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Optimizing Bus Line Based on Metro-Bus Integration

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  • Junjun Wei

    (Hunan Provincial Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems, Changsha University of Science & Technology, Changsha 410004, China
    School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410004, China)

  • Kejun Long

    (Hunan Provincial Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems, Changsha University of Science & Technology, Changsha 410004, China
    School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410004, China)

  • Jian Gu

    (Hunan Provincial Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems, Changsha University of Science & Technology, Changsha 410004, China)

  • Qingling Ju

    (School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410004, China)

  • Piao Zhu

    (Shenzhen comprehensive traffic design and Research Institute Co., Ltd., Shenzhen 518000, China)

Abstract

Metros are usually built and added on the basis of a completed bus network in Chinese cities. After the metro construction, it is faced with the problem of how to adjust and optimize the original bus lines based on the new metro system. This research mainly proposes a bus line optimization method based on bus and metro integration. In the consideration of the geographical space, the cooperation and competition relationship between bus and metro lines is qualitatively introduced according to the geographical location and service range of metro (800 m radius) and bus (500 m radius) stations. The competition and cooperation indexes are applied to define the co-opetition relationship between bus and metro lines. The bus line optimization model is constructed based on the co-opetition coefficient and Changsha Metro Line Number 2 is chosen as a case study to verify the optimization model. The results show that the positive competition, efficient cooperation, and travel efficiency between metro and bus has been significantly enhanced after optimization. Moreover, this paper provides a reasonable reference for public transport network planning and resource allocation.

Suggested Citation

  • Junjun Wei & Kejun Long & Jian Gu & Qingling Ju & Piao Zhu, 2020. "Optimizing Bus Line Based on Metro-Bus Integration," Sustainability, MDPI, vol. 12(4), pages 1-14, February.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:4:p:1493-:d:321567
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    References listed on IDEAS

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    1. Schmöcker, Jan-Dirk & Bell, Michael G.H. & Kurauchi, Fumitaka, 2008. "A quasi-dynamic capacity constrained frequency-based transit assignment model," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 925-945, December.
    2. Kuby, Michael & Barranda, Anthony & Upchurch, Christopher, 2004. "Factors influencing light-rail station boardings in the United States," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(3), pages 223-247, March.
    3. Kalouptsidis, N. & Psaraki, V., 2010. "Approximations of choice probabilities in mixed logit models," European Journal of Operational Research, Elsevier, vol. 200(2), pages 529-535, January.
    4. Ivanova, Olga, 2005. "A note on the consistent aggregation of nested logit demand functions," Transportation Research Part B: Methodological, Elsevier, vol. 39(10), pages 890-895, December.
    5. Luis A. Guzman & Daniel Oviedo & Rafael Cardona, 2018. "Accessibility Changes: Analysis of the Integrated Public Transport System of Bogotá," Sustainability, MDPI, vol. 10(11), pages 1-15, October.
    6. Zixia Xiang & Yanhong Yin & Yuanwen He, 2018. "A Microeconomic Methodology to Evaluate Energy Efficiency by Consumption Behaviors and Strategies to Improve Energy Efficiency," Sustainability, MDPI, vol. 10(11), pages 1-11, November.
    7. Jin, Jian Gang & Tang, Loon Ching & Sun, Lijun & Lee, Der-Horng, 2014. "Enhancing metro network resilience via localized integration with bus services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 63(C), pages 17-30.
    8. Ben-Akiva, Moshe & Morikawa, Takayuki, 2002. "Comparing ridership attraction of rail and bus," Transport Policy, Elsevier, vol. 9(2), pages 107-116, April.
    9. Zhi-Chun Li & William H.K. Lam & S.C. Wong, 2009. "Optimization of a Bus and Rail Transit System with Feeder Bus Services under Different Market Regimes," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 495-516, Springer.
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    Cited by:

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