How Prior Experience With Automated Technology Impacts Perceptions of Autonomous Vehicles: A Case Study of Midwestern Farmers

Autonomous Vehicles are likely coming soon, and their impacts are unclear. While there is speculation that they will result in increased safety and efficiency, any effect will depend on uptake of the new technology. Existing transportation literature suggests that early adopters tend to be younger, wealthier, tech-savvy, urbanites. While most farmers are neither wealthy nor urbanites, the agriculture industry is on the leading-edge of driverless technologies, and many farmers have extensive experience with these technologies. Diffusion of innovation theory would suggest that these farmers would be more likely to fall into the "early-adopter" category, and be enthusiastic about the introduction of autonomous vehicles. Through a series of in-depth interviews with leaders in the agriculture industry in Nebraska (growers, ag technology software engineers, and product specialists), the research questions assumptions of technology diffusion theory and explores the impacts of experience with automated agricultural technology on perceptions of autonomous vehicles. By focusing on the experiences of those who have participated in the decision-making calculus of new automated technologies--rather than focusing exclusively on early speculative perceptions with inexperienced populations--this study offers a more holistic scope to understanding AV adoption decisions. The findings span four themes: technology adoption, misaligned expectations, challenges with the technology, and perceptions of the technology. Across all themes, the authors suggest that proactive policies addressing user expectations and behavior, and necessary infrastructure and are needed to ensure autonomous vehicles meet or exceed expectations without unintended consequences.


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 19p

Subject/Index Terms

Filing Info

  • Accession Number: 01763503
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-02695
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:03AM