Variable Speed Limit Control Method of Freeway Mainline in Intelligent Connected Environment
Bibliographic record
Abstract
Freeway is an important component of transportation system. Bottleneck areas on freeway reduce driving safety and traffic efficiency. The development of intelligent connected technology provides a new idea for traffic management. In order to alleviate traffic congestion on the freeway bottleneck area, this paper proposes a variable speed limit (VSL) control method in intelligent connected environment. In this paper, the METANET model is improved by combining intelligent connected environment and VSL control theory. The total traffic capacity (TTC), total travel time (TTT), and total speed difference (TSD) are used to build multiobjective function. The microsimulation at SUMO by using the data from PeMS is employed as a case study to validate the proposed model. The results show that the VSL online control method in intelligent connected environment has better control effect. And the improvement is more obvious with increasing penetration rate of intelligent connected vehicle (ICV).
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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".