Percolation properties in a traffic model

TL;DR

This paper investigates how traffic flow transitions from free to congested states at a city scale using a lattice-based agent model, revealing a critical traffic volume where percolation properties change significantly.

Contribution

It introduces a simulation-based analysis of traffic percolation on a lattice, identifying a critical traffic volume and its relation to spatial correlations in traffic flow.

Findings

Percolation threshold decreases with increasing traffic volume.

Minimum percolation threshold occurs at the critical traffic volume.

Longest spatial correlations are observed at the critical point.

Abstract

As a dynamical complex system, traffic is characterized by a transition from free flow to congestions, which is mostly studied in highways. However, despite its importance in developing congestion mitigation strategies, the understanding of this common traffic phenomenon in a city-scale is still missing. An open question is how the traffic in the network collapses from a global efficient traffic to isolated local flows in small clusters, i.e. the question of traffic percolation. Here we study the traffic percolation properties on a lattice by simulation of an agent-based model for traffic. A critical traffic volume in this model distinguishes the free-state from congested state of traffic. Our results show that the threshold of traffic percolation decreases with increasing traffic volume and reaches a minimum value at the critical traffic volume. We show that this minimal threshold is the result of longest spatial correlation between traffic flows at the critical traffic volume. These findings may help to develop congestion mitigation strategies in a network view.