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

Meead Saberi, Homayoun Hamedmoghadam, Mudabber Ashfaq, Seyed Amir Hosseini, Ziyuan Gu, Sajjad Shafiei, Divya J. Nair, Vinayak Dixit, Lauren Gardner, S. Travis Waller, Marta C. González

2020Nature Communications168 citationsDOIOpen Access PDF

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 macroscopic characteristics for network traffic dynamics, namely congestion propagation rate β and congestion dissipation rate μ. We describe the dynamics of congestion spread using these new parameters embedded within a system of ordinary differential equations, similar 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.

Topics & Concepts

Computer scienceTraffic congestionProcess (computing)Network congestionSimple (philosophy)JAMSDissipationDistributed computingThree-phase traffic theoryTraffic congestion reconstruction with Kerner's three-phase theoryMathematical modelSimulationDifferential (mechanical device)Computer networkNetwork dynamicsComplex networkProcess dynamicsTraffic flow (computer networking)Empirical researchOrdinary differential equationTraffic waveVehicle dynamicsDynamics (music)Microscopic traffic flow modelNetwork modelComplex Network Analysis TechniquesCOVID-19 epidemiological studiesTraffic control and management