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Fast Way to Predict Parking Lots Availability: For Shared Parking Lots Based on Dynamic Parking Fee System

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  • Sheng-Ming Wang

    (Department of Interaction Design, National Taipei University of Technology, Taipei 10608, Taiwan)

  • Wei-Min Cheng

    (Doctoral Program in Design, College of Design, National Taipei University of Technology, Taipei 10608, Taiwan)

Abstract

This study mainly focuses on the estimation calculation of urban parking space. Urban parking has always been a problem that plagues governments worldwide. Due to limited parking space, if the parking space is not controlled correctly, with the city’s development, the city will eventually face the result that there is nowhere to park. In order to effectively manage the urban parking problem, using the dynamic parking fee pricing mechanism combined with the concept of shared parking is an excellent way to alleviate the parking problem, but how to quickly estimate the total number of available parking spaces in the area is a big problem. This study provides a fast parking space estimation method and verifies the feasibility of this estimation method through actual data from various types of fields. This study also comprehensively discusses the changing characteristics of parking space data in multiple areas and possible data anomalies and studies and explains the causes of data anomalies. The study also concludes with a description of potential applications of the predictive model in conjunction with subsequent dynamic parking pricing mechanisms and self-driving systems.

Suggested Citation

  • Sheng-Ming Wang & Wei-Min Cheng, 2023. "Fast Way to Predict Parking Lots Availability: For Shared Parking Lots Based on Dynamic Parking Fee System," Future Internet, MDPI, vol. 15(3), pages 1-22, February.
    • Handle: RePEc:gam:jftint:v:15:y:2023:i:3:p:89-:d:1076756
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    References listed on IDEAS

    as
    1. Zhenyu Mei & Chi Feng & Liang Kong & Lihui Zhang & Jun Chen, 2020. "Assessment of Different Parking Pricing Strategies: A Simulation-based Analysis," Sustainability, MDPI, vol. 12(5), pages 1-13, March.
    2. Jin Xie & Xiaofei Ye & Zhongzhen Yang & Xingchen Yan & Lili Lu & Zhen Yang & Tao Wang, 2019. "Impact of Risk and Benefit on the Suppliers’ and Managers’ Intention of Shared Parking in Residential Areas," Sustainability, MDPI, vol. 12(1), pages 1-17, December.
    3. Ange Wang & Hongzhi Guan & Zhengtao Qin & Junze Zhu & Abdul Qadeer Khan, 2021. "Study on the Intention of Private Parking Space Owners of Different Levels of Cities to Participate in Shared Parking in China," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-16, May.
    4. Xiao, Jun & Lou, Yingyan & Frisby, Joshua, 2018. "How likely am I to find parking? – A practical model-based framework for predicting parking availability," Transportation Research Part B: Methodological, Elsevier, vol. 112(C), pages 19-39.
    5. Shoup, Donald, 2021. "Pricing curb parking," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 399-412.
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