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Measuring health of highway network configuration against dynamic Origin-Destination demand network using weighted complex network analysis

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  • Sehyun Tak
  • Sunghoon Kim
  • Young-Ji Byon
  • Donghoun Lee
  • Hwasoo Yeo

Abstract

Ideal configuration or layout of highways should resemble the actual demands for the roads represented by Origin-Destination (OD) information. It would be beneficial if existing highways can be evaluated for their configurational fitness against the current demands, and newly planned highways can carefully be designed in terms of their layouts and topologies that would reflect the demands. Analysis techniques used for complex networks in the matured field of network theory can be applied for the highway layout health monitoring against the current OD information. This paper proposes a methodology of measuring the fitness of existing highways by comparing their structural configuration against conceptual OD networks using well-established techniques in network theory for complex networks. In the first phase, this paper conducts an empirical analysis and finds that both structural highway network and OD network follow the “power law” distribution as they are weighted by capacity and traffic volume respectively. It is also found that the power law coefficient of the OD network dynamically changes throughout the day and week. In the second phase, a noble methodology of weighting and measuring the health, of structural highway networks against OD networks by means of comparing their power law coefficients is proposed. It is found that the proposed method is effective at detecting deviations from ideal structural configurations associated with actual demands.

Suggested Citation

  • Sehyun Tak & Sunghoon Kim & Young-Ji Byon & Donghoun Lee & Hwasoo Yeo, 2018. "Measuring health of highway network configuration against dynamic Origin-Destination demand network using weighted complex network analysis," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-21, November.
  • Handle: RePEc:plo:pone00:0206538
    DOI: 10.1371/journal.pone.0206538
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    References listed on IDEAS

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    1. Jiang, Bin, 2007. "A topological pattern of urban street networks: Universality and peculiarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 647-655.
    2. Li, W. & Cai, X., 2007. "Empirical analysis of a scale-free railway network in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(2), pages 693-703.
    3. Alexander Erath & Michael Löchl & Kay Axhausen, 2009. "Graph-Theoretical Analysis of the Swiss Road and Railway Networks Over Time," Networks and Spatial Economics, Springer, vol. 9(3), pages 379-400, September.
    4. Jingyi Lin & Yifang Ban, 2013. "Complex Network Topology of Transportation Systems," Transport Reviews, Taylor & Francis Journals, vol. 33(6), pages 658-685, November.
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    Cited by:

    1. Jin, Kun & Wang, Wei & Li, Xinran & Chen, Siyuan & Qin, Shaoyang & Hua, Xuedong, 2023. "Cascading failure in urban rail transit network considering demand variation and time delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    2. Shiguang Wang & Dexin Yu & Mei-Po Kwan & Huxing Zhou & Yongxing Li & Hongzhi Miao, 2019. "The Evolution and Growth Patterns of the Road Network in a Medium-Sized Developing City: A Historical Investigation of Changchun, China, from 1912 to 2017," Sustainability, MDPI, vol. 11(19), pages 1-25, September.
    3. Jin, Kun & Wang, Wei & Li, Xinran & Hua, Xuedong & Qin, Shaoyang, 2022. "Exploring the robustness of public transportation system on augmented network: A case from Nanjing China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).

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