Exploring the impact of shared autonomous vehicles on urban parking demand: An agent-based simulation approach

Wenwen Zhang, Subhrajit Guhathakurta, Jinqi Fang, Ge Zhang

Research output: Contribution to journalArticlepeer-review

295 Scopus citations

Abstract

Although recent studies of Shared Autonomous Vehicles (SAVs) have explored the economic costs and environmental impacts of this technology, little is known about how SAVs can change urban forms, especially by reducing the demand for parking. This study estimates the potential impact of SAV system on urban parking demand under different system operation scenarios with the help of an agent-based simulation model. The simulation results indicate that we may be able to eliminate up to 90% of parking demand for clients who adopt the system, at a low market penetration rate of 2%. The results also suggest that different SAV operation strategies and client's preferences may lead to different spatial distribution of urban parking demand.

Original languageEnglish (US)
Article number302
Pages (from-to)34-45
Number of pages12
JournalSustainable Cities and Society
Volume19
DOIs
StatePublished - Dec 2015
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Transportation

Keywords

  • Agent-based model
  • Parking
  • Shared autonomous vehicle

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