A model to identify urban traffic congestion hotspots in complex networks

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.

8 pages, 4 figures

References in corpus (5)

• Critical phenomena in complex networks
• Dynamics of jamming transitions in complex networks
• Optimal routing on complex networks
• Congestion phenomena on complex networks
• Congestion and decongestion in a communication network

Cited by in corpus (7)

• Decongestion of urban areas with hotspot-pricing
• Effect of shortest path multiplicity on congestion of multiplex networks
• Scaling in the recovery of urban transportation systems from special events
• Multiple abrupt phase transitions in urban transport congestion
• Emergence of spatial transitions in urban congestion dynamics
• A link model approach to identify congestion hotspots
• Spatio-Temporal Point Processes with Attention for Traffic Congestion Event Modeling