Public transport networks: empirical analysis and modeling

By Christian von Ferber, Taras Holovatch, Yurij Holovatch, Vasyl Palchykov. 2008

348 citations recorded by the source corpus.

Public transport networks of fourteen cities of so far unexplored network size are analyzed in standardized graph representations: the simple graph of the network map, the bipartite graph of routes and stations, and both one mode projections of the latter. Special attention is paid to the inter-relations and spatial embedding of transport routes. This systematic approach reveals rich behavior beyond that of the ubiquitous scale-free complex network. We find strong evidence for structures in PTNs that are counter-intuitive and need to be explained, among these a pronounced diversity in the expression of typical network characteristics within the present sample of cities, a surprising geometrical behavior with respect to the two-dimensional geographical embedding and an unexpected attraction between transport routes. A simple model based on these observations reproduces many of the identified PTN properties by growing networks of attractive self-avoiding walks.

Subfields: Building and Construction, Statistical and Nonlinear Physics, Transportation

View Paper: https://www.semanticscholar.org/paper/a2274127de30a818d4a0d61cb8c5245c67b2ef3b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Marc Barthelemy

In Statistical and Nonlinear Physics

1. Stefan Thurner 4
2. Myriam Regattieri de Biase da Silva Delgado
3. Yurij Holovatch
4. Ralph Kenna
5. Keiko Verônica Ono Fonseca
6. Ricardo Lüders
7. Marcelo de Oliveira Rosa
8. Marc Barthelemy

In Transportation

1. Stefan Thurner 4
2. Yurij Holovatch
3. Ralph Kenna
4. Marc Barthelemy
5. Geoff Boeing

Citations in the corpus

• Spatial Networks (2010, background): “The ratio 〈C〉/CER is explicitly considered in [305] and is usually much larger than one (in the range [41, 625]).”
• Complex systems: physics beyond physics (2016, background): “) [14] Hong S-Y, Koo M-S, Jang J, Kim J-E E, Park H, Joh M-S, Kang J-H and Oh T-J 2013 An Evaluation of the Software System Dependency of a Global Atmospheric ModelMonthly Weather Review 141 4165-4172 [15] Gell-Mann M and Lloyd S (1996) Information measures, effective complexity, and total informati”
• Analysis of Public Bus Transportation of a Brazilian City Based on the Theory of Complex Networks Using the P-Space (2016, background): “Later, those authors [12] proposed an evolutionary model of mapping PTS growth in order to conduct a more comprehensive analysis.”