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Towards Sustainable Parking: Analyzing the Characteristics of Periodic Off-Street Parking Lots and Their Application in Shared Parking

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  • Yifei Cai

    (School of Civil and Transportation Engineering, Ningbo University of Technology, Ningbo 315211, China
    Zhejiang Engineering Research Center of Digital Road Construction Technology, Ningbo 315211, China)

  • Xiao Pan

    (Ningbo Municipal Public Investment Co., Ltd., Ningbo 315000, China)

  • Lei Zhang

    (Ningbo Municipal Public Investment Co., Ltd., Ningbo 315000, China)

  • Feifei Xu

    (School of Civil and Transportation Engineering, Ningbo University of Technology, Ningbo 315211, China
    Zhejiang Engineering Research Center of Digital Road Construction Technology, Ningbo 315211, China)

  • Shuichao Zhang

    (School of Civil and Transportation Engineering, Ningbo University of Technology, Ningbo 315211, China
    Zhejiang Engineering Research Center of Digital Road Construction Technology, Ningbo 315211, China)

Abstract

The pollution and congestion caused by the shortage of parking spaces are threatening the sustainable development of cities. Smart parking platforms are one of the major tools to solve the problem by providing the efficient usage of parking resources. However, current platforms can only realize limited functions, and shared parking is far from being implemented on a large scale. Since off-street parking provides the majority of potential shared parking spaces, this paper takes periodic off-street parking lots as the starting point for opening the shared parking market. Based on data from the Ningbo Yongcheng parking platform, power spectral density (PSD) and the autocorrelation function (ACF) are used to identify periodic parking lots. A Density-Based Spatial Clustering of Applications with Noise (DBSCAN)-based method is applied to clustering the occupancy time series. Land use, user type, parking duration, and parking patterns are then analyzed to study shared parking supply characteristics. The results show that (1) 31.3% of off-street parking lots are periodic parking lots, and 90.3% of them have regular users exceeding 50%. (2) Periodic parking lots are classified into four types. Most parking lots show convex flat peak, double peak, or triple peak characteristics. (3) The shared parking spaces demonstrate spatial and temporal imbalances. But in a small area, even considering the concentration of land use and the peak period, there are still enough spaces available. The above research is of significance for the large-scale implementation of shared parking, which can promote the sustainable development of a city.

Suggested Citation

  • Yifei Cai & Xiao Pan & Lei Zhang & Feifei Xu & Shuichao Zhang, 2025. "Towards Sustainable Parking: Analyzing the Characteristics of Periodic Off-Street Parking Lots and Their Application in Shared Parking," Sustainability, MDPI, vol. 17(3), pages 1-23, January.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:3:p:833-:d:1572644
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    References listed on IDEAS

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    1. Shoup, Donald C., 2006. "Cruising for Parking," University of California Transportation Center, Working Papers qt55s7079f, University of California Transportation Center.
    2. Zheng, Nan & Geroliminis, Nikolas, 2016. "Modeling and optimization of multimodal urban networks with limited parking and dynamic pricing," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 36-58.
    3. Kuo, Pei-Fen & Hsu, Wei-Ting & Putra, I Gede Brawiswa & Sulistyah, Umroh Dian, 2024. "The proposed model for analyzing off-street parking Dynamics: A case study of Taipei City," Transportation Research Part A: Policy and Practice, Elsevier, vol. 180(C).
    4. Yan, Xiang & Levine, Jonathan & Marans, Robert, 2019. "The effectiveness of parking policies to reduce parking demand pressure and car use," Transport Policy, Elsevier, vol. 73(C), pages 41-50.
    5. Xie, Minghui & Zhang, Xinying & Wu, Zhouhao & Wei, Sen & Gao, Yanan & Wang, Yuanqing, 2023. "A shared parking optimization framework based on dynamic resource allocation and path planning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 616(C).
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    1. Paweł Dobrzański & Magdalena Dobrzańska, 2025. "Sustainable Consumption in Urban Transport: A Case Study of a Selected European Union City," Sustainability, MDPI, vol. 17(13), pages 1-21, July.

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