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Research on parking sharing strategies considering user overtime parking

A parking sharing strategy is proposed to solve the problems of parking difficulty caused by the imbalance between parking spaces and parking demand. The vacant parking spaces of residential area can be efficiently utilized to meet the parking demands of those who are working at nearby or come for o...

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Detalles Bibliográficos
Autores principales: Huang, Xin, Long, Xueqin, Wang, Jianjun, He, Lan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286510/
https://www.ncbi.nlm.nih.gov/pubmed/32520933
http://dx.doi.org/10.1371/journal.pone.0233772
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author Huang, Xin
Long, Xueqin
Wang, Jianjun
He, Lan
author_facet Huang, Xin
Long, Xueqin
Wang, Jianjun
He, Lan
author_sort Huang, Xin
collection PubMed
description A parking sharing strategy is proposed to solve the problems of parking difficulty caused by the imbalance between parking spaces and parking demand. The vacant parking spaces of residential area can be efficiently utilized to meet the parking demands of those who are working at nearby or come for other activities based on the parking sharing strategy. The paper analyzes the distribution of vehicle arrival numbers and parking durations, then establishes a shared parking allocation model aiming to maximize the parking benefit considering the overtime-parking behavior of the parking users. Simulation methods are used to the analyze the relationship among the parking benefit, proportion of reserved parking, numbers of parking demand, acceptance rate of parking demand and utilization of shared parking spaces. Then, based on the principle of maximum parking benefit, we can determine the optimal proportion of reserved parking, number of shared parking spaces that should be purchased from the residents. Taking the utilization of shared parking spaces as an indicator, the validity of the static allocation principle is proved to be effective. Some allocation rules for parking demand are proposed to guarantees the maximum parking revenue and minimum impact on residents simultaneously.
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spelling pubmed-72865102020-06-17 Research on parking sharing strategies considering user overtime parking Huang, Xin Long, Xueqin Wang, Jianjun He, Lan PLoS One Research Article A parking sharing strategy is proposed to solve the problems of parking difficulty caused by the imbalance between parking spaces and parking demand. The vacant parking spaces of residential area can be efficiently utilized to meet the parking demands of those who are working at nearby or come for other activities based on the parking sharing strategy. The paper analyzes the distribution of vehicle arrival numbers and parking durations, then establishes a shared parking allocation model aiming to maximize the parking benefit considering the overtime-parking behavior of the parking users. Simulation methods are used to the analyze the relationship among the parking benefit, proportion of reserved parking, numbers of parking demand, acceptance rate of parking demand and utilization of shared parking spaces. Then, based on the principle of maximum parking benefit, we can determine the optimal proportion of reserved parking, number of shared parking spaces that should be purchased from the residents. Taking the utilization of shared parking spaces as an indicator, the validity of the static allocation principle is proved to be effective. Some allocation rules for parking demand are proposed to guarantees the maximum parking revenue and minimum impact on residents simultaneously. Public Library of Science 2020-06-10 /pmc/articles/PMC7286510/ /pubmed/32520933 http://dx.doi.org/10.1371/journal.pone.0233772 Text en © 2020 Huang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Huang, Xin
Long, Xueqin
Wang, Jianjun
He, Lan
Research on parking sharing strategies considering user overtime parking
title Research on parking sharing strategies considering user overtime parking
title_full Research on parking sharing strategies considering user overtime parking
title_fullStr Research on parking sharing strategies considering user overtime parking
title_full_unstemmed Research on parking sharing strategies considering user overtime parking
title_short Research on parking sharing strategies considering user overtime parking
title_sort research on parking sharing strategies considering user overtime parking
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286510/
https://www.ncbi.nlm.nih.gov/pubmed/32520933
http://dx.doi.org/10.1371/journal.pone.0233772
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