Hybrid impulsive cooperative control of vehicle platoons with switching communication topology
Bibliographic record
Abstract
This study delves into the cooperative control challenges within vehicle platoons using delayed hybrid impulsive protocols. These protocols involve both time-dependent and state-dependent switching in communication topology, where each mode includes potentially destabilizing continuous dynamics. By employing the Lyapunov Krasovskii functional method alongside mode-dependent average dwell time and the Lyapunov Razumikhin technique, the paper establishes sufficient conditions. These conditions relate to impulsive strength, switching parameters, convex switching regions, and the operational time ratio between stable and unstable subsystems, ensuring global exponential stability under both switching regimes. Moreover, the research integrates gyroscopic and braking forces to address collision avoidance effectively. Numerical simulations for each switching type validate the theoretical findings, demonstrating their efficacy and applicability. Overall, this paper not only advances the theoretical understanding of cooperative control in vehicle platoons but also holds capability for enhancing the efficiency, safety, and scalability of autonomous transportation systems in practical settings.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".