On the development of an early warning safety monitor for articulated freight vehicles
Bibliographic record
Abstract
An early warning safety monitor (EWSM) that can detect and warn drivers of an impending dynamic instability is proposed to improve the operational safety of articulated freight vehicles. Development of an EWSM involves: (1) quantitative description of onset of roll and yaw instabilities via directly measurable dynamic response quantities; (2) on–line monitoring of dynamic state of the vehicle and analyses; and (3) generation of an early warning on impending instabilities. Directional dynamics of articulated vehicles are investigated to determine vital response parameters related to onset of rollover and jack–knife. Parametric sensitivity analyses are conducted to quantify the dependency of identified response parameters on various design and operating conditions, and to establish reliable response parameters related to onset of dynamic instabilities. The response parameters are further examined in view of ease of on–line acquisition and analyses, and stability criteria are established to identify impending roll and jack–knife instabilities. The design of an EWSM to generate an early warning of the impending instabilities is discussed such that the driver can undertake a corrective action in appropriate time.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".