Examination of Effect of Driver Population at Freeway Reconstruction Zones
Bibliographic record
Abstract
An investigation into the effect of the driver population factor on the capacities of long-term freeway reconstruction zones is presented. A major reconstruction project in Ontario, Canada, provided an opportunity to conduct the investigation. Comprehensive data on traffic, weather, and work activity were used. Three different analyses were conducted. These analyses compared mean capacity flows during different times of the day and days of the week to estimate the effect of the noncommuter driver population during weekdays and weekends. The study found that the effect of the driver population factor on the capacity of the reconstruction site was highly significant. On the basis of a factor of 1.0 for commuter traffic, a driver population factor of 0.93 was estimated for the afternoon peak period and a driver population factor of 0.84 was estimated for weekends. Also, the driver population factor is likely responsible for a capacity reduction on weekends compared with the capacity on weekdays. This capacity reduction was 12 percent in one direction of travel and 17 percent in the other direction. Both the driver population factors and the capacity reductions on weekends found in the study are considered conservative, given that these data were collected in April and early May and that there is a higher proportion of tourist drivers during the summer season at this site. Nonetheless, numbers are consistent with empirical observations from other studies and provide further guidance for use of the driver population factor in the 2000 Highway Capacity Manual procedures.
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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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".