Study on Vehicle Fuel Consumption and Exhaust Emissions Based on a New Viscous Macroscopic Traffic Flow Model
Why this work is in the frame
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Bibliographic record
Abstract
Based on a conserved higher-order traffic flow model (CHO model), we propose a new viscous macroscopic traffic flow model taking into account the diffusion effect in traffic. The model can reasonably smooth the shock wave so that the acceleration is maintained in a reasonable range. To balance the computational efficiency and accuracy, this viscous macroscopic traffic flow model is integrated with the microscopic vehicle fuel consumption and emission models to estimate vehicle fuel consumption and exhaust emissions. The local discontinuous Galerkin (LDG) method is used to solve the viscous model, and the simulation results are inputted into the microscopic models to calculate vehicle fuel consumption and exhaust emissions. Numerical results illustrate that the proposed viscous model is reasonable and that the designed scheme is feasible and effective. Moreover, we provide concrete suggestions for controlling vehicle fuel consumption and exhaust emissions.
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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 | 0.000 | 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