Analysis of Urban Rail Public Transport Space Congestion Using Graph Fourier Transform Theory: A Focus on Seoul

Urban transportation efficiency is critical in densely populated cities, such as Seoul, South Korea, where subway transfer stations are vital. This study investigates the spatial efficiency and passenger flow dynamics of multilayered transfer stations, using triangular Fourier transform as the primary analytical method. The research incorporates principal component analysis (PCA) and K-means clustering to classify stations based on structural characteristics and congestion patterns. Data derived from transportation card usage during peak hours and architectural layouts were analysed to identify critical bottlenecks. The results highlighted notable inefficiencies in transfer times and congestion. For example, the analysis revealed that optimising transfer corridors at Seoul Station could reduce average transfer times by over 10 min. Dongdaemun History & Culture Park Station would benefit from ground-level pathways to address inefficiencies caused by its extensive underground network. Sindorim Station’s reorganisation of above-ground and underground connectivity was found to enhance passenger flow. By introducing the concept of the ‘entry baseline for passenger flow in public buildings’, this study offers a novel framework for evaluating and improving urban transit infrastructure. The findings provide actionable insights into transfer station design, supporting strategies for addressing the challenges of urban mobility in megacities while contributing to transit-oriented development.