Field Evaluation of Automatic Pedestrian Detectors in Cold Temperatures
Bibliographic record
Abstract
The equitable accommodation of pedestrians is critical in transportation engineering and planning. Major concerns over the use of push buttons to activate pedestrian signals have been raised in many jurisdictions because elderly pedestrians and certain physically impaired pedestrians experience difficulty using push buttons, even when the push button is placed in a convenient and standard location. This paper presents the results of an analysis of the performance of three commercially available curbside automatic pedestrian detectors (APD)—a passive infrared and stereovision curbside detector, a passive infrared curbside detector, and a microwave detector—in the field as a function of weather, temperature, and temporal variations at signalized intersections during the winter months at temperatures ranging from −34°C (−29°F) to 0°C (32°F). The results were classified according to detector sensitivity, which referred to the percentage of pedestrian crossings detected successfully, and detector selectivity, which referred to the percentage of activations triggered by actual pedestrians, instead of false activations from vehicle movement, trees in the wind, or other causes. From a sample of 8,225 detections at two sites, the results revealed that the three APDs were generally sensitive at sending valid pedestrian calls, but selectivity rates remained less than 50%. Under all conditions and of all APDs analyzed, the infrared detector consistently had the highest sensitivity and lowest selectivity; the infrared–video detector had the second-highest sensitivity and the highest selectivity; and the microwave detector had the lowest sensitivity and the second-highest selectivity.
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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 | 0.011 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".