A Method for Dynamic Coupling Coordination of High-speed Railway Node-line Passing Capacity Based on SEM

This study addresses the challenges posed by multiple dynamic factors affecting the passing capacity of high-speed railway node-line systems, particularly focusing on the complex interrelationships among these factors and the difficulty in quantifying their weights. A dynamic coupling coordination method based on structural equation modeling (SEM) is proposed to resolve these issues. The dynamic factors influencing high-speed railway node-line passing capacity are categorized into six subsystems: node system, line system, transportation organization, operational time, delays, and early arrivals. A PLE-SEM-based dynamic coordination model is subsequently constructed to analyze these subsystems. Operational data from the Shanghai West Station-Shanghai Station section are utilized to verify the model's validity, scientific rigor, and goodness-of-fit through measurement model and structural model validation. This process identifies interaction mechanisms, directional influences, and indicator weights across subsystems while detecting capacity bottlenecks. A coupling coordination degree model is further applied to assess system-level and subsystem-level coordination states, enabling the identification of key links. The results demonstrate: ①this model method is applicable for investigating the complex influence relationships among dynamic factors affecting the throughput capacity of high-speed railway node-line systems. It enables the identification of critical dynamic factors within subsystems of the system's throughput capacity, quantifies the influence relationships, and specifies the direction of impacts. ②Through comprehensive factor analysis and case study calculations, the proposed method effectively identifies key factors and reveals dynamic coupling relationships among them. A total of 13 direct influence paths and 9 indirect influence paths are established between subsystems, visualizing their interconnections. These results provide a basis for selecting appropriate capacity calculation parameters in practical applications.