Fighting for Curb Space: Parking, Ride-Hailing, Urban Freight Deliveries, and Other Users [supporting dataset]

There is a need to optimally allocate curb space - one of the scarcest resources in urban areas - to the different and growing needs of passenger and freight transport. Although there are plenty of linear miles of curbside space in every city, the growing adoption of ride-hailing services and the rise of e-commerce with its residential deliveries, and the increased number of micro-mobility services, have increased pressure on the already saturated transportation system. Traditional curbside planning strategies have relied on land-use based demand estimates to allocate access priority to the curb (e.g., pedestrian and transit for residential areas, commercial vehicles for commercial and industrial zones). In some locales, new guidelines provide ideas on flexible curbside management, but lack the systems to gather and analyze the data, and optimally and dynamically allocate the space to the different users and needs. This study conducted a comprehensive literature review on several topics related to curb space management, discussing various users (e.g., pedestrians, bicycles, transit, taxis, and commercial freight vehicles), summarizing different experiences, and focusing the discussion on Complete Street strategies. Moreover, the authors reviewed the academic literature on curbside and parking data collection, and simulation and optimization techniques. Considering a case study around the downtown area in San Francisco, the authors evaluated the performance of the system with respect to a number of parking behavior scenarios. In doing so, the authors developed a parking simulation in SUMO following a set of parking behaviors (e.g., parking search, parking with off-street parking information availability, double-parking). These scenarios were tested in three different (land use-based) sub-study areas representing residential, commercial and mixed-use. Data assembled by the Project:(1) Curb Demand. The sets of curb demand data are provided in Comma-delimited (csv) format. (2) MATsim Files. The files are compressed and offered as a single compressed ZIP file. (3) SUMO Files. The files are compressed and offered as a single compressed ZIP file.

• Record URL:
  https://doi.org/10.7922/G22N50JJ
• Dataset URL:
  https://doi.org/10.25338/B81W61
• Record URL:
  https://dot.ca.gov/-/media/dot-media/programs/research-innovation-system-information/documents/final-reports/ca21-3397-final-report-a11y.pdf
• 
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/56903
• Dataset URL:
  https://rosap.ntl.bts.gov/view/dot/57015
• Supplemental Notes:
  • The dataset supports report: Fighting for Curb Space: Parking, Ride-Hailing, Urban Freight Deliveries, and Other Users, available at the URL above. This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  University of California, Davis

  Institute of Transportation Studies
  Davis, CA  United States  95616

  California Department of Transportation

  Division of Research, Innovation and System Information
  1727 30th Street, MS 83
  Sacramento, CA  United States  95816

  National Center for Sustainable Transportation

  University of California, Davis
  Davis, CA  United States 

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Jaller, Miguel
  • 0000-0003-4053-750X
  • Rodie, Caroline
  • 0000-0002-9107-5547
  • Zhang, Michael
  • 0000-0002-4647-3888
  • Lin, Huachao
  • 0000-0002-7506-4434
  • Lewis, Kathryn
  • 0000-0002-5114-2645
• Publication Date: 2021-6

Language

• English

Media Info

• Media Type: Dataset

Subject/Index Terms

• TRT Terms: Curb side parking; Data; Delivery service; Parking demand; Ridesourcing; Simulation; Urban areas
• Identifier Terms: MATSim (Computer program); SUMO (Traffic simulation model)
• Geographic Terms: San Francisco (California)
• Subject Areas: Data and Information Technology; Freight Transportation; Highways; Operations and Traffic Management; Pedestrians and Bicyclists;

Filing Info

• Accession Number: 01776283
• Record Type: Publication
• Contract Numbers: Caltrans 65A0686 Task Order 007; USDOT Grant 69A35
• Files: UTC, NTL, TRIS, ATRI, USDOT, STATEDOT
• Created Date: Jul 8 2021 4:23PM