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Space evolution model and empirical analysis of an urban public transport network

Author

Listed:
  • Sui, Yi
  • Shao, Feng-jing
  • Sun, Ren-cheng
  • Li, Shu-jing

Abstract

This study explores the space evolution of an urban public transport network, using empirical evidence and a simulation model validated on that data. Public transport patterns primarily depend on traffic spatial-distribution, demands of passengers and expected utility of investors. Evolution is an iterative process of satisfying the needs of passengers and investors based on a given traffic spatial-distribution. The temporal change of urban public transport network is evaluated both using topological measures and spatial ones. The simulation model is validated using empirical data from nine big cities in China. Statistical analyses on topological and spatial attributes suggest that an evolution network with traffic demands characterized by power-law numerical values which distribute in a mode of concentric circles tallies well with these nine cities.

Suggested Citation

  • Sui, Yi & Shao, Feng-jing & Sun, Ren-cheng & Li, Shu-jing, 2012. "Space evolution model and empirical analysis of an urban public transport network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(14), pages 3708-3717.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:14:p:3708-3717
    DOI: 10.1016/j.physa.2012.01.011
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    Citations

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    Cited by:

    1. Yang, Zhijie & Chen, Xiaolong, 2018. "Evolution assessment of Shanghai Urban Rail Transit Network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1263-1274.
    2. Wang, Zhiru & Niu, Fangyan & Yang, Lili & Su, Guofeng, 2020. "Modeling a subway network: A hot-point attraction-driven evolution mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    3. Meng, Yangyang & Tian, Xiangliang & Li, Zhongwen & Zhou, Wei & Zhou, Zhijie & Zhong, Maohua, 2020. "Comparison analysis on complex topological network models of urban rail transit: A case study of Shenzhen Metro in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    4. Yang, Xu-Hua & Chen, Guang & Chen, Sheng-Yong & Wang, Wan-Liang & Wang, Lei, 2014. "Study on some bus transport networks in China with considering spatial characteristics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 1-10.
    5. Lin Zhang & Jian Lu & Bai-bai Fu & Shu-bin Li, 2018. "A Review and Prospect for the Complexity and Resilience of Urban Public Transit Network Based on Complex Network Theory," Complexity, Hindawi, vol. 2018, pages 1-36, December.
    6. Pu, Han & Li, Yinzhen & Ma, Changxi, 2022. "Topology analysis of Lanzhou public transport network based on double-layer complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    7. Zhang, Dezhi & Zhang, Fangtao & Liang, Yijing, 2021. "An evolutionary model of the international logistics network based on the Belt and Road perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    8. Zhang, Mengyao & Huang, Tao & Guo, Zhaoxia & He, Zhenggang, 2022. "Complex-network-based traffic network analysis and dynamics: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).

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