There is much speculation about the prospective impacts of automated vehicles (AVs) on parking supply and behaviour, however the literature contains little quantitative evidence. In this study, we develop a mixed‐integer non‐linear optimisation (MINLP) model of revenue maximisation to design parking facility layouts for privately‐owned automated cars that include separate vehicle‐storage and drop‐off/pick‐up zones (DOPU, or alternatively termed “PUDO zones”). The control variable is the allocation of space between these two competing uses. The model balances between revenue derived from parking (including revenue during activity time) and costs associated with the range of AVs’ parking and loading/unloading activities. Via numerical analysis of an archetypal shopping centre's parking facility, the authors demonstrate that the model responds intuitively to the stimulus of systematically varying the input parameters. This study is intended to provide an incremental advance to support researchers and practitioners tasked with quantifying the impacts of AVs on the parking system.
Optimal storage and loading zones within surface parking facilities for privately owned automated vehicles
IET Intelligent Transport Systems ; 13 , 12 ; 1754-1760
2019-12-01
7 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
design engineering , nonlinear programming , optimal storage zones , mobile robots , surface parking facilities , privately owned automated vehicles , separate vehicle‐storage , revenue maximisation , AV parking , integer programming , road traffic control , parking supply , activity time , control variable , archetypal shopping centre , mixed‐integer nonlinear optimisation , optimal loading zones , parking facility layout design
IET | 2019
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