IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i9p1404-d1388312.html
   My bibliography  Save this article

Cooperative Vehicle Infrastructure System or Autonomous Driving System? From the Perspective of Evolutionary Game Theory

Author

Listed:
  • Wei Bai

    (Department of Road Traffic Management, Sichuan Police College, Luzhou 646000, China)

  • Xuguang Wen

    (Guangxi Key Laboratory of International Join for China-ASEAN Comprehensive Transportation, Nanning University, Nanning 530000, China)

  • Jiayan Zhang

    (School of Transportation, Southeast University, Nanjing 210018, China)

  • Linheng Li

    (School of Transportation, Southeast University, Nanjing 210018, China)

Abstract

In this paper, we explore the trade-offs between public and private investment in autonomous driving technologies. Utilizing an evolutionary game model, we delve into the complex interaction mechanisms between governments and auto manufacturers, focusing on how strategic decisions impact overall outcomes. Specifically, we predict that governments may opt for strategies such as constructing and maintaining infrastructure for Roadside Infrastructure-based Vehicles (RIVs) or subsidizing high-level Autonomous Driving Vehicles (ADVs) without additional road infrastructure. Manufacturers’ choices involve deciding whether to invest in RIVs or ADVs, depending on governmental policies and market conditions. Our simulation results, based on scenarios derived from existing economic data and forecasts on technology development costs, suggest that government subsidy policies need to dynamically adjust in response to manufacturers’ shifting strategies and market behavior. This dynamic adjustment is crucial as it addresses the evolving economic environment and technological advancements, ensuring that subsidies effectively incentivize the desired outcomes in autonomous vehicle development. The findings of this paper could serve as valuable decision-making tools for governments and auto manufacturers, guiding investment strategies that align with the dynamic landscape of autonomous driving technology.

Suggested Citation

  • Wei Bai & Xuguang Wen & Jiayan Zhang & Linheng Li, 2024. "Cooperative Vehicle Infrastructure System or Autonomous Driving System? From the Perspective of Evolutionary Game Theory," Mathematics, MDPI, vol. 12(9), pages 1-17, May.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:9:p:1404-:d:1388312
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/9/1404/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/9/1404/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Jun & Qin, Yanjun & Zhou, Jingyang, 2021. "Incentive policies for prefabrication implementation of real estate enterprises: An evolutionary game theory-based analysis," Energy Policy, Elsevier, vol. 156(C).
    2. Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, April.
    3. Amir Izadi & Mohammad Nabipour & Omid Titidezh, 2019. "Cost Models and Cost Factors of Road Freight Transportation: A Literature Review and Model Structure," Fuzzy Information and Engineering, Taylor & Francis Journals, vol. 11(3), pages 257-278, July.
    4. Freeman, C., 1991. "Networks of innovators: A synthesis of research issues," Research Policy, Elsevier, vol. 20(5), pages 499-514, October.
    5. Ji, Shou-feng & Zhao, Dan & Luo, Rong-juan, 2019. "Evolutionary game analysis on local governments and manufacturers' behavioral strategies: Impact of phasing out subsidies for new energy vehicles," Energy, Elsevier, vol. 189(C).
    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. Meng Ding & Hui Zeng, 2022. "Multi-Agent Evolutionary Game in the Recycling Utilization of Sulfate-Rich Wastewater," IJERPH, MDPI, vol. 19(14), pages 1-20, July.
    2. Zhao, Dan & Ji, Shou-feng & Wang, He-ping & Jiang, Li-wen, 2021. "How do government subsidies promote new energy vehicle diffusion in the complex network context? A three-stage evolutionary game model," Energy, Elsevier, vol. 230(C).
    3. Ye Gao & Renfu Jia & Yi Yao & Jiahui Xu, 2022. "Evolutionary Game Theory and the Simulation of Green Building Development Based on Dynamic Government Subsidies," Sustainability, MDPI, vol. 14(12), pages 1-18, June.
    4. Wang, Yadong & Mao, Jinqi & Chen, Fan & Wang, Delu, 2022. "Uncovering the dynamics and uncertainties of substituting coal power with renewable energy resources," Renewable Energy, Elsevier, vol. 193(C), pages 669-686.
    5. Tingfa Zhang & Huaying Qin & Weishuang Xu, 2022. "Environmental Regulation, Greenwashing Behaviour, and Green Governance of High-Pollution Enterprises in China," IJERPH, MDPI, vol. 19(19), pages 1-22, October.
    6. Dufwenberg, Martin, 1997. "Some relationships between evolutionary stability criteria in games," Economics Letters, Elsevier, vol. 57(1), pages 45-50, November.
    7. Lichi Zhang & Yanyan Jiang & Junmin Wu, 2022. "Evolutionary Game Analysis of Government and Residents’ Participation in Waste Separation Based on Cumulative Prospect Theory," IJERPH, MDPI, vol. 19(21), pages 1-16, November.
    8. Tom Johnston & Michael Savery & Alex Scott & Bassel Tarbush, 2023. "Game Connectivity and Adaptive Dynamics," Papers 2309.10609, arXiv.org, revised Oct 2024.
    9. Gu, Tianqi & Xu, Weiping & Liang, Hua & He, Qing & Zheng, Nan, 2024. "School bus transport service strategies’ policy-making mechanism – An evolutionary game approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 182(C).
    10. Petrohilos-Andrianos, Yannis & Xepapadeas, Anastasios, 2017. "Resource harvesting regulation and enforcement: An evolutionary approach," Research in Economics, Elsevier, vol. 71(2), pages 236-253.
    11. Ruigrok, Winfried & Tate, John J, 1995. "Public Testing And Research Centers In Japan," UCAIS Berkeley Roundtable on the International Economy, Working Paper Series qt3581k5pd, UCAIS Berkeley Roundtable on the International Economy, UC Berkeley.
    12. Philippe Jehiel, 2022. "Analogy-Based Expectation Equilibrium and Related Concepts:Theory, Applications, and Beyond," Working Papers halshs-03735680, HAL.
    13. Havas, Attila & Weber, K. Matthias, 2017. "The 'fit' between forward-looking activities and the innovation policy governance sub-system: A framework to explore potential impacts," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 327-337.
    14. Waters, George A., 2009. "Chaos in the cobweb model with a new learning dynamic," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1201-1216, June.
    15. Kulsum, Umma & Alam, Muntasir & Kamrujjaman, Md., 2024. "Modeling and investigating the dilemma of early and delayed vaccination driven by the dynamics of imitation and aspiration," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    16. Geyer, Anton & Davies, Andrew, 2000. "Managing project-system interfaces: case studies of railway projects in restructured UK and German markets," Research Policy, Elsevier, vol. 29(7-8), pages 991-1013, August.
    17. Guohui Song & Yongbin Wang, 2021. "Mainstream Value Information Push Strategy on Chinese Aggregation News Platform: Evolution, Modelling and Analysis," Sustainability, MDPI, vol. 13(19), pages 1-17, October.
    18. Liu, Jicheng & Sun, Jiakang & Yuan, Hanying & Su, Yihan & Feng, Shuxian & Lu, Chaoran, 2022. "Behavior analysis of photovoltaic-storage-use value chain game evolution in blockchain environment," Energy, Elsevier, vol. 260(C).
    19. Gaudeul, Alexia & Keser, Claudia & Müller, Stephan, 2021. "The evolution of morals under indirect reciprocity," Games and Economic Behavior, Elsevier, vol. 126(C), pages 251-277.
    20. Sandholm,W.H., 2003. "Excess payoff dynamics, potential dynamics, and stable games," Working papers 5, Wisconsin Madison - Social Systems.

    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:gam:jmathe:v:12:y:2024:i:9:p:1404-:d:1388312. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.