Fuzzy-Based Adaptive Cruise Controller with Collision Avoidance and Warning System
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
The paper presents a Fuzzy-based adaptive cruise control system with collision avoidance and collision warning (ACC/CA/CW). The proposed control scheme aims to improve driver's comfort while keeping him/her safe by avoiding possible collisions. Depending on inputs from both the driver and the installed sensors, the controller accelerates/decelerates the vehicle to keep its speed at the desired limit. In case of a possible collision, the controller decelerates (accelerates) the vehicle to prevent possible crash with the vehicle ahead (behind). Moreover, the controller issues visual and/or audio alerts for the driver in order to warn him/her in case of the need for applying an uncomfortable deceleration level and/or to warn the driver for risky situations where he/she might need to change the lane. Simulation results illustrate the robustness of the proposed system over various ranges of inputs.
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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 | 0.001 | 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 | 0.001 |
| 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