Master of Science (MSc)
Kinesiology and Physical Education
Faculty of Science
Dr. Michael Cinelli
The ability to perceive and react to visual information is critical for avoiding a collision with an approaching obstacle. The perception-action system undergoes a prolonged period of development and as a result, children make more last-minute locomotor adjustments than adults when avoiding stationary obstacles. The purpose of this thesis was to compare the avoidance behaviours of middle-aged children (10-12 years old) to young adults (YA) during a head-on collision course with an approaching virtual pedestrian (VP). Children (N=16, 10.8 0.75 years; 8 males) and YA (N=16, 22.94 2.08 years; 7 males) were immersed in a virtual environment using the HTC Vive Pro 2 head-mounted display. Participants were instructed to walk along an 8m pathway, towards a goal, while avoiding a collision with a VP who approached at one of three speeds: 0.8x, 1.0x, or 1.2x the participant’s average walking speed. During each trial, the VP would approach along the midline and steer to the left, right, or continue walking straight. Results revealed a significant difference in the onset of deviation between groups, with children (1.65 ± 0.17s) deviating later than YA (1.52 ± 0.10s). Additionally, children were more variable in their onset of deviation and time-to-contact. Findings from this study demonstrate children have similar avoidance behaviours to YA, as both groups successfully used perceptual information to determine how to avoid a collision. However, children had a later onset of deviation and greater variability in their avoidance behaviours than adults. These results suggest that although middle-aged children are able to successfully avoid collisions, they employ different avoidance strategies than adults. Therefore, by 10-12 years of age, children appear to not have fully developed adult-like perceptual-motor skills.
Hammill, Megan, "Collision avoidance strategies of middle-aged children and young adults in a virtual environment" (2023). Theses and Dissertations (Comprehensive). 2584.
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