Quantifying traffic patterns with percolation theory: a case study of Seoul roads

Abstract

Urban traffic systems are characterized by dynamic interactions between congestion and free-flow states, influenced by human activity and road topology. This study employs percolation theory to analyze traffic dynamics in Seoul, focusing on the transition point qc and Fisher exponent τ. The transition point qc quantifies the robustness of the free-flow clusters, while the exponent τ captures the spatial fragmentation of the traffic networks. Our analysis reveals temporal variations in these metrics, with lower qc and lower τ values generally during rush hours representing low-dimensional behavior, within the broader context of the positive correlation between qc and τ. Weight–weight correlations are found to significantly impact cluster formation, driving the early onset of dominant traffic states. Comparisons with uncorrelated models highlight the role of real-world correlations. This approach provides a comprehensive framework for evaluating traffic resilience and informs strategies to optimize urban transportation systems. © The Korean Physical Society 2025.