Automated Vehicles and Older Drivers in Canada

As seniors represent a growing proportion of the driving population, research about how automated vehicles can help improve older driver safety and mobility is highly relevant. This paper examines the knowledge, attitudes and perceptions of older drivers towards limited self-driving vehicles (LSDVs), and how these variables can influence the likelihood that they will rely on this technology. The study includes data from a previous national survey (N = 2662) about automated vehicle technology, with new analyses to test hypothetical models using structural equation modeling. Results of the first model were confirmed and built upon with a second more complex model that incorporated the construct “behavioral adaptation.” Focus groups with older drivers were also conducted (N = 38) to help reveal nuances in older drivers' knowledge, attitudes, perceptions, and behaviors regarding this technology. Survey results demonstrated that feelings of safety and knowledge about LSDVs are positively related to perceived ease of use and adoption of the technology. The positive association between safety and perceived ease of use was further highlighted when comparing responses of older drivers to those of younger age groups, as older drivers were significantly less likely to agree that LSDVs were easy to use and were significantly less agreeable about feeling safe using them. Focus groups results confirmed that safety and knowledge of LSDVs are essential to the likelihood of adopting this technology, and revealed a high receptivity among older drivers to educational strategies and tools to increase their knowledge of LSDVs. Implications for educational strategies and safety benefits for older drivers are discussed. Results provide insight into strategies to encourage the early adoption of automated vehicles by older drivers and facilitate a safer transition towards automated vehicles that is led by a cohort of safety-conscious drivers.


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  • Accession Number: 01714115
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Aug 7 2019 3:05PM