# A simple contagion process describes spreading of traffic jams in urban networks

## TL;DR

This paper models the spread of traffic jams in urban networks using a simple contagion process inspired by epidemiology, introducing new parameters to describe congestion dynamics and validating the approach with empirical data.

## Contribution

It presents a novel contagion-based framework for traffic congestion dynamics, incorporating new macroscopic parameters and validated through multi-city empirical analysis.

## Key findings

- The contagion model accurately describes congestion spread and dissipation.
- New parameters ta and mma effectively capture congestion dynamics.
- Model can be used for monitoring, predicting, and controlling traffic jams.

## Abstract

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 {\mu}. We describe the dynamics of congestion propagation and dissipation using these new parameters, \b{eta}, and {\mu}, 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.

---
Source: https://tomesphere.com/paper/1906.00585