IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-05113190.html

MobilityCoins - Towards an Agent-Based Approach to Simulating Tradable Mobility Credits

Author

Listed:
  • Philipp Servatius

    (TUM - Technische Universität Munchen = Technical University Munich = Université Technique de Munich)

  • Sebastian Hörl

    (IRT SystemX)

  • Klaus Bogenberger

    (TUM - Technische Universität Munchen = Technical University Munich = Université Technique de Munich)

Abstract

Congestion and increased emissions are prominent in global metropolitan areas, largely due to the lack of restrictions on car usage. While the industry is innovating by shifting to less carbon-intensive engines, the congestion problem remains largely unsolved. We propose a novel economic policy instrument called the MobilityCoin System. Based on tradable mobility credits (TMC), every user receives a credit budget at the start of each term that can be used to pay for trips. The extended abstract serves as a proof of concept for the simulation environment

Suggested Citation

  • Philipp Servatius & Sebastian Hörl & Klaus Bogenberger, 2025. "MobilityCoins - Towards an Agent-Based Approach to Simulating Tradable Mobility Credits," Post-Print hal-05113190, HAL.
  • Handle: RePEc:hal:journl:hal-05113190
    Note: View the original document on HAL open archive server: https://hal.science/hal-05113190v1
    as

    Download full text from publisher

    File URL: https://hal.science/hal-05113190v1/document
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yang, Hai & Wang, Xiaolei, 2011. "Managing network mobility with tradable credits," Transportation Research Part B: Methodological, Elsevier, vol. 45(3), pages 580-594, March.
    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. Valentina Morandi, 2024. "Bridging the user equilibrium and the system optimum in static traffic assignment: a review," 4OR, Springer, vol. 22(1), pages 89-119, March.
    2. Choi, T.S. & To, Kiwing & Wong, K.Y. Michael, 2024. "The dynamics of traffic congestion: Data from a freeway Electronic Toll Collection system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).
    3. Dogterom, Nico & Ettema, Dick & Dijst, Martin, 2018. "Behavioural effects of a tradable driving credit scheme: Results of an online stated adaptation experiment in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 52-64.
    4. Ling-Ling Xiao & Tian-Liang Liu & Hai-Jun Huang, 2021. "Tradable permit schemes for managing morning commute with carpool under parking space constraint," Transportation, Springer, vol. 48(4), pages 1563-1586, August.
    5. Yu Nie, 2015. "A New Tradable Credit Scheme for the Morning Commute Problem," Networks and Spatial Economics, Springer, vol. 15(3), pages 719-741, September.
    6. Brands, Devi K. & Verhoef, Erik T. & Knockaert, Jasper & Koster, Paul R., 2020. "Tradable permits to manage urban mobility: Market design and experimental implementation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 34-46.
    7. Bi, Huibo & Shang, Wen-Long & Chen, Yanyan & Wang, Kezhi & Yu, Qing & Sui, Yi, 2021. "GIS aided sustainable urban road management with a unifying queueing and neural network model," Applied Energy, Elsevier, vol. 291(C).
    8. 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).
    9. Han, Linghui & Zhu, Chengjuan & Wang, David Z.W. & Sun, Huijun & Tan, Zhijia & Meng, Meng, 2019. "Discrete-time dynamic road congestion pricing under stochastic user optimal principle," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 131(C), pages 24-36.
    10. Tian, Ye & Li, Yudi & Sun, Jian, 2022. "Stick or carrot for traffic demand management? Evidence from experimental economics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 235-254.
    11. Geng, Kexin & Liang, Zhiyuan & Verhoef, Erik T. & Wang, Yacan, 2025. "Managing uncertain traffic and societal externalities in a road and rail network: Pricing versus Permits," Transportation Research Part B: Methodological, Elsevier, vol. 196(C).
    12. Ding, Yanyan & Jian, Sisi & Yu, Lin, 2025. "How to reduce carbon emissions in the urban transportation systems through carbon markets? Balancing the monetary and environmental benefits," Applied Energy, Elsevier, vol. 377(PB).
    13. Ding, Hongxing & Yang, Hai & Qin, Xiaoran & Xu, Hongli, 2023. "Credit charge-cum-reward scheme for green multi-modal mobility," Transportation Research Part B: Methodological, Elsevier, vol. 178(C).
    14. Fei Han & Jian Wang & Lingli Huang & Yan Li & Liu He, 2023. "Modeling Impacts of Implementation Policies of Tradable Credit Schemes on Traffic Congestion in the Context of Traveler’s Cognitive Illusion," Sustainability, MDPI, vol. 15(15), pages 1-18, July.
    15. Yang Liu & Yu (Marco) Nie, 2017. "A Credit-Based Congestion Management Scheme in General Two-Mode Networks with Multiclass Users," Networks and Spatial Economics, Springer, vol. 17(3), pages 681-711, September.
    16. Mounce, Richard & Nelson, John D., 2019. "On the potential for one-way electric vehicle car-sharing in future mobility systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 17-30.
    17. Xiao, Feng & Qian, Zhen (Sean) & Zhang, H. Michael, 2013. "Managing bottleneck congestion with tradable credits," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 1-14.
    18. Wang, Fei & Zhang, Zhentai & Lin, Shoufu, 2023. "Purchase intention of Autonomous vehicles and industrial Policies: Evidence from a national survey in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    19. Wang, Hua & Zhang, Xiaoning, 2016. "Joint implementation of tradable credit and road pricing in public-private partnership networks considering mixed equilibrium behaviors," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 158-170.
    20. Tian, Lijun & Cui, Shuang & Huang, Haijun & Xu, Yan & Wang, Yacan, 2024. "How the norm activation model explains the individuals’ response to Tradable Credit Schemes and reducing car use," Transport Policy, Elsevier, vol. 155(C), pages 208-223.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:hal:journl:hal-05113190. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.