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Flexible parking reservation system and pricing: A continuum approximation approach

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  • Wang, Xiaotian
  • Wang, Xin

Abstract

Reservation-based parking systems have the merit of eliminating vehicle cruising for parking. While many long-period (e.g., daily) parking reservation services are already in use, short-period (e.g., hourly) parking reservation remains a huge challenge due to the high uncertainty of customer arrivals and departures. To mitigate the service failure caused by random late departures of customers, we propose a new flexible reservation mechanism in which the reservation is no longer restricted to a specific location at a specific time, but tolerates predetermined spatiotemporal flexibility instead. With a pricing instrument designed for such parking flexibility, customers can coordinate to significantly reduce the reservation failure rate, resulting in an optimal system equilibrium benefiting the entire society. Due to the complex nature of this system, a continuum approximation framework is used to provide tractable analysis for a large-scale urban parking system. We can successfully provide accurate system management decision support with a bounded optimality gap and analytical insights.

Suggested Citation

  • Wang, Xiaotian & Wang, Xin, 2019. "Flexible parking reservation system and pricing: A continuum approximation approach," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 408-434.
    • Handle: RePEc:eee:transb:v:128:y:2019:i:c:p:408-434
    DOI: 10.1016/j.trb.2019.07.006
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    4. Nazmus Sakib & A. S. M. Bakibillah & Susilawati Susilawati & Md Abdus Samad Kamal & Kou Yamada, 2024. "Eco-Friendly Smart Car Parking Management System with Enhanced Sustainability," Sustainability, MDPI, vol. 16(10), pages 1-14, May.
    5. Ye, Jiao & Cao, Ruide & He, Biao & Kuai, Xi & Guo, Renzhong, 2024. "Disaggregated spatiotemporal traffic assignment for road reservation service and supply-demand statistical analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 645(C).
    6. Tan, Bing Qing & Xu, Su Xiu & Thürer, Matthias & Kang, Kai & Zhao, Zhiheng & Li, Ming, 2024. "Booking versus search-based parking strategy: A game-theoretic methodology," Research in Transportation Economics, Elsevier, vol. 104(C).
    7. Luetian Sun & Rui Song, 2022. "Improving Efficiency in Congested Traffic Networks: Pareto-Improving Reservations through Agent-Based Timetabling," Sustainability, MDPI, vol. 14(4), pages 1-24, February.
    8. Zhou, Xizhen & Lv, Mengqi & Ji, Yanjie & Zhang, Shuichao & Liu, Yong, 2023. "Pricing curb parking: Differentiated parking fees or cash rewards?," Transport Policy, Elsevier, vol. 142(C), pages 46-58.
    9. Macea, Luis F. & Serrano, Iván & Carcache-Guas, Camila, 2023. "A reservation-based parking behavioral model for parking demand management in urban areas," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    10. Chen, Rong & Gao, Ge & Kang, Liu-Jiang & Zhang, Li-Ye, 2024. "Efficiency and equity analysis on parking reservation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 187(C).
    11. 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).
    12. Yu, Hao & Huang, Min & Song, Yang & Wang, Xingwei & Yue, Xiaohang, 2025. "Making the most of your private parking slot: Strategy-proof double auctions-enabled staggered sharing schemes," Transportation Research Part B: Methodological, Elsevier, vol. 191(C).

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