Estimating Changes in Parking Capacity and Urban Form From Vehicle Automation

This project developed a method to characterize the impact of privately-owned autonomous electric vehicles on electric vehicle charger placement, distribution, utilization, and power demand. Using Seattle, WA as a case study, a least total cost optimization for charging station owner and driver costs is conducted for vehicle automation levels 0-3, 4, and 5. Moving from levels 0-3 to level 4 and level 5 automation reduces the peak electrical load for EV charging by approximately 31% and 68%, respectively. Moving from levels 0-3 to level 4 automation decreased the optimal number of chargers by 65%, lowered total cost by 46%. Moving from levels 0-3 automation to level 5 automation decreased the optimal number of chargers by 84% and total costs by 69%. Additional vehicle miles traveled and operating costs incurred by drivers for drop off and pick up were estimated with level 5 automation. The results suggest that highly automated vehicle technology used in privately-owned electric vehicles could reduce the cost of deployment for recharging infrastructure and reduce peak electrical demand associated with recharging. The results were published as a Technical Report (Mersky and Samaras, 2020, included in this document), and are under review at an academic journal. Several government, professional, and academic presentations were also completed.

  • Record URL:
  • Supplemental Notes:
    • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
  • Corporate Authors:


    Carnegie Mellon University
    Pittsburgh, PA  United States 

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Authors:
  • Publication Date: 2020-12


  • English

Media Info

  • Media Type: Digital/other
  • Edition: Final Research Report
  • Features: Figures; References; Tables;
  • Pagination: 34p

Subject/Index Terms

Filing Info

  • Accession Number: 01762055
  • Record Type: Publication
  • Contract Numbers: 69A3551747111
  • Created Date: Dec 21 2020 3:05PM