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The role of travel demand and network centrality on the connectivity and resilience of an urban street system

Author

Listed:
  • Meisam Akbarzadeh

    (Isfahan University of Technology)

  • Soroush Memarmontazerin

    (Isfahan University of Technology)

  • Sybil Derrible

    (University of Illinois at Chicago
    University of Illinois at Chicago)

  • Sayed Farzin Salehi Reihani

    (Isfahan University of Technology)

Abstract

In the transportation literature, two major and parallel approaches exist to identify the critical elements of a transportation system. On the one hand, conventional transportation engineering emphasizes travel demand, often in terms of traffic volume (i.e., demand side). On the other hand, newer techniques from Network Science emphasize network topology (i.e., supply side). To better understand the relationship between the two approaches, we first investigate whether they correlate by comparing traffic volume and node centrality. Second, we assess the impact of the two approaches on the connectivity and resilience of a transportation network; connectivity is measured by the relative size of the giant component, and resilience is measured by the network’s adaptive capacity (the amount of extra flow it can handle). The urban road system of Isfahan (Iran) is used as a practical case study. Overall, we find that traffic volume indeed correlates with node centrality. In addition, we find that the weighted degree of a node, i.e., the sum of the capacities of its incident links (for small disruptions) and node betweenness (for large disruptions), best captures node criticality. Nodes with high weighted degree and betweenness should therefore be given higher priority to enhance connectivity and resilience in urban street systems. Regarding link criticality, roads with higher capacities showed a more important role as opposed to betweenness, flow, and congestion.

Suggested Citation

  • Meisam Akbarzadeh & Soroush Memarmontazerin & Sybil Derrible & Sayed Farzin Salehi Reihani, 2019. "The role of travel demand and network centrality on the connectivity and resilience of an urban street system," Transportation, Springer, vol. 46(4), pages 1127-1141, August.
    • Handle: RePEc:kap:transp:v:46:y:2019:i:4:d:10.1007_s11116-017-9814-y
    DOI: 10.1007/s11116-017-9814-y
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    1. Gao, Cai & Wei, Daijun & Hu, Yong & Mahadevan, Sankaran & Deng, Yong, 2013. "A modified evidential methodology of identifying influential nodes in weighted networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5490-5500.
    2. Sybil Derrible & Nasir Ahmad, 2015. "Network-Based and Binless Frequency Analyses," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-10, November.
    3. Wang, Xiangrong & Koç, Yakup & Derrible, Sybil & Ahmad, Sk Nasir & Pino, Willem J.A. & Kooij, Robert E., 2017. "Multi-criteria robustness analysis of metro networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 19-31.
    4. Liu, Jun & Xiong, Qingyu & Shi, Weiren & Shi, Xin & Wang, Kai, 2016. "Evaluating the importance of nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 209-219.
    5. Tsekeris, Theodore & Geroliminis, Nikolas, 2013. "City size, network structure and traffic congestion," Journal of Urban Economics, Elsevier, vol. 76(C), pages 1-14.
    6. Caitlin D. Cottrill & Sybil Derrible, 2015. "Leveraging Big Data for the Development of Transport Sustainability Indicators," Journal of Urban Technology, Taylor & Francis Journals, vol. 22(1), pages 45-64, January.
    7. Suhyung Yoo & Hwasoo Yeo, 2016. "Evaluation of the resilience of air transportation network with adaptive capacity," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 20(sup1), pages 38-49, July.
    8. Dunn, Sarah & Wilkinson, Sean M., 2016. "Increasing the resilience of air traffic networks using a network graph theory approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 90(C), pages 39-50.
    9. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
    10. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    11. Flaviano Morone & Hernán A. Makse, 2015. "Influence maximization in complex networks through optimal percolation," Nature, Nature, vol. 524(7563), pages 65-68, August.
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