Approach speed m s
approach_speed_m_s
Approach speed converted to metres per second
Scores if within ±1% of the reference value.
Calculates the yellow change interval for a traffic signal approach using the metric ITE kinematic equation. The template converts approach speed to m/s, applies perception-reaction time, deceleration rate, and road grade, then reports both raw and one-decimal rounded yellow interval.
with-tool: The model is given an executable Python calculator script.
One template produces many comparable benchmark tasks while keeping the scoring contract fixed.
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The reusable contract shown on this page.
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An archetype and site context are sampled.
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Inputs may be hidden at harder tiers.
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The model responds with the declared outputs.
Inputs the model receives, and the outputs it is scored on.
4 inputs
Included directly in every task prompt.
Approach speed kmh
approach_speed_kmh
Approach speed
Perception reaction time
perception_reaction_time_s
Driver perception-reaction time
Deceleration rate
deceleration_rate_m_s2
Comfortable deceleration rate
Visible in easier tasks and withheld in one or more harder tiers.
Road grade pct
road_grade_pct
Approach grade, positive for upgrade and negative for downgrade
Hidden at hard difficulty.
4 outputs
approach_speed_m_s
Approach speed converted to metres per second
Scores if within ±1% of the reference value.
grade_adjusted_denominator
Denominator in the metric ITE stopping term
Scores if within ±3% of the reference value.
yellow_interval_s
Calculated yellow interval
Scores if within ±3% of the reference value.
yellow_interval_rounded_s
Yellow interval rounded to one decimal place
Scores if within ±1% of the reference value.
Each template is sampled at three tiers. Harder tiers may hide inputs, forcing the model to infer them from the scenario description.
All inputs given
Urban approach with all kinematic inputs given
All inputs given
Mixed speed approaches and grade effects
Some inputs hidden
Grade value hidden in the site context
Hidden inputs
Prompt replacement text
Use the approach grade implied by {{ archetype.description }}.
The exact instruction and parameter contract used to generate this task, pinned to the published library source.
/workspace
Teal lines show Jinja input conditions, not task visibility policy. A line renders only when that input or tool is visible.
1You are a senior traffic signals engineer calculating a yellow change interval.2 3## Problem4 5Calculate the yellow interval duration for the signal approach using the metric ITE kinematic equation.6 7## Given8 9| Parameter | Value | Unit |10|-----------|-------|------|11| Approach speed | {{ approach_speed_kmh }} | km/h |12| Perception-reaction time | {{ perception_reaction_time_s }} | s |13| Deceleration rate | {{ deceleration_rate_m_s2 }} | m/s2 |14{% if road_grade_pct is defined %}15| Road grade | {{ road_grade_pct }} | % |16{% endif %}17{% if archetype_description is defined %}18 19### Site Context20 21{{ archetype_description }}22{% endif %}23 24{% if tool_available %}25## Available Tool26 27A yellow interval calculation tool is available at `/workspace/yellow-interval-calculation_calc.py`. Run it with:28 29```bash30python3 /workspace/yellow-interval-calculation_calc.py --help31```32{% endif %}33 34## Required35 36Calculate:37 381. Approach speed in m/s392. Grade-adjusted denominator in the stopping term403. Yellow interval in seconds414. Yellow interval rounded to one decimal place42 43## Constraints44 45- Convert speed using `v_m_s = v_km_h / 3.6`.46- Use the metric ITE form `Y = t + v / (2a + 19.62G)`.47- `G` is grade as a decimal, positive for upgrade and negative for downgrade.48- Round the final signal timing value to one decimal place.49 50## Output Format51 52Show your working in Markdown. At the end, include a JSON block with exactly these keys:53 54```json55{56 "approach_speed_m_s": <numeric_value>,57 "grade_adjusted_denominator": <numeric_value>,58 "yellow_interval_s": <numeric_value>,59 "yellow_interval_rounded_s": <numeric_value>60}61```62 63Write your complete solution to `/workspace/output.md`.64 Each generated task is drawn from one of these realistic scenario bands.
Site contexts ground each scenario in a real locale the model can use to infer hidden values.
urban_arterial
Urban arterial signal approach
high_speed_approach
High-speed signalised approach
steep_grade_approach
Signal approach with material grade effect
hilly-arterial-steep-grade-approach-preview — hard difficulty, some inputs hidden.
Signal approach with material grade effect. hilly-arterial. Required outputs: approach_speed_m_s, grade_adjusted_denominator, yellow_interval_s, yellow_interval_rounded_s
Scenario context and visible inputs.
Executable tool: yellow-interval-calculation_calc.py
Inputs withheld at this difficulty.
Road grade pct
road_grade_pct
Stand-in text in the prompt
Use the approach grade implied by {{ archetype.description }}.
The scored JSON answer schema.
{
"approach_speed_m_s": <number>,
"grade_adjusted_denominator": <number>,
"yellow_interval_s": <number>,
"yellow_interval_rounded_s": <number>
}