Traffic Behavior and Compliance to Truck-Restriction Policies on Four-Lane Rural Freeways
Bibliographic record
Abstract
This study examined the overall traffic characteristics and truck compliance behavior under truck-lane-restriction and differential speed limit policies on an 18-mile rural four-lane elevated segment of I-10. Traffic data was collected at four different sites along the freeway corridor and analyzed using statistical methods. The results show that the overall traffic speed decreased as the percentage of trucks in the traffic stream increased and that trucks had the tendency to increase their speed in the absence of other types of vehicles. The results also showed a compliance rate of 60% to 80% to the truck-lane restriction. Linear regression models showed significant differences in speed between the right and left lane at each site, implying some compliance to the reduced speed limit by trucks. In addition, the pairwise comparison results indicated that for mixed traffic conditions truck speeds were within a 5-mph range above the imposed truck speed limit on the right lane and 5 mph above the truck speed limit on the left lane. The study concluded that the truck compliance to both policies seemed somewhat acceptable, but higher compliance rates could be attained by increasing the level of enforcement along the corridor.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".