Assessing the mobility benefits of proactive optimal variable speed limit control during recurrent and non-recurrent congestion
Bibliographic record
Abstract
Over the past few decades, several active traffic control methods have been proposed to improve freeway efficiency at bottleneck locations. Variable speed limit (VSL) is one of these effective controls. Previous studies have evaluated VSL control, but primarily during recurrent congestion only. This study focuses on evaluating the performance of VSL control for both recurrent and non-recurrent congestion. To assess the effectiveness of a previously proposed VSL control in a real-world situation, this study has three evaluation objectives: (1) examine the control performance when recurrent and (or) non-recurrent congestion occurs; (2) assess the effectiveness of the control when a queue encounters the VSL sign; and (3) consider the impact of system detection delay in VSL control. Comparative experiments for Whitemud Drive in Edmonton, Alberta, Canada, are simulated in the VISSIM platform, and traffic performance is compared among scenarios with and without control. The simulation results show that VSL improves mobility for both recurrent and non-recurrent congestion. The VSL control reduces total travel time, and improves total travel distance and total flow. Furthermore, it slows down the shockwave propagation speed, improves the average speed on most of the freeway segments, and reduces the duration of traffic recovery.
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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".