An overriding controller for vehicle lateral control system
Bibliographic record
Abstract
Driver assistance systems are expected to reduce the possibility of accidents caused by impaired or reckless driving. However, the current designs employed in some luxury cars are not entirely reliable and may even lead to more distraction of the driver. This paper presents the idea of an overriding controller for lateral control of a vehicle in a driver assistance system. In the proposed system, when the driver turns the steering wheel, the steer signal goes to a controller instead of the steering column of the car. The output of the controller is the actual value of steer signal which acts on the wheels. Since the driver might be in an abnormal situation while driving (due to drowsiness, fatigue, drunkenness, etc.), a second control structure is also presented in which the error signal, measured by exact sensors, is subtracted from the signal coming from the driver and resulting signal goes to the controller. Simulation results show the superiority of the proposed algorithms to the conventional driving. The stability robustness of the proposed control structures is shown using both structured singular value (μ) analysis and Monte-Carlo simulations.
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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".