A Hybrid Autonomous Intersection Management for Minimizing Delays Using Fuzzy Logic
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
This research proposes a fuzzy logic model to control intersection traffic flow to reduce average delay and increase throughput. To achieve this, vehicles and the controller exchange standard Vehicle-to-Infrastructure (V2I) messages to facilitate cooperation and utilization of the intersection. The proposed approach has been validated using the F1tenth_gym_ros simulation platform and on the Eclipse Mosaic platform. The simulation results show that the proposed approach outperforms the static controllers, 25s and 30s by 35.55% and 33.15%, respectively in terms of delay minimization; and 17.44% and 17.82% in terms of throughput, respectively. The proposed approach also outperforms the state-of-the-art controller by 16.18% in terms of delay minimization and 12.16% in terms of throughput. The results of the paired sample t-test also show that the proposed controller outperforms other controllers in both delay and throughput. This shows the potential to improve intelligent transportation systems using V2X technologies and smart intersection management.
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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