A novel evolving model of urban rail transit networks based on the local-world theory

Shumin Feng, Mengwei Xin, Tianling Lv and Baoyu Hu

Physica A: Statistical Mechanics and its Applications, 2019, vol. 535, issue C

Abstract: Since the expansion of the scale of urban rail construction, the networked structure is becoming a significant characteristic of rail transit systems. For a further understanding of the networked structure, the evolution mechanism of the rail transit network is worth research and discussion. To select the most appropriate modeling space, four topological spaces (L-Space, P-Space, B-Space, and R-Space) are analyzed based on three indicators (degree distribution, clustering coefficient, and average length); P-space is selected as the basic space for topology because of its high clustering coefficient and low average length. The topological network, which is obtained by P-space, shows exponential degree distribution and local-world characteristics. After dissecting the evolution law of degree distribution and other parameters and the connection mechanism of rail transit topology, the improved local-world evolving model of urban rail transit networks (URTNs) is developed. The model is verified by its application in six cities’ rail-transit networks (London, New York, Paris, Beijing, Shanghai, and Shenzhen). The results show little difference between the real network and evolving network, with a high consistency of their degree distributions and the network indicators. These illustrate that the model can reflect the real characteristics of URTNs and that it can be used to generate a new network that has a similar structure to the real network.

Keywords: Urban rail transit network; Local-world characteristics; Evolution law; Connection mechanism; Local-world evolving model (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:535:y:2019:i:c:s0378437119312919

DOI: 10.1016/j.physa.2019.122227

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