IDEAS home Printed from https://ideas.repec.org/a/spr/operea/v25y2025i1d10.1007_s12351-025-00898-1.html
   My bibliography  Save this article

Dynamic vehicle parking pricing: a bilevel optimization approach

Author

Listed:
  • Semeneh Hunachew Bayih

    (Arba Minch University)

  • Surafel Luleseged Tilahun

    (Addis Ababa Science and Technology University
    Debark University)

Abstract

This study addresses the critical challenge of optimizing parking pricing, demand, and supply in parking management systems. While previous studies have emphasized the role of dynamic pricing in traffic management, this research offers a new perspective by applying competitive game theory. By incorporating customer preferences and strategic interactions between parking agents, we address a key limitation in existing research. By considering parking agents as rational entities seeking to maximize their profits, we develop a bilevel optimization model that captures the interplay between demand, pricing strategies, and parking lot capacities. Our model leverages evolutionary algorithms to solve the optimization problem and provides valuable insights into the factors influencing parking lot profits.To evaluate the performance of our proposed model, we conducted extensive simulations using hypothetical and randomly generated data to achieve optimal pricing strategies and maximizes revenue for parking agents.

Suggested Citation

  • Semeneh Hunachew Bayih & Surafel Luleseged Tilahun, 2025. "Dynamic vehicle parking pricing: a bilevel optimization approach," Operational Research, Springer, vol. 25(1), pages 1-25, March.
  • Handle: RePEc:spr:operea:v:25:y:2025:i:1:d:10.1007_s12351-025-00898-1
    DOI: 10.1007/s12351-025-00898-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12351-025-00898-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s12351-025-00898-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lin, XuXun & Yuan, PengCheng, 2018. "A dynamic parking charge optimal control model under perspective of commuters’ evolutionary game behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1096-1110.
    2. 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.
    3. Arnott, Richard & Inci, Eren & Rowse, John, 2015. "Downtown curbside parking capacity," Journal of Urban Economics, Elsevier, vol. 86(C), pages 83-97.
    4. van Ommeren, Jos & Russo, Giovanni, 2014. "Time-varying parking prices," Economics of Transportation, Elsevier, vol. 3(2), pages 166-174.
    5. Shoup, Donald C., 1997. "The High Cost of Free Parking," University of California Transportation Center, Working Papers qt4vz087cc, University of California Transportation Center.
    6. Andrew Kelly, J. & Peter Clinch, J., 2006. "Influence of varied parking tariffs on parking occupancy levels by trip purpose," Transport Policy, Elsevier, vol. 13(6), pages 487-495, November.
    7. Shoup, Donald C., 2006. "Cruising for Parking," University of California Transportation Center, Working Papers qt55s7079f, University of California Transportation Center.
    8. Qian, Zhen (Sean) & Rajagopal, Ram, 2014. "Optimal occupancy-driven parking pricing under demand uncertainties and traveler heterogeneity: A stochastic control approach," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 144-165.
    9. Fang Zong & Yanan He & Yixin Yuan, 2015. "Dependence of Parking Pricing on Land Use and Time of Day," Sustainability, MDPI, vol. 7(7), pages 1-21, July.
    10. Hensher, David A. & King, Jenny, 2001. "Parking demand and responsiveness to supply, pricing and location in the Sydney central business district," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(3), pages 177-196, March.
    11. Shoup, Donald C., 1997. "The High Cost of Free Parking," University of California Transportation Center, Working Papers qt25w617n7, University of California Transportation Center.
    12. Liya Guo & Shan Huang & Jun Zhuang & Adel Sadek, 2013. "Modeling Parking Behavior Under Uncertainty: A Static Game Theoretic versus a Sequential Neo-additive Capacity Modeling Approach," Networks and Spatial Economics, Springer, vol. 13(3), pages 327-350, September.
    13. S. Muhammad Bagher Sadati & Jamal Moshtagh & Miadreza Shafie-khah & João P. S. Catalão, 2017. "Risk-Based Bi-Level Model for Simultaneous Profit Maximization of a Smart Distribution Company and Electric Vehicle Parking Lot Owner," Energies, MDPI, vol. 10(11), pages 1-16, October.
    14. Tilahun, Surafel Luleseged, 2019. "Feasibility reduction approach for hierarchical decision making with multiple objectives," Operations Research Perspectives, Elsevier, vol. 6(C).
    15. Zheng, Nan & Geroliminis, Nikolas, 2016. "Modeling and optimization of multimodal urban networks with limited parking and dynamic pricing," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 36-58.
    16. Shoup, Donald C., 2006. "Cruising for parking," Transport Policy, Elsevier, vol. 13(6), pages 479-486, November.
    17. Yating Zhu & Xiaofei Ye & Jun Chen & Xingchen Yan & Tao Wang, 2020. "Impact of Cruising for Parking on Travel Time of Traffic Flow," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    18. Burwell, Timothy H. & Dave, Dinesh S. & Fitzpatrick, Kathy E. & Roy, Melvin R., 1997. "Economic lot size model for price-dependent demand under quantity and freight discounts," International Journal of Production Economics, Elsevier, vol. 48(2), pages 141-155, January.
    19. Hamid Reza Eftekhari & Mehdi Ghatee, 2017. "The lower bound for dynamic parking prices to decrease congestion through CBD," Operational Research, Springer, vol. 17(3), pages 761-787, October.
    20. He, Fang & Yin, Yafeng & Chen, Zhibin & Zhou, Jing, 2015. "Pricing of parking games with atomic players," Transportation Research Part B: Methodological, Elsevier, vol. 73(C), pages 1-12.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Semeneh Hunachew Bayih & Surafel Luleseged Tilahun, 2024. "Dynamic vehicle parking pricing. A review," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 34(1), pages 35-59.
    2. Tian, Qiong & Yang, Li & Wang, Chenlan & Huang, Hai-Jun, 2018. "Dynamic pricing for reservation-based parking system: A revenue management method," Transport Policy, Elsevier, vol. 71(C), pages 36-44.
    3. 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.
    4. Krishnamurthy, Chandra Kiran B. & Ngo, Nicole S., 2020. "The effects of smart-parking on transit and traffic: Evidence from SFpark," Journal of Environmental Economics and Management, Elsevier, vol. 99(C).
    5. Inci, Eren, 2015. "A review of the economics of parking," Economics of Transportation, Elsevier, vol. 4(1), pages 50-63.
    6. Sowmya Karri & Meera M. Dhabu, 2022. "Multistage Game Model Based Dynamic Pricing for Car Parking Slot to Control Congestion," Sustainability, MDPI, vol. 14(19), pages 1-15, September.
    7. Kobus, Martijn B.W. & Gutiérrez-i-Puigarnau, Eva & Rietveld, Piet & Van Ommeren, Jos N., 2013. "The on-street parking premium and car drivers' choice between street and garage parking," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 395-403.
    8. Zhibin Chen & Stephen Spana & Yafeng Yin & Yuchuan Du, 2019. "An Advanced Parking Navigation System for Downtown Parking," Networks and Spatial Economics, Springer, vol. 19(3), pages 953-968, September.
    9. Sayarshad, Hamid R. & Sattar, Shahram & Oliver Gao, H., 2020. "A scalable non-myopic atomic game for a smart parking mechanism," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    10. Ottosson, Dadi Baldur & Chen, Cynthia & Wang, Tingting & Lin, Haiyun, 2013. "The sensitivity of on-street parking demand in response to price changes: A case study in Seattle, WA," Transport Policy, Elsevier, vol. 25(C), pages 222-232.
    11. Milosavljević, Nada & Simićević, Jelena, 2016. "User response to parking policy change: A comparison of stated and revealed preference data," Transport Policy, Elsevier, vol. 46(C), pages 40-45.
    12. Zakharenko, Roman, 2016. "The time dimension of parking economics," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 211-228.
    13. Gu, Ziyuan & Safarighouzhdi, Farshid & Saberi, Meead & Rashidi, Taha H., 2021. "A macro-micro approach to modeling parking," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 220-244.
    14. Du, Lili & Gong, Siyuan, 2016. "Stochastic Poisson game for an online decentralized and coordinated parking mechanism," Transportation Research Part B: Methodological, Elsevier, vol. 87(C), pages 44-63.
    15. Arnott, Richard & Rowse, John, 2013. "Curbside parking time limits," Transportation Research Part A: Policy and Practice, Elsevier, vol. 55(C), pages 89-110.
    16. Rodríguez, Andrés & Cordera, Rubén & Alonso, Borja & dell'Olio, Luigi & Benavente, Juan, 2022. "Microsimulation parking choice and search model to assess dynamic pricing scenarios," Transportation Research Part A: Policy and Practice, Elsevier, vol. 156(C), pages 253-269.
    17. 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.
    18. Gallo, Mariano & D'Acierno, Luca & Montella, Bruno, 2011. "A multilayer model to simulate cruising for parking in urban areas," Transport Policy, Elsevier, vol. 18(5), pages 735-744, September.
    19. Andrés Rodríguez & Luigi dell’Olio & José Luis Moura & Borja Alonso & Rubén Cordera, 2023. "Modelling Parking Choice Behaviour Considering Alternative Availability and Systematic and Random Variations in User Tastes," Sustainability, MDPI, vol. 15(11), pages 1-18, May.
    20. Lehner, Stephan & Peer, Stefanie, 2019. "The price elasticity of parking: A meta-analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 177-191.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:operea:v:25:y:2025:i:1:d:10.1007_s12351-025-00898-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.