The feasibility of a virtual reality hazard perception and gap acceptance task for older adults to improve pedestrian safety

Despite comprising 18% of the Australian population, older adults account for 40% of pedestrian fatalities. It has been proposed that age-related decline in perceptual, cognitive, and physical function contributes to these deaths. To date, the important safe street-crossing skills of hazard perception and gap acceptance have been understudied in an older population and would benefit from being examined using immersive technologies, such as virtual reality (VR). Using a mixed-method design and adopting human factors and ergonomics principles, this study determined the feasibility and acceptability of a protocol using a VR pedestrian street-crossing task (VR-PSCT), including the presence of cybersickness. Data were collected from 14 younger adults (25–45 years) and 14 older adults (> 60 years). Participants completed tasks that measured visual perceptual capacity (e.g., visual acuity), cognitive capacity (e.g., visuospatial attention), and physical capacity (e.g., balance). Hazard perception and gap acceptance were measured using a VR headset where a series of 360° video clips captured from real-world pedestrian situations were presented. Hazard perception response time did not differ between older and younger adults, nor did their hazard perception accuracy scores; however, gap acceptance response time was significantly slower for older adults compared with younger adults. The older adults reported that the protocol length was too long and induced high levels of fatigue. The VR-PSCT was well tolerated, with some instances of mild cybersickness and motor instability for the older adults. This study has established the feasibility of our VR-PSCT task and protocol and highlighted several user-centered modifications needed to conduct further testing with a larger cohort of older adults. By using the latest immersive technologies, we can obtain a greater understanding of older adult pedestrian behaviors and the factors that predict these behaviors.