Bibliographic record
Abstract
The paper examines typical vehicle dynamics models used for the design of car-trailer active safety systems, including active trailer braking and steering. A linear 3 degree-of-freedom (DOF), a nonlinear 4 DOF and a nonlinear 6 DOF car-trailer model are generated. Then, these models are compared with a car-trailer model developed with the commercial software package, CarSim. The benchmark investigation of the car-trailer models is carried out through examining numerical simulation results obtained in two emulated tests, i.e., a single lane-change and a Fishhook maneuver. In the vehicle modeling, a mathematical model of a tire with flexible sidewalls is included to account for transient tire forces. Steady-state aerodynamic forces are included in these models. The deviation of the model dynamic responses, e.g., the variation of the articulation angle between the car and trailer, is discussed. With the benchmark investigation, the car-trailer models in terms of fidelity, complexity, and applicability for active safety system design are addressed.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".