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On the allocation of city space to multiple transport modes

Author

Listed:
  • Eric J. Gonzales
  • Nikolas Geroliminis
  • Michael J. Cassidy
  • Carlos F. Daganzo

Abstract

This paper analyzes urban multimodal transportation systems in an aggregated way. To describe the aggregate behavior of traffic in cities, use is made of an idea that is now receiving some attention: the macroscopic fundamental diagram (MFD). We demonstrate through simulation how the MFD can be used to monitor and control a real network, in this case a portion of San Francisco, using readily available input data. We then show how different modes interact on the same network and discuss how these interactions might be incorporated into an MFD for multimodal networks. The work unveils two main results: first, it confirms recent results showing that restricting access to a city's congested areas can improve mobility for all travelers, including those who endure the restrictions; and second, that dedicating street space to collective transport modes can improve accessibility for all modes, even those from which space is taken away.

Suggested Citation

  • Eric J. Gonzales & Nikolas Geroliminis & Michael J. Cassidy & Carlos F. Daganzo, 2010. "On the allocation of city space to multiple transport modes," Transportation Planning and Technology, Taylor & Francis Journals, vol. 33(8), pages 643-656, September.
    • Handle: RePEc:taf:transp:v:33:y:2010:i:8:p:643-656
    DOI: 10.1080/03081060.2010.527171
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    Citations

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    Cited by:

    1. Anderson, Paul & Geroliminis, Nikolas, 2020. "Dynamic lane restrictions on congested arterials," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 224-243.
    2. Johari, Mansour & Keyvan-Ekbatani, Mehdi, 2024. "Macroscopic modeling of mixed bi-modal urban networks: A hybrid model of accumulation- and trip-based principles," Transportation Research Part B: Methodological, Elsevier, vol. 182(C).
    3. Zheng, Nan & Geroliminis, Nikolas, 2013. "On the distribution of urban road space for multimodal congested networks," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 326-341.
    4. Loder, Allister & Bliemer, Michiel C.J. & Axhausen, Kay W., 2022. "Optimal pricing and investment in a multi-modal city — Introducing a macroscopic network design problem based on the MFD," Transportation Research Part A: Policy and Practice, Elsevier, vol. 156(C), pages 113-132.
    5. Amirgholy, Mahyar & Shahabi, Mehrdad & Gao, H. Oliver, 2017. "Optimal design of sustainable transit systems in congested urban networks: A macroscopic approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 261-285.
    6. Lehe, Lewis J. & Pandey, Ayush, 2024. "A bathtub model of transit congestion," Transportation Research Part B: Methodological, Elsevier, vol. 181(C).
    7. José Gerardo Carrillo-González & Guillermo López-Maldonado & Juan Lopez-Sauceda & Francisco Perez-Martinez, 2023. "Method for Selecting the Vehicles That Can Enter a Street Network to Maintain the Speed on Links above a Speed Threshold," Sustainability, MDPI, vol. 15(13), pages 1-29, June.

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