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Sherrilene Classen

Dr. Classen receives Dean’s Citation Award 2023

Autonomous vehicles (AVs) may benefit the health and safety of drivers across the driving lifespan, but perceptions of drivers are not known. Lived experiences of drivers exposed to AVs in combination with surveys, can more accurately reveal their perceptions.

Aging Matters: Transportation tests county’s seniors

To drive or not to drive? That is the question confronting many people as they age, especially those who live in southern states like Florida, where a car-centric culture makes it more difficult to get around when one can’t, won’t, or is unable to continue driving.

Accelerating Innovation in Autonomous Ride Sharing through Diversity of Thought

During a session on “Accelerating Innovation Through Diversity of Thought” at XPONENTIAL 2022, attendees discussed how diversity and inclusiveness impact the uncrewed systems community, the technology we design, and how our systems integrate into society. Sherrilene Classen, Professor and Chair, University of Florida, Department of Occupational Therapy, presented her research findings on how autonomous vehicles can be designed to support populations with limited mobility and how uncrewed systems can be equitably integrated into society.

Webinar: What do Drivers Really Think about Autonomous Vehicles?

The deployment of autonomous vehicle (AV) technologies may hold important health and safety benefits for drivers across the driving lifespan. However, such benefits can materialize only if transportation users are willing to embrace the emerging technologies. Earlier studies document a wide variance in acceptance practices, based solely on surveys of drivers. This research used a combined approach of surveys and lived experiences of drivers engaging with AV technologies to examine technology acceptance and adoption of AV technologies. The webinar summarizes findings from the analysis of younger and middle-aged drivers’ perceptions of AVs before and after a) “driving” an interactive high-fidelity RTI driving simulator, in Level 4 autonomous mode, and b) riding in an autonomous shuttle (AS). Moreover, it discusses predictive models of facilitators and barriers for AV acceptance built from data collected from younger and middle-aged drivers (N=106) and older drivers (N=104). The findings reveal important foundational information about driver acceptance, their intention to use AVs, barriers to AV technology, and well-being related to AV technology across the driving lifespan.