Older adults’ acceptance of fully automated vehicles: Effects of exposure, driving style, age, and driving conditions

Automated vehicles are anticipated to have benefits for older adults in maintaining their mobility and autonomy. These anticipated benefits can only be realized if this technology is accepted and thus used by older adults. However, it remains unclear how certain factors affect older adults’ acceptance of automated vehicles. This study investigated the extent to which older adults’ acceptance of fully automated vehicles are affected by exposure to automated vehicle technology (pre- vs. post-exposure), driving style (manual style relative to automated style), driving conditions (clear, rain, traffic), and age. Thirty-six older adults (M = 73.25, SD = 5.96) completed non-automated (manual) and fully automated driving scenarios under different driving conditions in a high-fidelity driving simulator. The fully automated driving scenarios were designed to be reliably driven by the system in a conservative driving style. Driving conditions included clear daytime, rain, and high-traffic. Pre- and post-exposure to the simulated fully automated driving experience, participants rated their comfort level with fully automated vehicles (FAVs). Additionally, after each driving condition, participants answered a validated questionnaire on their acceptance of the simulated fully automated experience for each respective driving condition. Age and driving style were found to have a significant effect on older adults’ acceptance of FAVs, with older age and greater dissimilarity of an individual’s manual driving style from the FAV’s driving style being associated with lower acceptance. The results suggest that if reliability of fully automated vehicles is ultimately ensured and is demonstrated to the older adults, their acceptance of fully automated vehicles is generally high, particularly if the FAV is operated in a style similar to their own.

• Record URL:
  https://doi.org/10.1016/j.aap.2020.105919
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0001457520317395
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00014575
• Supplemental Notes:
  • © 2020 Shabnam Haghzare, et al. Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
• Authors:
  • Haghzare, Shabnam
  • 0000-0001-7973-2586
  • Campos, Jennifer L
  • 0000-0002-7054-3946
  • Bak, Katherine
  • 0000-0003-3628-671X
  • Mihailidis, Alex
  • 0000-0003-2233-0919
• Publication Date: 2021-2

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 105919
• Serial:
  • Accident Analysis & Prevention
  • Volume: 150
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0001-4575
  • Serial URL: http://www.sciencedirect.com/science/journal/00014575

Subject/Index Terms

• TRT Terms: Acceptance; Aged drivers; Attitudes; Automobile driving; Autonomous vehicles; Driving simulators; Intelligent vehicles; Mobility
• Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01762097
• Record Type: Publication
• Files: TRIS
• Created Date: Jan 11 2021 11:08AM