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

Authored by Wenwen Zhang, Subhrajit Guhathakurta, Jinqi Fang, Ge Zhang

Date Published: 2015

DOI: 10.1016/j.scs.2015.07.006

Sponsors: No sponsors listed

Platforms: MATLAB

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

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. (C) 2015 Elsevier Ltd. All rights reserved.

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