Cell Transmission Model-Based Variable Speed Limit Control for Freeways
Bibliographic record
Abstract
The use of variable speed limit (VSL) control along freeway in an effort to improve bottleneck traffic flow is a technique that has been around for some time. In this study, the authors propose a simple yet very efficient VSL control model using the cell transmission model (CTM). Two modifications of the fundamental diagram (FD) of the CTM are proposed. The first permits one to model active bottleneck cell in which there is a capacity drop once feeding flow exceeds its capacity. The second modification permits variable free flow speeds for the cells operated with VSL control. In order to allow those modifications, the local demand-supply approach is adopted to change the boundary condition of the CTM, and then traffic density is predicted in the freeway cells. Speed dynamics is derived from a piecewise linear FD. Then the modified CTM is implemented in a freeway corridor Whitemud Drive, Edmonton with the model predictive control (MPC) approach. The analysis is carried out to a micro-simulation model VISSIM with a scenario where shock wave is present, and the micro-simulation model functions as a substitute for the real-world traffic system. Due to possibility of shockwave formation from the VSL operated cell, the authors have developed and implemented a time-space discrete model to detect queue tail during VSL control. This queue tail detection model is implemented to update storage capacity of freeway cell. This study reveals that in terms of mobility, VSL is effective mostly during congestion period.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".