Slip-Aware Networked Vehicular Model and Control for Connected Automated Driving
Bibliographic record
Abstract
A slip-aware networked vehicle model is proposed to design a controller for cooperative adaptive cruise control and safety of the intended functionality (SOTIF) in connected automated driving systems. By sharing the magnitude of tire-level relative longitudinal speed (i.e., longitudinal slip ratio) in addition to the vehicle kinematic states, a novel slip-aware model is developed which utilizes an augmented state for communication to enhance the safety of the vehicular network. The proposed model is compelling in the sense that it requires minimal information sharing, while facilitating the formation of platoons which comprises of vehicles from various manufacturers. For controlling the overall system of networked vehicles, a time-delayed control based strategy is proposed and the stability of the model is discussed. Further simulation of the vehicle platoon control is carried out with the lead vehicle tracking a predefined trajectory and the follower vehicles satisfying various performance criteria.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".