Estimating Safety Effects of Green-Man Countdown Devices at Signalized Pedestrian Crosswalk Based on Cellular Automata
Bibliographic record
Abstract
Safety effects of Green-Man Countdown Device (GMCD) at signalized pedestrian crosswalks are evaluated. Pedestrian behavior at GMCD and non-GMCD crosswalks is observed and analyzed. A microsimulation model is developed based on field observations to estimate safety performance. Simulation outputs allow analysts to assess the impacts of GMCD at various conditions with different geometric layout, traffic and pedestrian volumes, and the green time. According to simulation results, it is found that the safety impact of GMCD is affected by traffic condition as well as different time duration within green-man signal phase. In general, GMCD increases average walking velocity, especially during the last few seconds. The installation of GMCD improves safety performance generally, especially at more crowded crossings. Conflict severity is increased during last 10 s after GMCD installation. Findings from this study suggest that the current practice, which is to install GMCD at more crowded crosswalks or near the school zone, is effective. Moreover, at crosswalks with GMCD, longer all red signal phase is suggested to improve pedestrian safety during intergreen 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 | 0.000 | 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".