Graph Theory and Metro Traffic Modelling

TL;DR

This paper applies graph theory to analyze the London underground network, identifying influential stations and assessing the impact of closures to improve network resilience and connectivity.

Contribution

It introduces an innovative method using graph theory for vulnerability analysis and impact assessment of station closures in metro networks.

Findings

Identifies key stations with greatest influence on network functionality

Provides a mathematical framework for vulnerability analysis

Offers insights for optimizing metro network resilience

Abstract

In this article we demonstrate how graph theory can be used to identify those stations in the London underground network which have the greatest influence on the functionality of the traffic, and proceed, in an innovative way, to assess the impact of a station closure on service levels across the city. Such underground network vulnerability analysis offers the opportunity to analyse, optimize and enhance the connectivity of the London underground network in a mathematically tractable and physically meaningful manner.