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 and Marta C. González
Additional contact information
Meead Saberi: University of New South Wales (UNSW)
Homayoun Hamedmoghadam: Monash University
Mudabber Ashfaq: University of New South Wales (UNSW)
Seyed Amir Hosseini: K.N. Toosi University of Technology
Ziyuan Gu: University of New South Wales (UNSW)
Sajjad Shafiei: CSIRO
Divya J. Nair: University of New South Wales (UNSW)
Vinayak Dixit: University of New South Wales (UNSW)
Lauren Gardner: Johns Hopkins University
S. Travis Waller: University of New South Wales (UNSW)
Marta C. González: University of California

Nature Communications, 2020, vol. 11, issue 1, 1-9

Abstract: 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.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15353-2

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DOI: 10.1038/s41467-020-15353-2

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