Florida’s Automated Shuttle Service Explored Perceptions and Impacts of Level 4 Automated Shuttles Among People with Disabilities.
Gainesville, Florida, United States
Barriers and Facilitators of People with Disabilities in Accepting and Adopting Autonomous Shared Mobility Services
Summary Information
Deployment of Automated Vehicles (AVs) potentially offers safety benefits for drivers with and without disabilities. Specifically, integration of automated shared mobility services into transportation systems, including Automated Shuttles (AS), could further enhance the quality of life for People with Disabilities (PWD).
This study described the STRIDE A5 initiative, which promotes Accessible, Affordable, Available, Acceptable, and Adaptable transportation. This study had two specific goals to first quantify and qualify PWDs’ perceptions, values, beliefs, and attitudes before and after riding in a Level 4 AS according to Society of Automotive Engineers (SAE) Guidelines, in downtown Gainesville, FL, using an AV User Perception Survey (AVUPS) with a sample size of 42 participants. The second goal of this study was to build a multiple linear regression model of facilitators and barriers of AS from data collected in STRIDE D2 (Phase 1, with 50 elderly drivers), STRIDE A3 (Phase 2, with 51 younger and middle-aged drivers), and STRIDE A5 (phase 3, with 42 PWDs as mentioned earlier). The AS used in this study was fully electric and had fully automated driving capabilities.
METHODOLOGY
In the study of the AVUPS, researchers enlisted participants with assistance from various stakeholders, including centers and facilities for PWDs, as well as community hubs like libraries, churches, and recreation centers. Participants engaged in a 20-minute ride in an AS in a controlled, low-speed environment (≤15 mph) and completed the AVUPS both before and after their experience. Inferential statistic tests assessed differences between participants’ AV perceptions (i.e., AVUPS scores) before and after riding in the AS was conducted. Furthermore, the research team developed four multiple linear regression models aimed at predicting three key AVUPS parameters: Intention to Use, Perceived Barriers, and Well-being, alongside an Acceptance score. This analysis included both able-bodied drivers and PWDs, with a combined total of 143 participants.
FINDINGS
- Results from the AVUPS revealed that, after riding the AS, PWDs expressed statistically significant increased Intention to Use, increased Acceptance of AVs, and decreased Perceived Barriers compared to baseline before riding the AS.
- AVUPS results also found that PWDs’ ability to actively participate in the community (Well-being), did not change.
- Results from the regression models revealed that predictors of user Acceptance of AV technology encompass factors like optimism, ease of use, driver status, and race/ethnicity. These variables accounted for 30.7 percent points of the increase in Acceptance.
