Collaborative Control Optimization on Reversible Lanes in Intersection Group under Intelligent Vehicle Infrastructure Cooperative System
Bibliographic record
Abstract
Based on the Intelligent Vehicle Infrastructure Cooperative System (IVICS), the paper firstly analyzes the operating characteristics of the intersection group under real-time reversible lanes from the capacity; secondly, the signal phase sequence and signal timing parameters of the intersection are designed, and the green wave control is designed based on the phase difference model. The scheme provides traffic flowing in this section with a continuous green light signal. Finally, taking the intersection of Yongle East Road in Wuxi, Jiangsu Province as an example, it optimizes and controls the green wave of the intersection group and verifies the effectiveness of the phase difference model using the evaluation indicators of the number of stops, green wave speed, traffic capacity, and saturation flow. The results show that the optimization of the number of stops is 9.5% and the vehicle speed is optimized by 5.3%. The intersection capacity and saturation flow are greatly improved.
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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".