Cyber-Physical Control for Energy-Saving Vehicle Following With Connectivity
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
This article aims to develop an optimal look-ahead control framework to maximize car-following fuel economy, while fulfilling requirements of intervehicle safety. Three original contributions make this work distinctive from the existing relevant literature. First, a model predictive fuel-optimal controller is constructed to optimize the vehicle speed and continuously variable transmission (CVT) gear ratio. The controller leverages state trajectories of the leading vehicle transmitted via Vehicle-to-Vehicle/Vehicle-to-Infrastructure (V2V/V2I) communication. How operating conditions affect the engine efficiency and CVT efficiency is explicitly taken into account. Second, the controller is sufficiently evaluated in a variety of traffic flows, such as cruising, urban, and highway-like driving, and is compared with a short-sighted alternative without V2V/V2I connectivity. Finally, we further demonstrate the advantages of the proposed scheme by a comparison with two existing benchmark controllers.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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