IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/fyhbc.html
   My bibliography  Save this paper

Converting One-Way Streets to Two-Way Streets to Improve Transportation Network Efficiency and Reduce Vehicle Distance Traveled

Author

Listed:
  • Boeing, Geoff

    (Northeastern University)

  • Riggs, William

    (University of San Francisco)

Abstract

Planning scholars have identified economic, safety, and social benefits of converting one-way streets to two-way. Less is known about how conversions could impact vehicular distances traveled—of growing relevance in an era of fleet automation, electrification, and ride-hailing. We simulate such a conversion in San Francisco, California. We find that its current street network’s average intra-city trip is about 1.7% longer than it would be with all two-way streets, corresponding to 27 million kilometers of annual surplus travel. As transportation technologies evolve, planners must consider different facets of network efficiency to align local policy and street design with sustainability and other societal goals.

Suggested Citation

  • Boeing, Geoff & Riggs, William, 2022. "Converting One-Way Streets to Two-Way Streets to Improve Transportation Network Efficiency and Reduce Vehicle Distance Traveled," SocArXiv fyhbc, Center for Open Science.
    • Handle: RePEc:osf:socarx:fyhbc
    DOI: 10.31219/osf.io/fyhbc
    as

    Download full text from publisher

    File URL: https://osf.io/download/6263268b64e02a0101b46358/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/fyhbc?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Mark R. Stevens, 2017. "Does Compact Development Make People Drive Less?," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(1), pages 7-18, January.
    2. Millard-Ball, Adam, 2019. "The autonomous vehicle parking problem," Transport Policy, Elsevier, vol. 75(C), pages 99-108.
    3. Susan Handy, 2017. "Thoughts on the Meaning of Mark Stevens’s Meta-Analysis," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(1), pages 26-28, January.
    4. Clewlow, Regina R. & Mishra, Gouri S., 2017. "Disruptive Transportation: The Adoption, Utilization, and Impacts of Ride-Hailing in the United States," Institute of Transportation Studies, Working Paper Series qt82w2z91j, Institute of Transportation Studies, UC Davis.
    5. William Riggs & Bruce Appleyard, 2018. "The economic impact of one to two-way street conversions: advancing a context-sensitive framework," Journal of Urbanism: International Research on Placemaking and Urban Sustainability, Taylor & Francis Journals, vol. 11(2), pages 129-148, April.
    6. Donald Appleyard, 1980. "Livable Streets: Protected Neighborhoods?," The ANNALS of the American Academy of Political and Social Science, , vol. 451(1), pages 106-117, September.
    7. E. Bavarez & G. F. Newell, 1967. "Traffic Signal Synchronization on a One-Way Street," Transportation Science, INFORMS, vol. 1(2), pages 55-73, May.
    8. Mark R. Stevens, 2017. "Response to Commentaries on “Does Compact Development Make People Drive Less?”," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(2), pages 151-158, April.
    9. Gayah, Vikash V., 2012. "Two-Way Street Networks: More Efficient than Previously Thought?," University of California Transportation Center, Working Papers qt6sx0q4kg, University of California Transportation Center.
    10. Ewing, R. & Schieber, R.A. & Zegeer, C.V., 2003. "Urban Sprawl as a Risk Factor in Motor Vehicle Occupant and Pedestrian Fatalities," American Journal of Public Health, American Public Health Association, vol. 93(9), pages 1541-1545.
    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. Ding, Chuan & Cao, Xinyu (Jason) & Næss, Petter, 2018. "Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 107-117.
    2. Guan, Xiaodong & Wang, Donggen, 2019. "Influences of the built environment on travel: A household-based perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 710-724.
    3. Jixiang Liu & Longzhu Xiao, 2024. "Socioeconomic differences in effect size: predicting commuting mode choice of migrants and locals using a light gradient boosting approach," Transportation, Springer, vol. 51(1), pages 1-24, February.
    4. Næss, Petter & Peters, Sebastian & Stefansdottir, Harpa & Strand, Arvid, 2018. "Causality, not just correlation: Residential location, transport rationales and travel behavior across metropolitan contexts," Journal of Transport Geography, Elsevier, vol. 69(C), pages 181-195.
    5. Liu, Jixiang & Wang, Bo & Xiao, Longzhu, 2021. "Non-linear associations between built environment and active travel for working and shopping: An extreme gradient boosting approach," Journal of Transport Geography, Elsevier, vol. 92(C).
    6. Erik Elldér & Katarina Haugen & Bertil Vilhelmson, 2022. "When local access matters: A detailed analysis of place, neighbourhood amenities and travel choice," Urban Studies, Urban Studies Journal Limited, vol. 59(1), pages 120-139, January.
    7. Ding, Chuan & Cao, Xinyu & Wang, Yunpeng, 2018. "Synergistic effects of the built environment and commuting programs on commute mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 104-118.
    8. Choi, Yunkyung & Guhathakurta, Subhrajit & Pande, Anurag, 2022. "An empirical Bayes approach to quantifying the impact of transportation network companies (TNCs) operations on travel demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 161(C), pages 269-283.
    9. Chetan Doddamani & M. Manoj, 2023. "Analysis of the influences of built environment measures on household car and motorcycle ownership decisions in Hubli-Dharwad cities," Transportation, Springer, vol. 50(1), pages 205-243, February.
    10. Carozzi, Felipe & Roth, Sefi, 2023. "Dirty density: Air quality and the density of American cities," Journal of Environmental Economics and Management, Elsevier, vol. 118(C).
    11. Mouratidis, Kostas & Ettema, Dick & Næss, Petter, 2019. "Urban form, travel behavior, and travel satisfaction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 306-320.
    12. Li, Xiaomeng & Neal, Zachary P., 2022. "Are larger cities more central in urban networks: A meta-analysis," OSF Preprints y3s69, Center for Open Science.
    13. Faizeh Hatami & Jean-Claude Thill, 2022. "Spatiotemporal Evaluation of the Built Environment’s Impact on Commuting Duration," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    14. Bindong Sun & Rui Guo & Chun Yin, 2023. "Inequity on suburban campuses: University students disadvantaged in self‐improvement travel," Growth and Change, Wiley Blackwell, vol. 54(2), pages 404-420, June.
    15. Chun Yin & Bindong Sun, 2020. "Does Compact Built Environment Help to Reduce Obesity? Influence of Population Density on Waist–Hip Ratio in Chinese Cities," IJERPH, MDPI, vol. 17(21), pages 1-16, October.
    16. Gao, Jiong & Ma, Shoufeng & Zou, Hongyang & Du, Huibin, 2023. "How does population agglomeration influence the adoption of new energy vehicles? Evidence from 290 cities in China," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    17. Nazari, Fatemeh & Mohammadian, Abolfazl (Kouros), 2023. "Modeling vehicle-miles of travel accounting for latent heterogeneity," Transport Policy, Elsevier, vol. 133(C), pages 45-53.
    18. Schmid, Basil & Becker, Felix & Axhausen, Kay W. & Widmer, Paul & Stein, Petra, 2023. "A simultaneous model of residential location, mobility tool ownership and mode choice using latent variables," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    19. Zhao, Chuyun & Tang, Jinjun & Zeng, Yu & Li, Zhitao & Gao, Fan, 2023. "Understanding the spatio-temporally heterogeneous effects of built environment on urban travel emissions," Journal of Transport Geography, Elsevier, vol. 112(C).
    20. Charles Raux & Ayana Lamatkhanova & Lény Grassot, 2021. "Does the built environment shape commuting? The case of Lyon (France)," Post-Print halshs-03010833, HAL.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:osf:socarx:fyhbc. 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: OSF (email available below). General contact details of provider: https://arabixiv.org .

    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.