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Modeling and solving the optimal allocation-pricing of public parking resources problem in urban-scale network

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  • Wang, Pengfei
  • Guan, Hongzhi
  • Liu, Peng

Abstract

This paper models and solves the optimal allocation-pricing of reservable parking resources and the pricing of unreservable parking resources, respectively. For reservable parking facility, a MP-DGS (modified proxy Demange-Gale-Sotomayor) mechanism and combinatorial system (integration of direct and evolutionary methods) are adopted to maximize the social surplus through optimizing the allocation-pricing of parking permits. As a result, it is found that: (i) the proposed approaches not only simplify the users’ bidding procedures but also ensure the users express their preference truthfully even under the situation of non-optimal parking permits allocation; (ii) in homogeneous case (parking periods for all users are the same), it is theoretically demonstrated that the MP-DGS mechanism is more efficient than the traditional mechanisms in the worst-case scenario; (iii) in heterogeneous case (users are heterogeneous in desired parking timing and duration), time-dependent parking permits are taken into account. The ranking of the algorithm time complexity in the worst-case scenario is that direct method = evolutionary method < Leonard mechanism = VCG (Vickrey-Clarke-Groves) mechanism, and the combinatorial system not only solves out the optimal allocation-pricing results effectively but also ensures the optimal results can be obtained in a shorter time. In addition, for unreservable parking facility, we formulate a dynamic social optimum as a stochastic control problem and then obtain a region-based optimal dynamic parking pricing. Through theoretical analysis, it is revealed that depending on the realization of the queue length due to the cruising-for-parking, the region-based optimal dynamic parking pricing can be divided into two patterns, furthermore, each pattern results in a “bang-bang” control.

Suggested Citation

  • Wang, Pengfei & Guan, Hongzhi & Liu, Peng, 2020. "Modeling and solving the optimal allocation-pricing of public parking resources problem in urban-scale network," Transportation Research Part B: Methodological, Elsevier, vol. 137(C), pages 74-98.
    • Handle: RePEc:eee:transb:v:137:y:2020:i:c:p:74-98
    DOI: 10.1016/j.trb.2019.03.003
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    6. Yunqiang Xue & Qifang Kong & Feng Sun & Meng Zhong & Haokai Tu & Caifeng Tan & Hongzhi Guan, 2022. "Shared Parking Decision Behavior of Parking Space Owners and Car Travelers Based on Prospect Theory—A Case Study of Nanchang City, China," Sustainability, MDPI, vol. 14(24), pages 1-17, December.

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