Emergence of Scale-Free Traffic Jams in Highway Networks: A Probabilistic Approach

TL;DR

This paper introduces a probabilistic cascade model explaining the universal scale-free distribution of traffic congestion costs in highway networks, highlighting the role of large traffic surges from single sources.

Contribution

It presents a stochastic model that accounts for the scale-free behavior of congestion costs, linking it to the distribution of traffic intensities and the catastrophe principle.

Findings

Congestion cost follows a scale-free distribution.

Severe congestion is often caused by large traffic originating from a single point.

The scale-free behavior is robust across different propagation rules.

Abstract

Traffic congestion continues to escalate with urbanization and socioeconomic development, necessitating advanced modeling to understand and mitigate its impacts. In large-scale networks, traffic congestion can be studied using cascade models, where congestion not only impacts isolated segments, but also propagates through the network in a domino-like fashion. One metric for understanding these impacts is congestion cost, which is typically defined as the additional travel time caused by traffic jams. Recent data suggests that congestion cost exhibits a universal scale-free-tailed behavior. However, the mechanism driving this phenomenon is not yet well understood. To address this gap, we propose a stochastic cascade model of traffic congestion. We show that traffic congestion cost is driven by the scale-free distribution of traffic intensities. This arises from the catastrophe principle, implying that severe congestion is likely caused by disproportionately large traffic originating from a single location. We also show that the scale-free nature of congestion cost is robust to various congestion propagation rules, explaining the universal scaling observed in empirical data. These findings provide a new perspective in understanding the fundamental drivers of traffic congestion and offer a unifying framework for studying congestion phenomena across diverse traffic networks.