Older Driver’s Perceptions Before and After Riding in an Autonomous Shuttle

PURPOSE: Autonomous shuttles (AS) may support community mobility of young-old (65-74 years old) and old-old adults (>75 years old). However, they may differ in their perceptions of AS, which may deter their adoption practices [1,2]. This study compared young-old and old-old drivers’ perceptions of an AS before and after riding in the AS.

METHOD: A pre-post experimental design exposed 27 young-old and 27 old-old drivers to an AS. All drivers had a valid driver’s license and did not display signs of cognitive impairment (i.e., no MoCA score = <18) [3].

DESIGN: The AS operated on a closed-loop route in Gainesville, Florida at ∼10mph for 10 minutes. Participants completed the Automated Vehicle User Perception Survey (AVUPS) [4] before and after riding the AS. A one-way ANOVA assessed differences in AVUPS domain scores (i.e., Intention to Use, Perceived Barriers, Well-being, and Acceptance) at baseline. A two-way mixed ANOVA quantified the effects of group (young-old vs. old-old), time (pre vs. post exposure), and group-by-time interaction. The Benjamini-Hochberg procedure was used to control for multiple comparisons.

RESULTS: The one-way ANOVAs revealed no differences at baseline for AVUPS scores between the age groups (p’s >.05). Neither the group-by-time interaction nor the group effects, for either AVUPS domain, was significant (p >.05). However, a time effect was observed (p <.05). Compared to baseline, older drivers’ Intention to Use and Acceptance of the AS increased after riding the AS.

CONCLUSION: Older drivers improved their Intention to Use and Acceptance of the AS post exposure. Industry partners and policymakers may consider exposing older drivers to AS to facilitate adoption practices and widespread deployment.

IMPACT STATEMENT: The AS can support older drivers’ community mobility, and hence their health and independence; and may be incorporated by occupational therapists, in a comprehensive community mobility plan for drivers who no longer drive, need a driving cessation plan, or prefer to rideshare.

References

Haghzare, S., Campos, J. L., Bak, K., & Mihailidis, A. (2021). Older adults’ acceptance of fully automated vehicles: Effects of exposure, driving style, age, and driving conditions. Accident Analysis & Prevention, 150, 105919. https://doi.org/10.1016/j.aap.2020.105919

Classen, S., Mason, J., Hwangbo, S. W., Wersal, J., Rogers, J., & Sisiopiku, V. (2021). Older drivers’ experience with automated vehicle technology. Journal of Transport & Health, 22, 101107. https://doi.org/10.1016/j.jth.2021.101107

Nasreddine, Z. S., Phillips, N. A., Bedirian, V., Charbonneau, S., Whitehead, V., Collin, I., Cummings, J. L., & Chertkow, H. (2005). The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool for Mild Cognitive Impairment. Journal of the American Geriatrics Society, 53(4), 695–699. https://doi.org/10.1111/j.1532-5415.2005.53221.x

Mason, J., Classen, S., Wersal, J., & Sisiopiku, V. (2021). Construct validity and test-retest reliability of the automated vehicle user perception survey. Frontiers in Psychology, 12, 61. https://doi.org/10.3389/fpsyg.2021.626791