A general rollover index for tripped and un-tripped rollovers on flat and sloped roads
Why this work is in the frame
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Bibliographic record
Abstract
In order to develop a rollover prevention system, it is essential to have a reliable index that properly indicates real-time rollover danger during vehicle maneuvers. The existing rollover indices are mainly for un-tripped rollovers and have limitations in detecting tripped rollovers. This study introduces a general rollover index (GRI) for the detection of rollover in both tripped and un-tripped cases and also on flat and sloped roads. Based on the lateral load transfer ratio, the proposed index is analytically derived in terms of measurable vehicle parameters and state variables. The general rollover index considers both lateral and vertical road inputs and thus can indicate tripped rollovers in the instance of curbs, soft soil or bumps. Sensitivity analysis for the proposed index is also provided to evaluate the effects of different vehicle parameters and different state variables on tripped and un-tripped rollovers. The introduced index can be used not only for the development of active rollover prevention systems, but also for rollover analysis and design of vehicles. The performance of the introduced general rollover index is validated through simulations using a high-fidelity CarSim model for a SUV.
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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) | 0.001 | 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