IDEAS home Printed from https://ideas.repec.org/a/igg/jsda00/v10y2021i2p88-106.html
   My bibliography  Save this article

Modelling Uptake Sensitivities of Connected and Automated Vehicle Technologies

Author

Listed:
  • Gillian Harrison

    (University of Leeds, UK)

  • Simon P. Shepherd

    (University of Leeds, UK)

  • Haibo Chen

    (University of Leeds, UK)

Abstract

Connected and automated vehicle (CAV) technologies and services are rapidly developing and have the potential to revolutionise the transport systems. However, like many innovations, the uptake pathways are uncertain. The focus of this article is on improving understanding of factors that may affect the uptake of highly and fully automated vehicles, with a particular interest in the role of the internet of things (IoT). Using system dynamic modelling, sensitivity testing towards vehicle attributes (e.g., comfort, safety, familiarity) is carried out and scenarios were developed to explore how CAV uptake can vary under different conditions based around the quality of IoT provision. Utility and poor IoT are found to have the biggest influence. Attention is then given to CAV ‘services' that are characterized by the attributes explored earlier in the paper, and it is found that they could contribute to a 20% increase in market share.

Suggested Citation

  • 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.
    • Handle: RePEc:igg:jsda00:v:10:y:2021:i:2:p:88-106
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSDA.2021040106
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marshall, Phil, 2015. "System dynamics modeling of the impact of Internet-of-Things on intelligent urban transportation," 2015 Regional ITS Conference, Los Angeles 2015 146348, International Telecommunications Society (ITS).
    2. Alex Kizito & Agnes Rwashana Semwanga, 2020. "Modeling the Complexity of Road Accidents Prevention: A System Dynamics Approach," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 9(2), pages 24-41, April.
    3. Aalok Kumar & Ramesh Anbanandam, 2019. "Multimodal Freight Transportation Strategic Network Design for Sustainable Supply Chain: An OR Prospective Literature Review," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 8(2), pages 19-35, April.
    4. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    5. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    6. Paul Pfaffenbichler & Günter Emberger & Simon Shepherd, 2008. "The Integrated Dynamic Land Use and Transport Model MARS," Networks and Spatial Economics, Springer, vol. 8(2), pages 183-200, September.
    7. 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).
    8. Jeroen Struben & John D. Sterman, 2008. "Transition Challenges for Alternative Fuel Vehicle and Transportation Systems," Post-Print hal-02312277, HAL.
    9. David E. Boyce & Huw C.W.L. Williams, 2015. "Forecasting Urban Travel," Books, Edward Elgar Publishing, number 13829.
    10. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    11. David Pierce & Simon Shepherd & Daniel Johnson, 2019. "Modelling the Impacts of Inter-City Connectivity on City Specialisation," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 8(4), pages 47-70, October.
    12. repec:igg:jsda00:v:8:y:2019:i:4:p:1-24 is not listed on IDEAS
    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. 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).
    2. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    3. Anders F. Jensen & Elisabetta Cherchi & Stefan L. Mabit & Juan de Dios Ortúzar, 2017. "Predicting the Potential Market for Electric Vehicles," Transportation Science, INFORMS, vol. 51(2), pages 427-440, May.
    4. Shepherd, Simon & Bonsall, Peter & Harrison, Gillian, 2012. "Factors affecting future demand for electric vehicles: A model based study," Transport Policy, Elsevier, vol. 20(C), pages 62-74.
    5. Karsten Kieckhäfer & Thomas Volling & Thomas Stefan Spengler, 2014. "A Hybrid Simulation Approach for Estimating the Market Share Evolution of Electric Vehicles," Transportation Science, INFORMS, vol. 48(4), pages 651-670, November.
    6. Tran, Martino, 2012. "Technology-behavioural modelling of energy innovation diffusion in the UK," Applied Energy, Elsevier, vol. 95(C), pages 1-11.
    7. Petschnig, Martin & Heidenreich, Sven & Spieth, Patrick, 2014. "Innovative alternatives take action – Investigating determinants of alternative fuel vehicle adoption," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 68-83.
    8. Pasaoglu, Guzay & Harrison, Gillian & Jones, Lee & Hill, Andrew & Beaudet, Alexandre & Thiel, Christian, 2016. "A system dynamics based market agent model simulating future powertrain technology transition: Scenarios in the EU light duty vehicle road transport sector," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 133-146.
    9. J�r�me Massiani, 2013. "The use of Stated Preferences to forecast alternative fuel vehicles market diffusion: Comparisons with other methods and proposal for a Synthetic Utility Function," Working Papers 2013:12, Department of Economics, University of Venice "Ca' Foscari".
    10. Axsen, Jonn, 2010. "Interpersonal Influence within Car Buyers’ Social Networks: Observing Consumer Assessment of Plug-in Hybrid Electric Vehicles (PHEVs) and the Spread of Pro-Societal Values," Institute of Transportation Studies, Working Paper Series qt8p32d18k, Institute of Transportation Studies, UC Davis.
    11. Lee, Yongseung & Kim, Chongman & Shin, Juneseuk, 2016. "A hybrid electric vehicle market penetration model to identify the best policy mix: A consumer ownership cycle approach," Applied Energy, Elsevier, vol. 184(C), pages 438-449.
    12. Wolinetz, Michael & Axsen, Jonn, 2017. "How policy can build the plug-in electric vehicle market: Insights from the REspondent-based Preference And Constraints (REPAC) model," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 238-250.
    13. Oliveira, Gabriela D. & Roth, Richard & Dias, Luis C., 2019. "Diffusion of alternative fuel vehicles considering dynamic preferences," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 83-99.
    14. Sykes, Maxwell & Axsen, Jonn, 2017. "No free ride to zero-emissions: Simulating a region's need to implement its own zero-emissions vehicle (ZEV) mandate to achieve 2050 GHG targets," Energy Policy, Elsevier, vol. 110(C), pages 447-460.
    15. Sierzchula, William & Bakker, Sjoerd & Maat, Kees & van Wee, Bert, 2014. "The influence of financial incentives and other socio-economic factors on electric vehicle adoption," Energy Policy, Elsevier, vol. 68(C), pages 183-194.
    16. Sana Akbar Khan, 2017. "Consumer Innovation Adoption Stages and Determinants," Working Papers 03, Department of Management, Università Ca' Foscari Venezia.
    17. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    18. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    19. Proost, Stef & Van Dender, Kurt, 2012. "Energy and environment challenges in the transport sector," Economics of Transportation, Elsevier, vol. 1(1), pages 77-87.
    20. Ito, Nobuyuki & Takeuchi, Kenji & Managi, Shunsuke, 2019. "Do battery-switching systems accelerate the adoption of electric vehicles? A stated preference study," Economic Analysis and Policy, Elsevier, vol. 61(C), pages 85-92.

    More about this item

    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:igg:jsda00:v:10:y:2021:i:2:p:88-106. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.