IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v179y2024ics0965856423003099.html
   My bibliography  Save this article

Autonomous vehicle market development in Beijing: A system dynamics approach

Author

Listed:
  • Mao, Wei
  • Shepherd, Simon
  • Harrison, Gillian
  • Xu, Meng

Abstract

A system dynamics (SD) model for the autonomous vehicles (AVs) market development in Beijing is proposed. The model approaches the vehicle scale evolution with the marketization development of private AVs and shared AVs. Some potential factors such as trust, AV purchase willingness, AV using willingness and shared AV service accessibility, are analyzed. Based on the passenger vehicle situation in Beijing, optimistic scenarios from 2014 to 2050 are developed. The base scenario involves the marketization of private AVs and the operation of shared AV fleets, and based on the levels of driving automation, which are divided into six types. The causal feedback relationship and system flow diagram are illustrated. Results show that with the introduction of AVs in Beijing, the number of private vehicles is significantly decreased, which is dependent on the use of shared AVs. To compare with the private vehicle ownership in 2020, the total number of private vehicles has decreased and the number of the private vehicles is over 2.2 million vehicles in 2050. After 2030, the shared vehicle fleet will be dominated by the high-level shared AV and the number of high-level shared AVs is about 2 million. Further, to consider the impact of ride-sharing, the model compares the different attitudes for customers to share their rides and use the shared AV alternative ratio to approach this. The result shows that the extreme ratio will reduce the number of shared AVs, and the fleet size of shared vehicle is about 400,000 vehicles in 2050. For the low ratio scenario, the fleet size of shared vehicle will increase a lot to over 3,186,000 vehicles, which will lead to a large number of cars on the road and thus increase congestion. The introduction of AVs is expected to reduce the number of private vehicles; However, the uncertainty of residents' attitudes towards car sharing will affect the introduction of AVs. At present, the existing policies prefer to limit the number of vehicles by controlling car registration in Beijing. In the future, with the application of AVs, this could be adjusted by encouraging ride sharing, to achieve sustainable urban transport development in Beijing.

Suggested Citation

  • Mao, Wei & Shepherd, Simon & Harrison, Gillian & Xu, Meng, 2024. "Autonomous vehicle market development in Beijing: A system dynamics approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
  • Handle: RePEc:eee:transa:v:179:y:2024:i:c:s0965856423003099
    DOI: 10.1016/j.tra.2023.103889
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856423003099
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2023.103889?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. May, Anthony D. & Shepherd, Simon & Pfaffenbichler, Paul & Emberger, Günter, 2020. "The potential impacts of automated cars on urban transport: An exploratory analysis," Transport Policy, Elsevier, vol. 98(C), pages 127-138.
    2. Meyer, Jonas & Becker, Henrik & Bösch, Patrick M. & Axhausen, Kay W., 2017. "Autonomous vehicles: The next jump in accessibilities?," Research in Transportation Economics, Elsevier, vol. 62(C), pages 80-91.
    3. Yap, Menno D. & Correia, Gonçalo & van Arem, Bart, 2016. "Preferences of travellers for using automated vehicles as last mile public transport of multimodal train trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 1-16.
    4. Puylaert, S. & Snelder, M. & van Nes, R. & van Arem, B., 2018. "Mobility impacts of early forms of automated driving – A system dynamic approach," Transport Policy, Elsevier, vol. 72(C), pages 171-179.
    5. Lavieri, Patrícia S. & Bhat, Chandra R., 2019. "Modeling individuals’ willingness to share trips with strangers in an autonomous vehicle future," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 242-261.
    6. Fagnant, Daniel J. & Kockelman, Kara, 2015. "Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 167-181.
    7. Abbas, Khaled A. & Bell, Michael G. H., 1994. "System dynamics applicability to transportation modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 28(5), pages 373-390, September.
    8. Bansal, Prateek & Kockelman, Kara M., 2017. "Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 49-63.
    9. Kaltenhäuser, Bernd & Werdich, Karl & Dandl, Florian & Bogenberger, Klaus, 2020. "Market development of autonomous driving in Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 882-910.
    10. Fraedrich, Eva & Heinrichs, Dirk & Bahamonde-Birke, Francisco J. & Cyganski, Rita, 2019. "Autonomous driving, the built environment and policy implications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 122(C), pages 162-172.
    11. Gómez Vilchez, Jonatan J. & Jochem, Patrick, 2019. "Simulating vehicle fleet composition: A review of system dynamics models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    12. Scott Kaplan & Ben Gordon & Feras El Zarwi & Joan L. Walker & David Zilberman, 2019. "The Future of Autonomous Vehicles: Lessons from the Literature on Technology Adoption," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 41(4), pages 583-597, December.
    13. Peng Jing & Hao Huang & Bin Ran & Fengping Zhan & Yuji Shi, 2019. "Exploring the Factors Affecting Mode Choice Intention of Autonomous Vehicle Based on an Extended Theory of Planned Behavior—A Case Study in China," Sustainability, MDPI, vol. 11(4), pages 1-20, February.
    14. Gillian Harrison & Simon P. Shepherd & Haibo Chen, 2021. "Modelling Uptake Sensitivities of Connected and Automated Vehicle Technologies," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 10(2), pages 88-106, April.
    15. Contreras, Seth D. & Paz, Alexander, 2018. "The effects of ride-hailing companies on the taxicab industry in Las Vegas, Nevada," Transportation Research Part A: Policy and Practice, Elsevier, vol. 115(C), pages 63-70.
    16. Hudson, John & Orviska, Marta & Hunady, Jan, 2019. "People’s attitudes to autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 164-176.
    17. Docherty, Iain & Marsden, Greg & Anable, Jillian, 2018. "The governance of smart mobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 115(C), pages 114-125.
    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. Kassens-Noor, Eva & Dake, Dana & Decaminada, Travis & Kotval-K, Zeenat & Qu, Teresa & Wilson, Mark & Pentland, Brian, 2020. "Sociomobility of the 21st century: Autonomous vehicles, planning, and the future city," Transport Policy, Elsevier, vol. 99(C), pages 329-335.
    2. Limin Tan & Changxi Ma & Xuecai Xu & Jin Xu, 2019. "Choice Behavior of Autonomous Vehicles Based on Logistic Models," Sustainability, MDPI, vol. 12(1), pages 1-16, December.
    3. Tang, Zhe-Yi & Tian, Li-Jun & Wang, David Z.W., 2021. "Multi-modal morning commute with endogenous shared autonomous vehicle penetration considering parking space constraint," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    4. Wadud, Zia & Mattioli, Giulio, 2021. "Fully automated vehicles: A cost-based analysis of the share of ownership and mobility services, and its socio-economic determinants," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 228-244.
    5. Schepis, Daniel & Purchase, Sharon & Olaru, Doina & Smith, Brett & Ellis, Nick, 2023. "How governments influence autonomous vehicle (AV) innovation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    6. Nastjuk, Ilja & Herrenkind, Bernd & Marrone, Mauricio & Brendel, Alfred Benedikt & Kolbe, Lutz M., 2020. "What drives the acceptance of autonomous driving? An investigation of acceptance factors from an end-user's perspective," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    7. Devon McAslan & Farah Najar Arevalo & David A. King & Thaddeus R. Miller, 2021. "Pilot project purgatory? Assessing automated vehicle pilot projects in U.S. cities," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-16, December.
    8. Sindi, Safaa & Woodman, Roger, 2021. "Implementing commercial autonomous road haulage in freight operations: An industry perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 235-253.
    9. Kassens-Noor, Eva & Kotval-Karamchandani, Zeenat & Cai, Meng, 2020. "Willingness to ride and perceptions of autonomous public transit," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 92-104.
    10. Nikitas, Alexandros & Parkinson, Simon & Vallati, Mauro, 2022. "The deceitful Connected and Autonomous Vehicle: Defining the concept, contextualising its dimensions and proposing mitigation policies," Transport Policy, Elsevier, vol. 122(C), pages 1-10.
    11. Guo, Yuntao & Souders, Dustin & Labi, Samuel & Peeta, Srinivas & Benedyk, Irina & Li, Yujie, 2021. "Paving the way for autonomous Vehicles: Understanding autonomous vehicle adoption and vehicle fuel choice under user heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 364-398.
    12. Manivasakan, Hesavar & Kalra, Riddhi & O'Hern, Steve & Fang, Yihai & Xi, Yinfei & Zheng, Nan, 2021. "Infrastructure requirement for autonomous vehicle integration for future urban and suburban roads – Current practice and a case study of Melbourne, Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 36-53.
    13. Nadafianshahamabadi, Razieh & Tayarani, Mohammad & Rowangould, Gregory, 2021. "A closer look at urban development under the emergence of autonomous vehicles: Traffic, land use and air quality impacts," Journal of Transport Geography, Elsevier, vol. 94(C).
    14. Simpson, Jesse R. & Mishra, Sabyasachee, 2021. "Developing a methodology to predict the adoption rate of Connected Autonomous Trucks in transportation organizations using peer effects," Research in Transportation Economics, Elsevier, vol. 90(C).
    15. Raj, Alok & Kumar, J. Ajith & Bansal, Prateek, 2020. "A multicriteria decision making approach to study barriers to the adoption of autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 122-137.
    16. Mohamad Shatanawi & Mohammed Hajouj & Belal Edries & Ferenc Mészáros, 2022. "The Interrelationship between Road Pricing Acceptability and Self-Driving Vehicle Adoption: Insights from Four Countries," Sustainability, MDPI, vol. 14(19), pages 1-32, October.
    17. Jen Sim Ho & Booi Chen Tan & Teck Chai Lau & Nasreen Khan, 2023. "Public Acceptance towards Emerging Autonomous Vehicle Technology: A Bibliometric Research," Sustainability, MDPI, vol. 15(2), pages 1-18, January.
    18. Mohammadhossein Abbasi & Amir Reza Mamdoohi & Grzegorz Sierpiński & Francesco Ciari, 2023. "Usage Intention of Shared Autonomous Vehicles with Dynamic Ride Sharing on Long-Distance Trips," Sustainability, MDPI, vol. 15(2), pages 1-17, January.
    19. Schweitzer, Nicola & Hofmann, Rupert & Meinheit, Andreas, 2019. "Strategic customer foresight: From research to strategic decision-making using the example of highly automated vehicles," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 49-65.
    20. Mourad, Abood & Puchinger, Jakob & Chu, Chengbin, 2019. "A survey of models and algorithms for optimizing shared mobility," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 323-346.

    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:transa:v:179:y:2024:i:c:s0965856423003099. 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/547/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.