Effect of High-Altitude Environment on Driving Safety: A Study on Drivers’ Mental Workload, Situation Awareness, and Driving Behaviour
Bibliographic record
Abstract
This study aims to analyze the effect of high-altitude environment on drivers’ mental workload (MW), situation awareness (SA), and driving behaviour (DB), and to explore the relationship among those driving performances. Based on a survey, the data of 356 lowlanders engaging in driving activities at Tibetan Plateau (high-altitude group) and 341 lowlanders engaging in driving activities at low altitudes (low-altitude group) were compared and analyzed. The results suggest that the differences between the two groups are noteworthy. Mental workload of high-altitude group is significantly higher than that of low-altitude group, and their situation awareness is lower significantly. The possibility of risky driving behaviours for high-altitude group, especially aggressive violations, is higher. For the high-altitude group, the increase of mental workload can lead to an increase on aggressive violations, and the situation understanding plays a full mediating effect between mental workload and aggressive violations. Measures aiming at the improvement of situation awareness and the reduction of mental workload can effectively reduce the driving risk from high-altitude environment for lowlanders.
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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 | 0.001 |
| 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) | 0.001 | 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".