Changing Lanes in a Simulator: Effects of Aging on the Control of the Vehicle and Visual Inspection of Mirrors and Blind Spot
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to examine lane change strategies in active younger and older drivers. Visual inspection of mirrors and the blind spot and the control of the vehicle were documented in a simulator environment. METHODS: Younger (n = 10, 21-31 years) and older (n = 11, 65-75 years) active drivers drove through a continuous simulated environment including urban and rural sections. The scenario included events where, to negotiate a secure lane change, the driver needed to look at 3 regions of interest (ROI): (1) the rearview mirror, (2) the left side mirror, and (3) the left blind spot. The lane change maneuvers were necessary to avoid a vehicle parked halfway in the rightmost lane that was partially or completely blocking the lane or for overtaking a slower moving vehicle. RESULTS: Compared with younger drivers, older drivers showed a reduced frequency of visual inspection toward the rearview mirror and the blind spot. Also, though the older drivers showed a constant frequency of visual inspection across the 2 types of driving maneuvers, the younger drivers increased their frequency of inspection when overtaking a slower vehicle. Control of the car was mostly similar for both groups. CONCLUSION: A better knowledge of the drivers' visual search strategies when changing lanes could help in identifying suboptimal strategies at-risk of causing crashes and also serves to develop retraining programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it