Public transport networks: empirical analysis and modeling

TL;DR

This paper analyzes urban public transport networks using complex network theory, comparing properties across 14 cities, and proposes a simple growth model based on self-avoiding walks that reproduces key network features.

Contribution

It provides a comprehensive empirical analysis of PTNs across multiple cities and introduces a novel growth model capturing essential network characteristics.

Findings

PTNs exhibit specific statistical properties relevant to passengers.

Different network representations reveal diverse features of PTNs.

A simple growth model with self-avoiding walks can replicate many PTN properties.

Abstract

We use complex network concepts to analyze statistical properties of urban public transport networks (PTN). To this end, we present a comprehensive survey of the statistical properties of PTNs based on the data of fourteen cities of so far unexplored network size. Especially helpful in our analysis are different network representations. Within a comprehensive approach we calculate PTN characteristics in all of these representations and perform a comparative analysis. The standard network characteristics obtained in this way often correspond to features that are of practical importance to a passenger using public traffic in a given city. Specific features are addressed that are unique to PTNs and networks with similar transport functions (such as networks of neurons, cables, pipes, vessels embedded in 2D or 3D space). Based on the empirical survey, we propose a model that albeit being simple enough is capable of reproducing many of the identified PTN properties. A central ingredient of this model is a growth dynamics in terms of routes represented by self-avoiding walks.