The effects of physical motion cues on driving performance in older and younger adults
Bibliographic record
Abstract
• Driving uses complex visual and vestibular (physical motion) inputs for vehicle control. • Age affects vestibular sensitivity and multisensory processing during driving. • Effects of specific physical motion types on driving performance over the lifespan remain unclear. • Participants completed driving tasks with no motion, yaw only, or full 6-DOF motion. • Motion effects were strongest between no motion and full motion; more motion-related effects in older than younger adults. Driving is a multisensory task relying on inputs from our sensory systems, including vestibular and somatosensory (i.e. physical motion cues). However, the effects of different physical motion parameters (translations and rotations) on driving performance during simulated realistic conditions is not well understood. Further, there are known age-related changes to vestibular function and multisensory integration, which may affect driving differently in older versus younger adults. This study used a high-fidelity driving simulator to investigate whether different physical motion cues (from no motion, to yaw rotation, to 6-degrees of freedom motion) affect driving performance, and whether these effects differ between older and younger adults. Forty-five younger adults (18–35 years, 26 females, 19 males) and 40 older adults (65 + years, 19 females, 21 males) completed driving scenarios under one of three motion conditions: no motion (fixed-base), yaw rotation (turntable), or full motion (turntable and hexapod). Scenarios included straight roads, turns, and hills, chosen to introduce specific types of physical motions. Driving performance measures included mean speed, speed variability, steering reversals, and variability in acceleration (longitudinal and lateral). Motion-related effects were most pronounced between no motion and full motion conditions. However, for scenario elements involving pitch (e.g., hills), the largest effects were between yaw rotation and full motion conditions. Older adults exhibited more motion-related effects than younger adults, though not consistently across all elements or measures. These findings enhance understanding of how physical motion influences driving behavior, with potential implications for vehicle design and simulator research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".