A Dynamic Modeling of Network-level Accumulation Heterogeneity

Abstract

This study proposes a dynamic modeling framework that characterizes spatial heterogeneity as a key state variable in urban traffic systems. By using the dispersion parameter of the negative binomial distribution as a bridge, the framework captures the temporal evolution of spatial dispersion of link accumulation, interpreted as a proxy measure of network homogeneity, and its interaction with network accumulation. This relationship is further extended to describe the evolution of accumulation heterogeneity across links. The model is evaluated using simulation data under both uncongested and congested traffic conditions. Results suggest that the proposed framework can capture the dynamic evolution of network heterogeneity in both regimes. Moreover, the model provides a physically interpretable mechanism for explaining hysteresis phenomena and establishes a foundation for improved aggregate traffic modeling and control.