Pedestrians' Normal Walking Speed and Speed When Crossing a Street
Bibliographic record
Abstract
Walking speed is a key input for various traffic engineering applications. This paper presents the results of research conducted over 18 months to understand the difference between the normal and the crossing walking speeds of pedestrians at signalized intersections and to determine the effect of seasonality on walking speed, taking into account age and gender. For the purposes of this paper, normal walking speed is the speed at which pedestrians walk without needing to cross an intersection, and crossing walking speed is that at which pedestrians walk when they are crossing a signalized intersection. The research found that in all cases the normal walking speed is less than the crossing walking speed. It also found that younger pedestrians walk faster than older pedestrians, regardless of the season and gender, and females walk slower than males, regardless of the season and age. Furthermore, both younger and older pedestrians have a greater normal walking speed in summer than in winter but a lower crossing walking speed in winter than in summer. In addition, the research also found that by use of a design value of 1.2 m/s (4.0 ft/s), as recommended in the current Manual of Uniform Traffic Control Devices, nearly two-thirds of older pedestrians would be excluded in the design process on the basis of their normal walking speed and about 40% would be excluded on the basis of their crossing walking speed. The design value of 1.2 m/s (4.0 ft/s) excludes nearly one-third of younger pedestrians on the basis of their normal walking speed and about 10% on the basis of their crossing walking speed.
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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 | 0.018 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".