Public transport networks: empirical analysis and modeling

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.

19 pages, 23 figures

References in corpus (34)

• Emergence of scaling in random networks
• Statistical mechanics of complex networks
• The structure and function of complex networks
• Efficient Behavior of Small-World Networks
• Assortative mixing in networks
• The architecture of complex weighted networks
• Random graphs with arbitrary degree distributions and their applications
• Evolution of networks
• Mixing patterns in networks
• Classes of behavior of small-world networks
• Mean-field theory for scale-free random networks
• The worldwide air transportation network: Anomalous centrality, community structure, and cities' global roles
• Structural Vulnerability of the North American Power Grid
• Small-world properties of the Indian Railway network
• Is the Boston subway a small-world network ?
• The spatial structure of networks
• Statistical Analysis of Airport Network of China
• Statistical analysis of 22 public transport networks in Poland
• Structural Properties of Planar Graphs of Urban Street Patterns
• Harmony in the Small-World
• Percolation Critical Exponents in Scale-Free Networks
• Bipartite Graphs as Models of Complex Networks
• Self-organization of collaboration networks
• Scale-free Networks from Optimal Design
• Stations, trains and small-world networks
• Small-worlds: How and why
• Scaling and correlations in three bus-transport networks of China
• Mean-field theory for clustering coefficients in Barabasi-Albert networks
• Network Harness: Metropolis Public Transport
• Universal scaling of distances in complex networks
• Polymers in long-range-correlated disorder
• How to fit the degree distribution of the air network?
• Degree-dependent intervertex separation in complex networks
• Where two fractals meet: the scaling of a self-avoiding walk on a percolation cluster

Cited by in corpus (19)

• Human Mobility: Models and Applications
• Resilience of public transport networks against attacks
• The Multilayer Temporal Network of Public Transport in Great Britain
• Complex systems: physics beyond physics
• Urban road networks -- Spatial networks with universal geometric features? A case study on Germany's largest cities
• A tale of two cities. Vulnerabilities of the London and Paris transit networks
• Statistical Analysis of Bus Networks in India
• Measuring Road Network Topology Vulnerability by Ricci Curvature
• Transportation Network Stability: a Case Study of City Traffic
• Network structure of subway passenger flows
• Public transportation in UK viewed as a complex network
• Application of a Quantum Ensemble Model to Linguistic Analysis
• A complex network analysis of hypertension-related genes
• Fractal transit networks: self-avoiding walks and Lévy flights
• Evolution of transport under cumulative damage in metro systems
• Pendular behavior of public transport networks
• gtfs2vec -- Learning GTFS Embeddings for comparing Public Transport Offer in Microregions
• StationRank: Aggregate dynamics of the Swiss railway
• Unveiling connectivity patterns of railway timetables through complex network theory and Infomap clustering