Study on Parking Adaptability in Urban Complexes on Top of Subways Based on Shared Parking Spaces

Urban complexes on top of subways as a function of intensive building groups, including residential, office, business, and other types nature of land use where parking time differences are obvious, can implement shared parking spaces, thereby reducing the index of parking allotment. Currently, the parking space allocation index for complexes is only a simple superposition of different land uses, resulting in an over-allocation of parking allotments, leading to a waste of land resources and a low utilization rate of parking allotments. Considering the factor of shared parking spaces, this paper conducted an in-depth analysis of the parking adaptability of urban complexes on top of subways and selected five urban complexes on top of subway stations in Wuhan to conduct a parking survey to analyze the parking demand characteristics. This study also investigated the parking behavior of parkers and analyzed the characteristics of parking behavior in urban complexes on top of subways as well as the current parking demand prediction methods and models, establishing a parking demand prediction model based on shared parking spaces and conducting an adaptability analysis. Finally, using five urban complexes in Wuhan as examples, the number of parking spaces demanded by urban complexes on top of subways in 2025 was predicted, and Wuhan Golden Harvest Fashion Plaza was used as an example to verify the feasibility and implementation ability of the theoretical and applied research in this paper.

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Publication Details

Journal
Sustainability
Published
2024-08-26
DOI
https://doi.org/10.3390/su16177334
Citations
1
Primary Topic
Smart Parking Systems Research
Type
article
Field-Weighted Citation Impact
0.27
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article

Study on Parking Adaptability in Urban Complexes on Top of Subways Based on Shared Parking Spaces

X. Zhang, Yuqin Feng, Wang Fu, Xinyu Chen
1 citations
Sustainability
Smart Parking Systems Research
0.27
article

Study on Parking Adaptability in Urban Complexes on Top of Subways Based on Shared Parking Spaces

X. Zhang, Yuqin Feng, Wang Fu, Xinyu Chen
article en
1 citations

Abstract

Urban complexes on top of subways as a function of intensive building groups, including residential, office, business, and other types nature of land use where parking time differences are obvious, can implement shared parking spaces, thereby reducing the index of parking allotment. Currently, the parking space allocation index for complexes is only a simple superposition of different land uses, resulting in an over-allocation of parking allotments, leading to a waste of land resources and a low utilization rate of parking allotments. Considering the factor of shared parking spaces, this paper conducted an in-depth analysis of the parking adaptability of urban complexes on top of subways and selected five urban complexes on top of subway stations in Wuhan to conduct a parking survey to analyze the parking demand characteristics. This study also investigated the parking behavior of parkers and analyzed the characteristics of parking behavior in urban complexes on top of subways as well as the current parking demand prediction methods and models, establishing a parking demand prediction model based on shared parking spaces and conducting an adaptability analysis. Finally, using five urban complexes in Wuhan as examples, the number of parking spaces demanded by urban complexes on top of subways in 2025 was predicted, and Wuhan Golden Harvest Fashion Plaza was used as an example to verify the feasibility and implementation ability of the theoretical and applied research in this paper.

SustainabilityVol. 16(17)
Hainan Tropical Ocean University (CN), Wuhan Institute of Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 44%
Smart Parking Systems Research
0.27
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Study on Parking Adaptability in Urban Complexes on Top of Subways Based on Shared Parking Spaces — X. Zhang, Yuqin Feng, et al. · Sustainability (2024) | TGRS Research Map | TGRS