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Robustness Analysis of Urban Road Networks from Topological and Operational Perspectives

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  • Wen-Long Shang
  • Yanyan Chen
  • Chengcheng Song
  • Washington Y. Ochieng

Abstract

This study comprehensively analyses the robustness of urban road networks through topological indices based on the complex network theory and operational indices based on traffic assignment theory: User Equilibrium (UE), System Optimum (SO), and Price of Anarchy (POA). Analysing topological indices may pin down the most important nodes for URNs from the perspective of connectivity, while more sophisticated operational indices are helpful to examine the importance of nodes for URNs by taking into account link capacity, travel demand, and drivers’ behaviour. The previous way is calculated in a static way, which reduces the computation times and increases the efficiency for quick assessment of the robustness of URNs, while the latter is in a dynamic way, namely, calculating is based on removal of individual nodes, although this way is more likely to capture realistic meanings but consumes huge amount of time. The efforts made in this study try to find the relationship between topological and operational indices so as to assist the assessment of robustness of URNs to local disruptions. Seven realistic urban road networks such as Sioux Falls and Anaheim are used as network examples, and results show that different indices reflect robustness characteristics of urban road networks from different ways, and rank correlations between any two indices are poor although small network such as Sioux Falls have better correlations than others.

Suggested Citation

  • Wen-Long Shang & Yanyan Chen & Chengcheng Song & Washington Y. Ochieng, 2020. "Robustness Analysis of Urban Road Networks from Topological and Operational Perspectives," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-12, August.
  • Handle: RePEc:hin:jnlmpe:5875803
    DOI: 10.1155/2020/5875803
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    1. Qiao, Dongdong & Wei, Xuezhe & Fan, Wenjun & Jiang, Bo & Lai, Xin & Zheng, Yuejiu & Tang, Xiaolin & Dai, Haifeng, 2022. "Toward safe carbon–neutral transportation: Battery internal short circuit diagnosis based on cloud data for electric vehicles," Applied Energy, Elsevier, vol. 317(C).
    2. Yu, Qing & Li, Weifeng & Zhang, Haoran & Chen, Jinyu, 2022. "GPS data in taxi-sharing system: Analysis of potential demand and assessment of fuel consumption based on routing probability model," Applied Energy, Elsevier, vol. 314(C).
    3. Chen, Haoqian & Sui, Yi & Shang, Wen-long & Sun, Rencheng & Chen, Zhiheng & Wang, Changying & Han, Chunjia & Zhang, Yuqian & Zhang, Haoran, 2022. "Towards renewable public transport: Mining the performance of electric buses using solar-radiation as an auxiliary power source," Applied Energy, Elsevier, vol. 325(C).
    4. Schuster, Hannah & Polleres, Axel & Wachs, Johannes, 2024. "Stress-testing road networks and access to medical care," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    5. Shang, Wen-Long & Chen, Jinyu & Bi, Huibo & Sui, Yi & Chen, Yanyan & Yu, Haitao, 2021. "Impacts of COVID-19 pandemic on user behaviors and environmental benefits of bike sharing: A big-data analysis," Applied Energy, Elsevier, vol. 285(C).
    6. Chen Zeng & Zhe Zhao & Cheng Wen & Jing Yang & Tianyu Lv, 2020. "Effect of Complex Road Networks on Intensive Land Use in China’s Beijing-Tianjin-Hebei Urban Agglomeration," Land, MDPI, vol. 9(12), pages 1-19, December.
    7. Liu, Qing & Yang, Yang & Ng, Adolf K.Y. & Jiang, Changmin, 2023. "An analysis on the resilience of the European port network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(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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