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Modelling Uptake Sensitivities of Connected and Automated Vehicle Technologies

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  • 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
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    References listed on IDEAS

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    Cited by:

    1. 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).

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