Transportation-Related Human Factors in High-Altitude Regions: Review, Needs, and Novelties
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
The low pressure at high altitudes (above 2500 m) causes hypoxia (decreased oxygen) that affects people’s physiological and psychological characteristics. Specifically, hypoxia may affect the neural function of the brain, leading to severe cognitive deficits and a significant decline in memory function and attention. This article addresses the effect of human factors on transportation design and operation at high altitudes (HA), with some details on the Tibet-China region. Specifically, the paper first reviews the basic transportation-related concepts for high altitude, including oxygen and temperature levels, driver perception-reaction time, hazard perception, vehicle speed, and walking speed. Then, the transportation users affected by high altitudes are discussed, including drivers, pedestrians, cyclists, passengers, and others. Next, the impacts of human factors on highway design and operation for HA regions are discussed along with the research needs. Finally, recent innovations to address the challenges of HA transportation are presented, along with case studies comparing some human factors of the plateau and plain areas. This article represents a valuable reference for future research in HA regions to improve transportation design and safety.
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 | 0.000 | 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 it