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An empirical discourse on forecasting the use of autonomous vehicles using consumers’ preferences

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  • Saeed, Tariq Usman
  • Burris, Mark W.
  • Labi, Samuel
  • Sinha, Kumares C.

Abstract

Given many known and unknown uncertainties, it is hard to forecast reliably the mode choices, expected to prevail with autonomous vehicle (AV) technology; however, the key to getting some idea lies in understanding the preferences of end users. In this vein, a random parameters logit model is employed to study the consumers’ preferences in small- and medium-sized metropolitan areas, based on their travel behavior and household characteristics, socio-demographic features, awareness about AV technology and new travel choices, psychological factors, and built environment features. Most of the past studies hypothesize that due to a wide range of anticipated benefits, there would be increased use of AVs especially as a shared service where multiple travelers use the same AV concomitantly. However, the results from this study do not support the hypothesis that vehicle ownership will be an obsolete model at least during the early phase of transitioning to the self-driving era (when roads are expected to contain vehicles with and without human drivers). The findings of this study reveal key factors influencing consumer preferences and offer important insights to technology developers and service providers in understanding the ways consumers would like to use this technology and hence, defining the business model.

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  • 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).
    • Handle: RePEc:eee:tefoso:v:158:y:2020:i:c:s0040162520309562
    DOI: 10.1016/j.techfore.2020.120130
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    10. Hassan, Hany M. & Ferguson, Mark R. & Vrkljan, Brenda & Newbold, Bruce & Razavi, Saiedeh, 2021. "Older adults and their willingness to use semi and fully autonomous vehicles: A structural equation analysis11Revised manuscript prepared for publication at the special issue in Journal of Transport G," Journal of Transport Geography, Elsevier, vol. 95(C).
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    14. Su, Yu-Shan & Huang, Hsini & Daim, Tugrul & Chien, Pan-Wei & Peng, Ru-Ling & Karaman Akgul, Arzu, 2023. "Assessing the technological trajectory of 5G-V2X autonomous driving inventions: Use of patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
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    18. Kalakou, Sofia & Marques, Catarina & Prazeres, Duarte & Agouridas, Vassilis, 2023. "Citizens' attitudes towards technological innovations: The case of urban air mobility," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    19. McLeay, Fraser & Olya, Hossein & Liu, Hongfei & Jayawardhena, Chanaka & Dennis, Charles, 2022. "A multi-analytical approach to studying customers motivations to use innovative totally autonomous vehicles," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    20. Loes M. Derikx & Dea van Lierop, 2021. "Intentions to Participate in Carsharing: The Role of Self- and Social Identity," Sustainability, MDPI, vol. 13(5), pages 1-31, February.
    21. Ishant Sharma & Sabyasachee Mishra, 2023. "Ranking preferences towards adopting autonomous vehicles based on peer inputs and advertisements," Transportation, Springer, vol. 50(6), pages 2139-2192, December.
    22. Rungskunroch, Panrawee & Jack, Anson & Kaewunruen, Sakdirat, 2021. "Benchmarking on railway safety performance using Bayesian inference, decision tree and petri-net techniques based on long-term accidental data sets," Reliability Engineering and System Safety, Elsevier, vol. 213(C).

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