Determinants of road user behavior at marked midblock crosswalks
Bibliographic record
Abstract
Drivers do not properly respect pedestrian priority at marked mid-block crosswalks. This study assesses pedestrians and vehicles behavior at such locations. Video recording at two mid-block crosswalks was used to analyze 12 crossing attributes and their correlations. Analysis of 884 pedestrians’ and 2087 vehicle’s data showed that all demographic and crossing related attributes affected the crossing speed and crossing time of pedestrians. The average crossing speed of pedestrians was 1.3 m/s. Only parked car at crosswalk affected the waiting and delay times of pedestrians. Lastly, gender and crossing related parameters were found to affect the accepted gap of pedestrians. The average accepted gap of pedestrians was 6.17 s. Vehicle speeds before, at, and after crosswalks were statistically different and had mean values of 19.38, 17.31, and 20.40 kmph, respectively. Driver yielding rate was found to be 40% and was statistically significantly influenced by gender, dressing style, crossing in-group, and rolling behavior.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".