Hybrid Approach for Stabilizing Large Time Delays in Cooperative Adaptive Cruise Control with Reduced Performance Penalties
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Bibliographic record
Abstract
Cooperative adaptive cruise control (CACC) is a smart transportation solution that can mitigate traffic jams and improve road safety. CACC performance is heavily impacted by communication time delay; moreover, control theory solutions generally compromise control performance by tuning control gains in order to maintain plant stability. We propose a control-machine learning hybrid approach called deep time delay filter (DTDF). DTDF predicts the present (un-delayed) car states given time delayed versions. We successfully train a neural network for the DTDF method and use a physical testbed to show that DTDF can mitigate the effects of constant time delays as large as 5s while maintaining superior control performance compared to that of a baseline control algorithm.
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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