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Establishment and Analysis of the Supernetwork Model for Nanjing Metro Transportation System

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  • Yu Wei
  • Sun Ning

Abstract

In recent years, many researchers have applied complex network theory to urban public transport network to construct complex network and analyze its network performance. The original analysis method generally uses the Space L and Space R model to establish a simple link between public sites but ignores the organic link between the overall network system and the line subsystem. As an important part of urban public transport system, subway plays an important role in alleviating traffic pressure. In this paper, a supernetwork model of Nanjing metro network is established by using the supernetwork method. Three parameters, node-hyperedge degree, hyperedge-node degree, and hyperedge degree, are proposed to describe the model. The model is compared with the traditional Space L and Space P models. The study on the supernetwork model of Nanjing metro complex network shows that the network density, network centrality, and network clustering coefficient are large, and the average network distance is small, which meets the requirements of traffic planning and design. In this study, the subway line is considered as a subsystem and further simplified as a node, so that the complex network analysis method can be applied to the new supernetwork model, expanding the thinking of complex network research.

Suggested Citation

  • Yu Wei & Sun Ning, 2018. "Establishment and Analysis of the Supernetwork Model for Nanjing Metro Transportation System," Complexity, Hindawi, vol. 2018, pages 1-11, December.
    • Handle: RePEc:hin:complx:4860531
    DOI: 10.1155/2018/4860531
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    Cited by:

    1. Wei Yu & Xiaofei Ye & Jun Chen & Xingchen Yan & Tao Wang, 2020. "Evaluation Indexes and Correlation Analysis of Origination–Destination Travel Time of Nanjing Metro Based on Complex Network Method," Sustainability, MDPI, vol. 12(3), pages 1-21, February.
    2. Ming Li & Wei Yu & Jun Zhang, 2023. "Clustering Analysis of Multilayer Complex Network of Nanjing Metro Based on Traffic Line and Passenger Flow Big Data," Sustainability, MDPI, vol. 15(12), pages 1-17, June.
    3. Wei Yu & Tao Wang & Yujie Xiao & Jun Chen & Xingchen Yan, 2020. "A Carbon Emission Measurement Method for Individual Travel Based on Transportation Big Data: The Case of Nanjing Metro," IJERPH, MDPI, vol. 17(16), pages 1-15, August.
    4. Zhiru Wang & Wubin Ma & Albert Chan, 2020. "Exploring the Relationships between the Topological Characteristics of Subway Networks and Service Disruption Impact," Sustainability, MDPI, vol. 12(10), pages 1-18, May.
    5. Chen, Junlan & Pu, Ziyuan & Guo, Xiucheng & Cao, Jieyu & Zhang, Fang, 2023. "Multiperiod metro timetable optimization based on the complex network and dynamic travel demand," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).

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