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Pricing curb parking

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  • Shoup, Donald

Abstract

Where traffic is congested and all the curb spaces are occupied, some drivers are probably cruising for parking. Cities can eliminate this cruising by charging demand-based prices for curb parking to ensure one or two open spaces on every block. Drivers will then usually find convenient places to park within a short walk of their destinations. But if cities charge demand-based prices for curb parking, how will drivers choose where to park, and what will they pay? To answer these questions, I have examined how four variables—parking duration, number of persons in the car, walking speed, and value of saving time spent walking—determine parking choices when prices increase as drivers approach their destinations. Short-term parkers, carpools, slow walkers, and drivers with a high value of saving time will park closer to their destinations. Long-term parkers, solo drivers, fast walkers, and drivers with a low value of saving time will park farther away. This spontaneous, self-organizing pattern of parking choices responding to demand-based parking prices will minimize the collective cost of the time drivers spend walking to and from their destinations. Demand-priced curb parking will also reduce uncertainty about travel times. Drivers delayed by traffic congestion can save time at the end of their trips by paying a higher price to park closer to their destinations. Demand-priced curb parking at the end of a trip can serve as a buffer allowing late-arriving drivers to buy time when they need it most.

Suggested Citation

  • Shoup, Donald, 2021. "Pricing curb parking," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 399-412.
    • Handle: RePEc:eee:transa:v:154:y:2021:i:c:p:399-412
    DOI: 10.1016/j.tra.2021.04.012
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    References listed on IDEAS

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    Cited by:

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    2. Zhang, Xinying & Pitera, Kelly & Wang, Yuanqing, 2024. "Exploring parking choices under the coexistence of autonomous and conventional vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
    3. Tscharaktschiew, Stefan & Reimann, Felix, 2023. "The economics of speed choice and control in the presence of driverless vehicle cruising and parking-as-a-substitute-for-cruising," Transportation Research Part B: Methodological, Elsevier, vol. 178(C).
    4. Ogulenko, Aleksey & Benenson, Itzhak & Fulman, Nir, 2022. "The nature of the on-street parking search," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 48-68.
    5. Ben-Dor, Golan & Ogulenko, Aleksey & Klein, Ido & Ben-Elia, Eran & Benenson, Itzhak, 2024. "Simulation-based policy evaluation of monetary car driving disincentives in Jerusalem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 183(C).
    6. Eliasson, Jonas & Börjesson, Maria, 2022. "Costs and benefits of parking charges in residential areas," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 95-109.
    7. Zhuang, Zheng-Yun & Chung, Cheng-Kung, 2024. "Dissecting the visiting willingness of driving visitors facing a retail market's dual-pricing policy for parking," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    8. McAslan, Devon & Sprei, Frances, 2023. "Minimum parking requirements and car ownership: An analysis of Swedish municipalities," Transport Policy, Elsevier, vol. 135(C), pages 45-58.
    9. 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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