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Examining motivations for owning autonomous vehicles: Implications for land use and transportation

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  • Tao, Tao
  • Cao, Jason

Abstract

Illustrating the associations between built environment characteristics and autonomous vehicle (AV) ownership helps policymakers understand where AVs emerge first and their impacts on society. However, few studies have addressed interest in AV ownership from the spatial perspective. Using regional travel survey data from the Twin Cities, we applied the gradient boosting decision tree method to test three hypotheses (diffusion of innovation, efficiency, and modal substitution) underlying the relationships between respondents' interest in owning AVs and its correlates. Results showed that the innovation-diffusion hypothesis dominates the motivations for owning AVs, followed by preference for efficiency and then modal substitution. However, its associations with built environment variables suggest more of preference for efficiency than of diffusion of innovation and modal substitution. Population density, road connectivity, and land use entropy are negatively associated with the interest. The results provide suggestions to address the externalities of AVs in different areas.

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  • Tao, Tao & Cao, Jason, 2022. "Examining motivations for owning autonomous vehicles: Implications for land use and transportation," Journal of Transport Geography, Elsevier, vol. 102(C).
    • Handle: RePEc:eee:jotrge:v:102:y:2022:i:c:s0966692322000849
    DOI: 10.1016/j.jtrangeo.2022.103361
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    1. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    2. Mokhtarian, Patricia L. & Salomon, Ilan, 2001. "How derived is the demand for travel? Some conceptual and measurement considerations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(8), pages 695-719, September.
    3. William P. Anderson & Lata Chatterjee & T.R. Lakshmanan, 2003. "E‐commerce, Transportation, and Economic Geography," Growth and Change, Wiley Blackwell, vol. 34(4), pages 415-432, September.
    4. Robert W. Wassmer, 2006. "The Influence of Local Urban Containment Policies and Statewide Growth Management on the Size of United States Urban Areas," Journal of Regional Science, Wiley Blackwell, vol. 46(1), pages 25-65, February.
    5. 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).
    6. Saeed, Tariq Usman & Burris, Mark W. & Labi, Samuel & Sinha, Kumares C., 2020. "An empirical discourse on forecasting the use of autonomous vehicles using consumers’ preferences," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    7. Felix Becker & Kay W. Axhausen, 2017. "Literature review on surveys investigating the acceptance of automated vehicles," Transportation, Springer, vol. 44(6), pages 1293-1306, November.
    8. Zhen, Feng & Du, Xiaojuan & Cao, Jason & Mokhtarian, Patricia L., 2018. "The association between spatial attributes and e-shopping in the shopping process for search goods and experience goods: Evidence from Nanjing," Journal of Transport Geography, Elsevier, vol. 66(C), pages 291-299.
    9. Aggelos Soteropoulos & Martin Berger & Francesco Ciari, 2019. "Impacts of automated vehicles on travel behaviour and land use: an international review of modelling studies," Transport Reviews, Taylor & Francis Journals, vol. 39(1), pages 29-49, January.
    10. Prateek Bansal & Kara M. Kockelman, 2018. "Are we ready to embrace connected and self-driving vehicles? A case study of Texans," Transportation, Springer, vol. 45(2), pages 641-675, March.
    11. Mokhtarian, P.L., 2005. "Travel as a desired end, not just a means," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 93-96.
    12. Daniel W. Apley & Jingyu Zhu, 2020. "Visualizing the effects of predictor variables in black box supervised learning models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(4), pages 1059-1086, September.
    13. Nodjomian, Adam T. & Kockelman, Kara, 2019. "How does the built environment affect interest in the ownership and use of self-driving vehicles?," Journal of Transport Geography, Elsevier, vol. 78(C), pages 115-134.
    14. Xu, Yiming & Yan, Xiang & Liu, Xinyu & Zhao, Xilei, 2021. "Identifying key factors associated with ridesplitting adoption rate and modeling their nonlinear relationships," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 170-188.
    15. Ding, Chuan & Cao, Xinyu (Jason) & Næss, Petter, 2018. "Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 107-117.
    16. Peng Jing & Gang Xu & Yuexia Chen & Yuji Shi & Fengping Zhan, 2020. "The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review," Sustainability, MDPI, vol. 12(5), pages 1-26, February.
    17. Pettigrew, Simone & Dana, Liyuwork Mitiku & Norman, Richard, 2019. "Clusters of potential autonomous vehicles users according to propensity to use individual versus shared vehicles," Transport Policy, Elsevier, vol. 76(C), pages 13-20.
    18. White, Lee V. & Sintov, Nicole D., 2017. "You are what you drive: Environmentalist and social innovator symbolism drives electric vehicle adoption intentions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 94-113.
    19. Yang, Linchuan & Ao, Yibin & Ke, Jintao & Lu, Yi & Liang, Yuan, 2021. "To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults," Journal of Transport Geography, Elsevier, vol. 94(C).
    20. Yang, Jiawen & Cao, Jason & Zhou, Yufei, 2021. "Elaborating non-linear associations and synergies of subway access and land uses with urban vitality in Shenzhen," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 74-88.
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    2. Lixun Liu & Yujiang Wang & Robin Hickman, 2023. "How Rail Transit Makes a Difference in People’s Multimodal Travel Behaviours: An Analysis with the XGBoost Method," Land, MDPI, vol. 12(3), pages 1-23, March.

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