IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v166y2025icp87-100.html
   My bibliography  Save this article

Parking pricing strategies in the era of autonomous vehicles

Author

Listed:
  • Zhang, Xinying
  • Zhang, Haitao
  • Yan, Sanghuiyu
  • Xie, Minghui
  • Wang, Yuanqing

Abstract

Conventional parking behavior could be completely changed with the arrival of autonomous vehicles (AVs). Unlike conventional vehicles (CVs), which are restricted to parking in specified lots, AVs eliminate the limitation of human driving and provide travelers with a wider range of parking options. This study examines the distinct parking choice behaviors of AVs and CVs and develops pricing strategies for parking lots. To this end, parking choice models for AVs and CVs are separately developed based on their respective parking costs. An agent-based simulation framework is constructed to simulate the parking processes of both vehicle types and capture the macroscopic impacts of individual parking decisions on system. A genetic algorithm (GA) optimization approach is applied to determine the optimal parking pricing. The results indicate that when AVs and CVs each account for 50% of the market, distinct pricing strategies are required to achieve specific objectives. Specifically, under the objective of minimizing vehicle kilometers of travel (VKT), high parking fees should be imposed on parking lots in the city center to guide them toward adjacent areas with low prices. Similarly, achieving vehicle travel time (VTT) minimization requires implementing extremely low prices for peripheral parking lots to attract vehicles, thereby reducing congestion in central areas. Notably, the pricing strategies for VTT minimization and total utilization time (TUT) maximization share certain similarities under this equal-proportion scenario. Moreover, if the penetration rate of CVs exceeds that of AVs, parking revenue can be maximized by establishing high prices across all parking lots. Conversely, when AVs become dominant, it is necessary to lower parking prices appropriately to encourage AVs to utilize parking lots.

Suggested Citation

  • Zhang, Xinying & Zhang, Haitao & Yan, Sanghuiyu & Xie, Minghui & Wang, Yuanqing, 2025. "Parking pricing strategies in the era of autonomous vehicles," Transport Policy, Elsevier, vol. 166(C), pages 87-100.
    • Handle: RePEc:eee:trapol:v:166:y:2025:i:c:p:87-100
    DOI: 10.1016/j.tranpol.2025.03.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X25000927
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tranpol.2025.03.003?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. Millard-Ball, Adam, 2019. "The autonomous vehicle parking problem," Transport Policy, Elsevier, vol. 75(C), pages 99-108.
    2. Mei, Zhenyu & Feng, Chi & Ding, Wenchao & Zhang, Lihui & Wang, Dianhai, 2019. "Better lucky than rich? Comparative analysis of parking reservation and parking charge," Transport Policy, Elsevier, vol. 75(C), pages 47-56.
    3. Bahrami, Sina & Roorda, Matthew, 2022. "Autonomous vehicle parking policies: A case study of the City of Toronto," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 283-296.
    4. Lam, William H.K. & Li, Zhi-Chun & Huang, Hai-Jun & Wong, S.C., 2006. "Modeling time-dependent travel choice problems in road networks with multiple user classes and multiple parking facilities," Transportation Research Part B: Methodological, Elsevier, vol. 40(5), pages 368-395, June.
    5. 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).
    6. 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.
    7. Lu, Xiao-Shan & Huang, Hai-Jun & Guo, Ren-Yong & Xiong, Fen, 2021. "Linear location-dependent parking fees and integrated daily commuting patterns with late arrival and early departure in a linear city," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 293-322.
    8. Fabusuyi, Tayo & Hampshire, Robert C., 2018. "Rethinking performance based parking pricing: A case study of SFpark," Transportation Research Part A: Policy and Practice, Elsevier, vol. 115(C), pages 90-101.
    9. Chaniotakis, Emmanouil & Pel, Adam J., 2015. "Drivers’ parking location choice under uncertain parking availability and search times: A stated preference experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 228-239.
    10. Najmi, Ali & Bostanara, Maryam & Gu, Ziyuan & Rashidi, Taha H., 2021. "On-street parking management and pricing policies: An evaluation from a system enhancement perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 146(C), pages 128-151.
    11. Martha A. Roper & Konstantinos Triantis & G. Don Taylor & Dusan Teodorović, 2018. "Revenue management in the parking industry: a multiple garage intelligent reservation model," Transportation Planning and Technology, Taylor & Francis Journals, vol. 41(3), pages 286-300, April.
    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. 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).
    2. Najmi, Ali & Bostanara, Maryam & Gu, Ziyuan & Rashidi, Taha H., 2021. "On-street parking management and pricing policies: An evaluation from a system enhancement perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 146(C), pages 128-151.
    3. Xie, Minghui & Lin, Siyu & Wei, Sen & Zhang, Xinying & Wang, Yao & Wang, Yuanqing, 2025. "Online configuration of reservable parking spaces: An agent-based deep reinforcement learning approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 194(C).
    4. Xiaojuan Yu & Vincent A.C. van den Berg, 2024. "Human-driven vehicles’ cruising versus autonomous vehicles’ back- and-forth congestion: The effects on traveling, parking and congestion," Tinbergen Institute Discussion Papers 24-032/VIII, Tinbergen Institute.
    5. Gu, Ziyuan & Li, Yifan & Saberi, Meead & Rashidi, Taha H. & Liu, Zhiyuan, 2023. "Macroscopic parking dynamics and equitable pricing: Integrating trip-based modeling with simulation-based robust optimization," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 354-381.
    6. 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.
    7. 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.
    8. Bahrami, Sina & Roorda, Matthew, 2022. "Autonomous vehicle parking policies: A case study of the City of Toronto," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 283-296.
    9. Jiang, Bowen & Fan, Zhi-Ping, 2020. "Optimal allocation of shared parking slots considering parking unpunctuality under a platform-based management approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    10. 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.
    11. Feng, Jianghong & Xu, Su Xiu & Xu, Gangyan & Cheng, Huibing, 2022. "An integrated decision-making method for locating parking centers of recyclable waste transportation vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    12. 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.
    13. Zipeng Zhang & Ning Zhang, 2021. "Early Bird Scheme for Parking Management: How Does Parking Play a Role in the Morning Commute Problem," Sustainability, MDPI, vol. 13(15), pages 1-19, July.
    14. You Kong & Jihong Ou & Longfei Chen & Fengchun Yang & Bo Yu, 2023. "The Environmental Impacts of Automated Vehicles on Parking: A Systematic Review," Sustainability, MDPI, vol. 15(20), pages 1-21, October.
    15. Phuc Hai Hoang & Shengchuan Zhao & Siv Eng Houn, 2019. "Motorcycle Drivers’ Parking Lot Choice Behaviors in Developing Countries: Analysis to Identify Influence Factors," Sustainability, MDPI, vol. 11(9), pages 1-15, April.
    16. Tian, Li-Jun & Tang, Zhe-Yi & Liu, Peng & Huang, Hai-Jun, 2024. "Parking policy design for managing morning commute with dedicated autonomous vehicle lane," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 192(C).
    17. Fan Wu & Wei Ma, 2022. "Clustering Analysis of the Spatio-Temporal On-Street Parking Occupancy Data: A Case Study in Hong Kong," Sustainability, MDPI, vol. 14(13), pages 1-25, June.
    18. Wei Wu & Wei Liu & Fangni Zhang & Vinayak Dixit, 2021. "A New Flexible Parking Reservation Scheme for the Morning Commute under Limited Parking Supplies," Networks and Spatial Economics, Springer, vol. 21(3), pages 513-545, September.
    19. Kadkhodaei, Masoud & Shad, Rouzbeh & Ziaee, Seyed Ali & Kadkhodaei, Mohsen, 2023. "Prediction model for drivers' tendency to perpetrate a double parking violation on urban trips," Transport Policy, Elsevier, vol. 141(C), pages 331-339.
    20. 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).

    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:eee:trapol:v:166:y:2025:i:c:p:87-100. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/30473/description#description .

    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.