Identification and prioritization of urban traffic bottlenecks

TL;DR

This paper introduces a comprehensive network analysis methodology to identify, evaluate, and prioritize urban traffic bottlenecks, aiding in better traffic management and congestion reduction strategies.

Contribution

It extends existing methods by applying network analysis to entire road systems, enabling dynamic tracking and prioritization of traffic bottlenecks over time and space.

Findings

Traffic bottlenecks exhibit macro-stability with consistent scaling characteristics.

Bottleneck locations change dynamically, influenced by meso-dynamics.

The proposed framework effectively evaluates the impact of evolving bottlenecks on the entire network.

Abstract

The increasing urbanization process we have been witnessing in the last decades is accompanied by a significant increase in traffic congestion in cities around the world. The effect of the congestion is represented in the enormous time people spent on roads leading to significant money waste and air pollution. Here, we present a new methodology for identification, cost evaluation, and thus, prioritization of congestion sources, the jam bottlenecks. It extends existing methods as it is based on network analysis of the entire road network and can be applied to different traffic models. Our results show that the macro-stability, presented by scaling characteristics of the traffic bottlenecks, overshadows the existence of meso-dynamics, where the bottlenecks change their location in time and space. This means that to plan and manage traffic jams in different locations and at different times, it is required to implement a framework, as developed here, that tracks traffic and evaluates the relative effect of each evolving bottleneck on the entire road network.