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Assessment of Different Parking Pricing Strategies: A Simulation-based Analysis

Author

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  • Zhenyu Mei

    (College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China)

  • Chi Feng

    (College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China)

  • Liang Kong

    (College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China)

  • Lihui Zhang

    (College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China)

  • Jun Chen

    (School of Transportation, Southeast University, Nanjin 210096, China)

Abstract

Parking demand exceeding parking supply and uneven parking demand distribution are the existing conflicts in city centers. Parking pricing is frequently utilized to manage parking resources. This study aims to assess different parking pricing strategies through simulations for providing operational suggestions for urban parking managers. Two widely used parking pricing strategies in China combined with an optimized parking pricing strategy are proposed and compared. We introduce an agent-based simulation system to describe the parking and traffic conditions. Various measures of effectiveness under different parking pricing strategies can be obtained via agent-based simulations. We then construct a comprehensive benefit combining average cost and failure rate. Results show that the second strategy with charging different parking fees by considering locations and third optimized strategy can effectively improve traffic efficiency. However, the second strategy may lead to higher average cost than that of the third one. Thus, the third optimized strategy performs the best and can be used to optimize the parking policy of parking managers in the future. The entire assessment through simulations can provide evaluation suggestions for parking managers to adjust parking policies.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:5:p:2056-:d:329616
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    References listed on IDEAS

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    6. 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.

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