and environmental factors. Therefore, this paper aimed to identify appropriate indicators to describe the emergency evacuation capacity of HSRSs and proposed a Pythagorean fuzzy three-way decision (PF-3 WD) method to assess and evaluate the fuzziness and uncertainty of information. The reasons why the PF-3 WD Model is suitable for HSRSs are as follows: first, handling uncertainty: the PF-3 WD model is specifically designed to address uncertainty and imprecision, which are inherent in HSRS evacuation scenarios. For example, it can effectively model ambiguous or incomplete information, such as uncertain passenger behavior and dynamic environmental conditions. It provides a robust framework for balancing conflicting criteria, such as safety, efficiency, and resource allocation.