Understanding Gap Crossing Decisions Across the Lifespan
Bibliographic record
Abstract
By 2063, it is expected that one in four Canadians will be over the age of 65 (Government of Canada, 2022), demonstrating the urgent need to understand how aging impacts safety in everyday environments. Older adults (OA) are disproportionately represented in pedestrian fatalities, in part due to age-related declines in visuomotor integration. Much of what is known about risky pedestrian behaviour is derived from simulator-based studies examining street crossing decisions, which have provided valuable insights into the perceptual, cognitive, and motor abilities that increase collision risk. However, our understanding of how people use optical information to guide behaviour when navigating closing gaps, and how this ability changes across the lifespan, remains limited. Furthermore, few studies have directly examined the cortical activity underlying gap crossing decisions, which may offer insight into why errors occur. Therefore, the purpose of this thesis was to take an integrative approach across two studies, to examine age-related differences in: 1) the use of visual information to guide speed adjustments while navigating closing gaps in virtual reality, and 2) cortical activation associated with decisions of gap passability. In Study 1, 15 younger adults (YA; 21.7 +/-1.3 yrs) and 15 OA (69.4 +/-3.8 yrs) completed a virtual path crossing task, by walking through an intersection while virtual pedestrians (VPs) approached from either side at various speeds, creating shrinking gaps. Participants were asked to adjust their own speed as necessary to avoid collisions. Results revealed that YA modulated the onset, magnitude, and rate of speed change based on the VP speed, demonstrating efficient use of visual cues to inform their behaviour. Alternatively, OA used a fixed “one solution fits all” approach, initiating speed changes with consistent timing and larger magnitudes across all conditions, placing them at greater risk in faster gap-closing scenarios. To better understand the cognitive demands underlying these behaviours, Study 2 involved a treadmill-based version of a similar task. Thirteen YA (22.5 +/- 3.9 yrs) and 14 OA (69.7 +/- 3.3 yrs) indicated whether approaching VP gaps were passable. Using functional near-infrared spectroscopy (fNIRS), cortical activity was measured during decision-making. Although both groups made similar decisions with comparable response times, OA exhibited greater and more sustained activation of the left dorsolateral prefrontal cortex, suggesting an increased need for cognitive resources compared to YA. This finding may reflect reduced neural efficiency or a compensatory response to maintain task performance. Together, these studies demonstrate that aging affects both the behavioural strategies and neural processes involved in path crossing decisions. Recognizing how older adults perceive, process, and respond to dynamic environments can inform the design of safer public spaces and targeted interventions that promote mobility, cognitive efficiency, and independence across the lifespan.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".