A model to identify urban traffic congestion hotspots in complex networks

TL;DR

This paper introduces the Microscopic Congestion Model, an analytical tool based on complex network phenomena, to predict potential traffic congestion hotspots in urban road networks, aiding in urban mobility management.

Contribution

The paper presents a novel idealized model that predicts congestion hotspots in urban networks using complex network critical phenomena, validated with real city data.

Findings

Model accurately identifies susceptible junctions.

Predicts hotspots under increased mobility demand.

Effective with real-traffic data.

Abstract

Traffic congestion is one of the most notable problems arising in worldwide urban areas, importantly compromising human mobility and air quality. Current technologies to sense real-time data about cities, and its open distribution for analysis, allow the advent of new approaches for improvement and control. Here, we propose an idealized model, the Microscopic Congestion Model, based on the critical phenomena arising in complex networks, that allows to analytically predict congestion hotspots in urban environments. Results on real cities' road networks, considering, in some experiments, real-traffic data, show that the proposed model is capable of identifying susceptible junctions that might become hotspots if mobility demand increases.