A simple contagion process describes spreading of traffic jams in urban networks
For urban traffic engineers and city planners, this provides a simple, computationally efficient framework for monitoring and controlling congestion dynamics.
This paper models traffic jam propagation in urban networks as a simple contagion process, introducing congestion propagation and dissipation rates. The model, validated with empirical data from multiple cities, accurately predicts the fraction of congested links over time.
The spread of traffic jams in urban networks has long been viewed as a complex spatio-temporal phenomenon that often requires computationally intensive microscopic models for analysis purposes. In this study, we present a framework to describe the dynamics of congestion propagation and dissipation of traffic in cities using a simple contagion process, inspired by those used to model infectious disease spread in a population. We introduce two novel macroscopic characteristics of network traffic, namely congestion propagation rate \b{eta} and congestion dissipation rate μ. We describe the dynamics of congestion propagation and dissipation using these new parameters, \b{eta}, and μ, embedded within a system of ordinary differential equations, analogous to the well-known Susceptible-Infected-Recovered (SIR) model. The proposed contagion-based dynamics are verified through an empirical multi-city analysis, and can be used to monitor, predict and control the fraction of congested links in the network over time.