IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i12p4956-d1412038.html
   My bibliography  Save this article

Urban Traffic Dominance: A Dynamic Assessment Using Multi-Source Data in Shanghai

Author

Listed:
  • Yuyang Mei

    (Changwang School of Honors, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Shenmin Wang

    (School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Mengjie Gong

    (School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China)

  • Jiazheng Chen

    (Changwang School of Honors, Nanjing University of Information Science & Technology, Nanjing 210044, China)

Abstract

This study redefines the evaluation of urban traffic dominance by integrating complex network theory with multi-source spatiotemporal trajectory data, addressing the dynamic nature of various transportation modes, including public transit and shared mobility. Traditional traffic studies, which focus predominantly on static road traffic characteristics, overlook the fluid dynamics integral to urban transport systems. We introduce Relative Weighted Centrality (RWC) as a novel metric for quantifying dynamic traffic dominance, combining it with traditional static metrics to forge a comprehensive traffic dominance evaluation system. The results show the following: (1) Both static and dynamic traffic dominance display core-periphery structures centered around Huangpu District. (2) Dynamically, distinct variations in RWC emerge across different times and transport modes; during the early hours (0:00–6:00), shared bicycles show unique spatial distributions, the subway network experiences a notable decrease in RWC yet maintains its spatial pattern, and taxis exhibit intermediate characteristics. Conversely, the RWC for all modes generally increases during morning (6:00–12:00) and evening (18:00–24:00) peaks, with a pronounced decrease in subway RWC in the latter period. (3) The integration of dynamic evaluations significantly modifies conventional static results, emphasizing the impact of population movements on traffic dominance. This comprehensive analysis provides crucial insights into the strategic management and development of urban traffic infrastructure in Shanghai.

Suggested Citation

  • Yuyang Mei & Shenmin Wang & Mengjie Gong & Jiazheng Chen, 2024. "Urban Traffic Dominance: A Dynamic Assessment Using Multi-Source Data in Shanghai," Sustainability, MDPI, vol. 16(12), pages 1-23, June.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:12:p:4956-:d:1412038
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/12/4956/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/12/4956/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. An, Xin-lei & Zhang, Li & Li, Yin-zhen & Zhang, Jian-gang, 2014. "Synchronization analysis of complex networks with multi-weights and its application in public traffic network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 412(C), pages 149-156.
    2. Seaton, Katherine A. & Hackett, Lisa M., 2004. "Stations, trains and small-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(3), pages 635-644.
    3. Julin Li & Tongsheng Li & Bingchen Zhu & Yilin Wang & Xieyang Chen & Ruikuan Liu, 2023. "The Spatial Pattern and Influencing Factors of Traffic Dominance in Xi’an Metropolitan Area," Land, MDPI, vol. 12(6), pages 1-20, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xueguo Xu & Chen Xu & Wenxin Zhang, 2022. "Research on the Destruction Resistance of Giant Urban Rail Transit Network from the Perspective of Vulnerability," Sustainability, MDPI, vol. 14(12), pages 1-26, June.
    2. Yujin Lu & Xingmeng Xu & Gaoru Zhu & Yuting Peng & Yi Li & Xueyan Zhao, 2024. "Land Space and High-Speed Transportation Coordinated Development Evaluation in the Beijing–Tianjin–Hebei Urban Agglomeration of China," Land, MDPI, vol. 13(10), pages 1-27, October.
    3. Lordan, Oriol & Sallan, Jose M., 2019. "Core and critical cities of global region airport networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 724-733.
    4. Xuelei Meng & Yahui Wang & Limin Jia & Lei Li, 2020. "Reliability Optimization of a Railway Network," Sustainability, MDPI, vol. 12(23), pages 1-27, November.
    5. Wen, Tao & Jiang, Wen, 2018. "An information dimension of weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 388-399.
    6. Shi, Jinyao & Zhou, Peipei & Cai, Shuiming & Jia, Qiang, 2023. "Exponential synchronization for multi-weighted dynamic networks via finite-level quantized control with adaptive scaling gain," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    7. Yi Junmin, 2014. "System Planning of Route Diagram for China Railway Passengers Based on Network and Ergonomics," Journal of Systems Science and Information, De Gruyter, vol. 2(2), pages 170-177, April.
    8. 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.
    9. Zhang, Qi & Luo, Chuanhai & Li, Meizhu & Deng, Yong & Mahadevan, Sankaran, 2015. "Tsallis information dimension of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 707-717.
    10. Aldrich, Preston R. & El-Zabet, Jermeen & Hassan, Seerat & Briguglio, Joseph & Aliaj, Enela & Radcliffe, Maria & Mirza, Taha & Comar, Timothy & Nadolski, Jeremy & Huebner, Cynthia D., 2015. "Monte Carlo tests of small-world architecture for coarse-grained networks of the United States railroad and highway transportation systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 32-39.
    11. Haifeng Du & Jiarui Fan & Xiaochen He & Marcus W. Feldman, 2018. "A Genetic Simulated Annealing Algorithm to Optimize the Small-World Network Generating Process," Complexity, Hindawi, vol. 2018, pages 1-12, November.
    12. Guo, Beibei & Xiao, Yu, 2023. "Intermittent synchronization for multi-link and multi-delayed large-scale systems with semi-Markov jump and its application of Chua’s circuits," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    13. Bingxue Qian & Ning Zhang, 2022. "Topology and Robustness of Weighted Air Transport Networks in Multi-Airport Region," Sustainability, MDPI, vol. 14(11), pages 1-15, June.
    14. Dupuy, Gabriel, 2013. "Network geometry and the urban railway system: the potential benefits to geographers of harnessing inputs from “naive” outsiders," Journal of Transport Geography, Elsevier, vol. 33(C), pages 85-94.
    15. Junjun Zheng & Yi Cheng & Gang Ma & Xue Han & Liukai Yu, 2020. "Feasibility Analysis of Green Travel in Public Transportation: A Case Study of Wuhan," Sustainability, MDPI, vol. 12(16), pages 1-22, August.
    16. Zhang, Chunmei & Han, Bang-Sheng, 2020. "Stability analysis of stochastic delayed complex networks with multi-weights based on Razumikhin technique and graph theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    17. Du, Zhouyang & Tang, Jinjun & Qi, Yong & Wang, Yiwei & Han, Chunyang & Yang, Yifan, 2020. "Identifying critical nodes in metro network considering topological potential: A case study in Shenzhen city—China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    18. Calzada-Infante, L. & Adenso-Díaz, B. & García Carbajal, S., 2020. "Analysis of the European international railway network and passenger transfers," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    19. Roanes-Lozano, Eugenio & Laita, Luis M. & Roanes-Macías, Eugenio & Wester, Michael J. & Ruiz-Lozano, José Luis & Roncero, Carlos, 2009. "Evolution of railway network flexibility: The Spanish broad gauge case," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2317-2332.
    20. Dimitrov, Stavri Dimitri & Ceder, Avishai (Avi), 2016. "A method of examining the structure and topological properties of public-transport networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 373-387.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:12:p:4956-:d:1412038. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.