IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i8p6450-d1120340.html
   My bibliography  Save this article

Urban Agglomeration High-Speed Railway Backbone Network Planning: A Case Study of Beijing-Tianjin-Hebei Region, China

Author

Listed:
  • Jun Zhao

    (School of Transportation Engineering, Dalian Jiaotong University, Dalian 116028, China)

  • Wenyu Rong

    (School of Transportation Engineering, Dalian Jiaotong University, Dalian 116028, China)

  • Di Liu

    (School of Transportation Engineering, Dalian Jiaotong University, Dalian 116028, China)

Abstract

In order to optimize the network layout of urban agglomerations, improve the comprehensive benefits of transportation networks and promote the sustainable development of urban agglomerations, this paper studies the main trunk line selection model of the Beijing–Tianjin–Hebei high-speed railway (HSR). Firstly, the characteristics of cities in urban agglomeration are analyzed, and the economic capacity, transportation capacity, passenger turnover and network characteristics of urban nodes are selected as evaluation indexes. A node importance model and a line urgency model were established to obtain the value of the importance of urban nodes and the urgency of each line in the urban agglomeration. Secondly, the DBSCAN is used to cluster the city nodes, and the city nodes are divided into four grades. With the goal of maximizing the urgency of the lines and considering the constraints of the urban node level, the optimization model of the Beijing–Tianjin–Hebei backbone network selection is constructed. The backbone lines of the Beijing–Tianjin–Hebei urban agglomeration are obtained, and the selection results of backbone lines are analyzed, which lays a foundation for the design and optimization of the HSR operation scheme in urban agglomeration. The planned backbone network can basically realize the commuting between the important urban nodes in the Beijing–Tianjin–Hebei urban agglomeration to achieve the goal of driving and alleviating the operation of the branch line. It can accelerate the development of the internal traffic of the urban agglomeration. In addition, it has certain practical significance and practical value.

Suggested Citation

  • Jun Zhao & Wenyu Rong & Di Liu, 2023. "Urban Agglomeration High-Speed Railway Backbone Network Planning: A Case Study of Beijing-Tianjin-Hebei Region, China," Sustainability, MDPI, vol. 15(8), pages 1-22, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6450-:d:1120340
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/8/6450/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/8/6450/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Su, Qingyu & Chen, Cong & Huang, Xin & Li, Jian, 2022. "Interval TrendRank method for grid node importance assessment considering new energy," Applied Energy, Elsevier, vol. 324(C).
    2. Xu, Fei & Li, Qiangyi & Yang, Mian, 2022. "The impacts of high-speed rail on the transformation of resource-based cities in China: A market segmentation perspective," Resources Policy, Elsevier, vol. 78(C).
    3. Danyu Liu & Ke Zhang, 2022. "Analysis of Spatial Differences and the Influencing Factors in Eco-Efficiency of Urban Agglomerations in China," Sustainability, MDPI, vol. 14(19), pages 1-21, October.
    4. Peiqing Li & Longlong Jiang & Shunfeng Zhang & Xi Jiang, 2022. "Demand Response Transit Scheduling Research Based on Urban and Rural Transportation Station Optimization," Sustainability, MDPI, vol. 14(20), pages 1-17, October.
    5. Xuyang Han & Costas Armenakis & Mojgan Jadidi, 2021. "Modeling Vessel Behaviours by Clustering AIS Data Using Optimized DBSCAN," Sustainability, MDPI, vol. 13(15), pages 1-22, July.
    6. Attila Mester & Andrei Pop & Bogdan-Eduard-Mădălin Mursa & Horea Greblă & Laura Dioşan & Camelia Chira, 2021. "Network Analysis Based on Important Node Selection and Community Detection," Mathematics, MDPI, vol. 9(18), pages 1-16, September.
    7. Cuiping Ren & Bianbian Chen & Fengjie Xie & Xuan Zhao & Jiaqian Zhang & Xueyan Zhou, 2022. "Understanding Hazardous Materials Transportation Accidents Based on Higher-Order Network Theory," IJERPH, MDPI, vol. 19(20), pages 1-13, October.
    8. Rui Ding & Jun Fu & Yiming Du & Linyu Du & Tao Zhou & Yilin Zhang & Siwei Shen & Yuqi Zhu & Shihui Chen, 2022. "Structural Evolution and Community Detection of China Rail Transit Route Network," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    9. Gu, Hongyi & Wan, Yulai, 2022. "Airline reactions to high-speed rail entry: Rail quality and market structure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 511-532.
    10. Yafei Xu & Guoli Ou, 2022. "Does High-Speed Railway Promote the Level of Human Capital? An Empirical Analysis Based on Three Urban Agglomerations in China," Sustainability, MDPI, vol. 14(19), pages 1-17, October.
    11. Jian Wang & Yuzhou Deng & Sonia Kumari & Zhihui Song, 2023. "Research on the Spatial Spillover Effect of Transportation Infrastructure on Urban Resilience in Three Major Urban Agglomerations in China," Sustainability, MDPI, vol. 15(6), pages 1-21, March.
    12. Congmou Zhu & Lixia Yang & Qiuyu Xu & Jinwei Fu & Yue Lin & Le Sun & Shan He & Shaofeng Yuan, 2022. "A Comparative Analysis of Farmland Occupation by Urban Sprawl and Rural Settlement Expansion in China," Land, MDPI, vol. 11(10), pages 1-16, October.
    13. Claessens, M. T. & van Dijk, N. M. & Zwaneveld, P. J., 1998. "Cost optimal allocation of rail passenger lines," European Journal of Operational Research, Elsevier, vol. 110(3), pages 474-489, November.
    14. Shalvi Sharma & Sewa Ram, 2023. "Investigation of Road Network Connectivity and Accessibility in Less Accessible Airport Regions: The Case of India," Sustainability, MDPI, vol. 15(7), pages 1-15, March.
    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. Jiayu Ding & Yuewei Wang & Chaoyue Li, 2024. "A Dual-Layer Complex Network-Based Quantitative Flood Vulnerability Assessment Method of Transportation Systems," Land, MDPI, vol. 13(6), pages 1-27, May.
    2. Li, Mengxu & Liu, Jianghua & Chen, Yang & Yang, Zhijiu, 2023. "Can sustainable development strategy reduce income inequality in resource-based regions? A natural resource dependence perspective," Resources Policy, Elsevier, vol. 81(C).
    3. Bugarinovic, Mirjana & Boskovic, Branislav, 2015. "A systems approach to access charges in unbundling railways," European Journal of Operational Research, Elsevier, vol. 240(3), pages 848-860.
    4. Eliasson, Jonas & Börjesson, Maria, 2014. "On timetable assumptions in railway investment appraisal," Transport Policy, Elsevier, vol. 36(C), pages 118-126.
    5. Yu Zhang & Xi Cai & Yanying Mao & Liudan Jiao & Liu Wu, 2023. "What Is the State of Development of Eco-Wellbeing Performance in China? An Analysis from a Three-Stage Network Perspective," Land, MDPI, vol. 12(8), pages 1-18, July.
    6. Hamid, Faiz & Agarwal, Yogesh K., 2024. "Train stop scheduling problem: An exact approach using valid inequalities and polar duality," European Journal of Operational Research, Elsevier, vol. 313(1), pages 207-224.
    7. Karolina Dudzic-Gyurkovich, 2023. "Study of Centrality Measures in the Network of Green Spaces in the City of Krakow," Sustainability, MDPI, vol. 15(18), pages 1-30, September.
    8. Eisuke Watanabe & Ryuichi Shibasaki, 2023. "Extraction of Bunkering Services from Automatic Identification System Data and Their International Comparisons," Sustainability, MDPI, vol. 15(24), pages 1-19, December.
    9. Masing, Berenike & Lindner, Niels & Borndörfer, Ralf, 2022. "The price of symmetric line plans in the Parametric City," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 419-443.
    10. Zheng, Zunxin & Qiu, Zhongjie & Li, Mengjia & Ding, Wenjie, 2024. "High-speed rail and stock return comovement in China," Research in International Business and Finance, Elsevier, vol. 67(PA).
    11. Canca, David & Barrena, Eva & De-Los-Santos, Alicia & Andrade-Pineda, José Luis, 2016. "Setting lines frequency and capacity in dense railway rapid transit networks with simultaneous passenger assignment," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 251-267.
    12. Goerigk, Marc & Schmidt, Marie, 2017. "Line planning with user-optimal route choice," European Journal of Operational Research, Elsevier, vol. 259(2), pages 424-436.
    13. Mathias Michaelis & Anita Schöbel, 2009. "Integrating line planning, timetabling, and vehicle scheduling: a customer-oriented heuristic," Public Transport, Springer, vol. 1(3), pages 211-232, August.
    14. Wenliang Zhou & Jing Kang & Jin Qin & Sha Li & Yu Huang, 2022. "Robust Optimization of High-Speed Railway Train Plan Based on Multiple Demand Scenarios," Mathematics, MDPI, vol. 10(8), pages 1-26, April.
    15. Jan-Willem Goossens & Stan van Hoesel & Leo Kroon, 2004. "A Branch-and-Cut Approach for Solving Railway Line-Planning Problems," Transportation Science, INFORMS, vol. 38(3), pages 379-393, August.
    16. Yan, Fei & Goverde, Rob M.P., 2019. "Combined line planning and train timetabling for strongly heterogeneous railway lines with direct connections," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 20-46.
    17. Zanyang Cui & Zhimei Wang & Junhua Chen & Xingchen Zhang & Chunxiao Zhao, 2023. "Integrated Planning for Depot Location and Line Planning Problems in the Intercity Railway Network with Passenger Demand Uncertainty," Sustainability, MDPI, vol. 15(20), pages 1-22, October.
    18. Thomas Lindner & Uwe Zimmermann, 2005. "Cost optimal periodic train scheduling," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 62(2), pages 281-295, November.
    19. Xu, Fei & Liu, Qian & Zheng, Xingdong & Cao, Luqi & Yang, Mian, 2022. "Research on the impact of China's high-speed rail opening on enterprise market power: Based on the perspective of market segmentation," Transport Policy, Elsevier, vol. 128(C), pages 121-137.
    20. van Lieshout, R.N. & Bouman, P.C. & Huisman, D., 2018. "Determining and Evaluating Alternative Line Plans in (Near) Out-of-Control Situations," Econometric Institute Research Papers EI2018-20, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    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:15:y:2023:i:8:p:6450-:d:1120340. 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.