Scale-free Resilience of Real Traffic Jams

TL;DR

This paper defines and analyzes the scale-free statistical properties of traffic resilience in urban and highway systems, revealing universal patterns in congestion recovery dynamics.

Contribution

It introduces a new definition of traffic resilience based on congestion clusters and uncovers universal scale-free distributions and scaling relations.

Findings

Resilience follows a scale-free distribution in city and highway networks.

Different cities and days show similar exponents in resilience distribution.

A novel scaling relation links cluster size to recovery duration, independent of microscopic details.

Abstract

The concept of resilience can be realized in natural and engineering systems, representing the ability of system to adapt and recover from various disturbances. Although resilience is a critical property needed for understanding and managing the risks and collapses of transportation system, an accepted and useful definition of resilience for urban traffic as well as its statistical property under perturbations is still missing. Here we define city traffic resilience based on the spatio-temporal clusters of congestion in real traffic, and find that the resilience follows a scale free distribution in two-dimensional city road networks and one-dimensional highways, with different exponents, but similar exponents in different days and different cities. The traffic resilience is also revealed to have a novel scaling relation between the cluster size of the spatio-temporal jam and its recovery duration, independent of microscopic details. Our findings of universal traffic resilience can provide indication towards better understanding and designing these complex engineering systems under internal and external disturbances.