Capacity impacts and optimal geometry of automated cars' surface parking facilities
File(s)
Author(s)
Kong, You
Le Vine, Scott
Liu, Xiaobo
Type
Journal Article
Abstract
The impact of Automated Vehicles (AVs) on urban geography has been widely speculated, though there is little quantitative evidence in the literature to establish the magnitude of such effects. To quantify the impact of the greater precision of automated driving on the spatial efficiency of off-street parking facilities, we develop a mixed integer nonlinear model (solved via a branch-and-cut approach) and present comparisons against industry-standard requirements for human-driving operation. We demonstrate that gains on the order of 40–50% in spatial efficiency (parking spaces per unit area) are in principle achievable while ensuring that each parked vehicle is independently accessible. We further show that the large majority of these efficiency gains can be obtained under current automotive engineering practice in which only the front two wheels pivot. There is a need for standardized methods that take the parking supply of a city as an input and calculate both the aggregate (citywide) efficiency impacts of automated driving and the spatial distribution of the effects. This study is intended as an initial step towards this objective.
Date Issued
2018-04-26
Date Acceptance
2018-03-11
Citation
Journal of Advanced Transportation, 2018, 2018
ISSN
0197-6729
Publisher
Hindawi Publishing Corporation
Journal / Book Title
Journal of Advanced Transportation
Volume
2018
Copyright Statement
© 2018 You Kong et al. This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000431682300001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Technology
Engineering, Civil
Transportation Science & Technology
Engineering
Transportation
VEHICLES
BEHAVIOR
Publication Status
Published
Article Number
ARTN 6908717
Date Publish Online
2018-04-26