Exploring the impact of shared autonomous vehicles on urban parking demand: An agent-based simulation approach
Exploring the impact of shared autonomous vehicles on urban parking demand: An agent-based simulation approach
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DOI：
10.1016/j.scs.2015.07.006
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发表时间：
2015-12-01
影响因子：
11.7
通讯作者：
Zhang, Ge
中科院分区：
文献类型：
--
作者：
Zhang, Wenwen;Guhathakurta, Subhrajit;Zhang, Ge
尽管最近对共享自动驾驶汽车 (SAV) 的研究探讨了该技术的经济成本和环境影响，但人们对 SAV 如何改变城市形态（尤其是通过减少停车需求）知之甚少。本研究借助基于代理的仿真模型估计了不同系统运行场景下 SAV 系统对城市停车需求的潜在影响。模拟结果表明，我们或许能够在 2% 的低市场渗透率下，为采用该系统的客户消除高达 90% 的停车需求。研究结果还表明，不同的SAV运营策略和客户偏好可能会导致城市停车需求的不同空间分布。 (C) 2015 Elsevier Ltd. 保留所有权利。
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.