Older Adults and Vehicle Design
Bibliographic record
Abstract
Vehicle designs that enhance the safety of older users should consider their needs in the design process. This study aimed to capture the ingress and egress strategies employed by older drivers in order to understand the relationship between balance and mobility and movement patterns. A sample of healthy older drivers ( n=15; aged 72.5±7.9) and those with mobility impairments ( n=17; aged 71.3±6.0) were captured entering and exiting four vehicle models using an adjustable vehicle mock-up. As well, semi-structured interviews and ride-a-longs were conducted with a sub-group ( n=7) of participants with mobility impairments in order to explore how bodily changes associated with aging impact vehicle usability. There were no significant differences across vehicle models in terms of ingress, but there were with egress. Particular movement strategies used by both groups are discussed with regard to safety. Through this movement analyses, such evidence can be used to develop innovations that inform the next generation of vehicles that consider the needs of older users.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".