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Building on the past to help prepare the workforce for the future with automated vehicles: A systematic review of automated passenger vehicle deployment timelines

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  • Agrawal, Shubham
  • Schuster, Amy M.
  • Britt, Noah
  • Mack, Elizabeth A.
  • Tidwell, Michael L.
  • Cotten, Shelia R.

Abstract

A variety of stakeholders have put forth automated vehicle (AV) deployment timeline predictions over the past decade. To synthesize these predictions, we performed a systematic literature review of past and current AV deployment timeline predictions in the United States from different stakeholder groups, including private stakeholders, government organizations, and research organizations. Our analysis revealed that none of the AV mass deployment timelines from any stakeholder group have been met. It also shows discrepancies between timelines put forth by private and public stakeholders, with the private sector being more optimistic in their predictions. Accurate timelines are needed so regulators are able to create appropriate public policies and comprehensive budgets, and private stakeholders can make better informed decisions. More specifically, the mass deployment of AVs is anticipated to affect many transportation-related jobs which reinforces the importance of accurate AV deployment timelines to prepare the workers who may be displaced and for the development of workforce education and training initiatives.

Suggested Citation

  • Agrawal, Shubham & Schuster, Amy M. & Britt, Noah & Mack, Elizabeth A. & Tidwell, Michael L. & Cotten, Shelia R., 2023. "Building on the past to help prepare the workforce for the future with automated vehicles: A systematic review of automated passenger vehicle deployment timelines," Technology in Society, Elsevier, vol. 72(C).
    • Handle: RePEc:eee:teinso:v:72:y:2023:i:c:s0160791x2200327x
    DOI: 10.1016/j.techsoc.2022.102186
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    Cited by:

    1. Leon, Ramona Diana, 2023. "Employees’ reskilling and upskilling for industry 5.0: Selecting the best professional development programmes," Technology in Society, Elsevier, vol. 75(C).
    2. Schuster, Amy M. & Agrawal, Shubham & Britt, Noah & Sperry, Danielle & Van Fossen, Jenna A. & Wang, Sicheng & Mack, Elizabeth A. & Liberman, Jessica & Cotten, Shelia R., 2023. "Will automated vehicles solve the truck driver shortages? Perspectives from the trucking industry," Technology in Society, Elsevier, vol. 74(C).

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