IDEAS home Printed from https://ideas.repec.org/p/cdl/itsdav/qt63m6k29n.html
   My bibliography  Save this paper

The Impacts of Automated Vehicles on Center City Parking Demand

Author

Listed:
  • Chai, Huajun
  • Rodier, Caroline
  • Song, Jeffery
  • Zhang, Michael
  • Jaller, Miguel

Abstract

The potential for automated vehicles (AVs) to reduce parking in city centers has generated much excitement among urban planners. AVs could drop-off (DO) and pick-up (PU) passengers in areas where parking costs are high: personal AVs could return home or park in less expensive locations, and shared AVs could serve other passengers. Reduced on-street and off-street parking present numerous opportunities for redevelopment that could improve the livability of cities, for example, more street and sidewalk space for pedestrian and bicycle travel. However, reduced demand for parking would be accompanied by increased demand for curbside DO/PU space with related movements to enter and exit the flow of traffic. This change could be particularly challenging for traffic flows in downtown urban areas during peak hours, where high volumes of DOs and PUs are likely to occur. Only limited research examines the travel effects of a shift from parking to DO/PU travel and the impact of changes in parking supply. This study uses a microscopic road traffic model with local travel activity data to simulate personal AV parking scenarios in San Francisco's downtown central business district. These scenarios vary (1) the demand for DO and PU travel versus parking, (2) the supply of on-street and off-street parking, and (3) the total demand for parking and DO/PU travel due to an increase in the cost of travel to the central business district. View the NCST Project Webpage

Suggested Citation

  • Chai, Huajun & Rodier, Caroline & Song, Jeffery & Zhang, Michael & Jaller, Miguel, 2020. "The Impacts of Automated Vehicles on Center City Parking Demand," Institute of Transportation Studies, Working Paper Series qt63m6k29n, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt63m6k29n
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/63m6k29n.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rodier, Caroline & Jaller, Miguel & Pourrahmani, Elham & Bischoff, Joschka & Freedman, Joel & Pahwa, Anmol, 2018. "Automated Vehicle Scenarios: Simulation of System-Level Travel Effects Using Agent-Based Demand and Supply Models in the San Francisco Bay Area," Institute of Transportation Studies, Working Paper Series qt4dk3n531, Institute of Transportation Studies, UC Davis.
    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. Chai, Huajun & Rodier, Caroline J. & Song, Jeffery W. & Zhang, Michael H. & Jaller, Miguel, 2023. "The impacts of automated vehicles on Center city parking," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).

    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:cdl:itsdav:qt63m6k29n. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucdus.html .

    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.