Ground Truth Traffic Dashboard

College Ave, Menlo Park · sensor measurement · Mar 31 – Apr 24, 2026 · all times PDT

1 · Who uses this street?

Mode mix

Total counts across the period. Vehicles dominate; pedestrians and bikes share the same right-of-way.

Hourly conflict — vehicles vs vulnerable users

Vehicles per hour (cars + heavy stacked) and bikes + pedestrians per hour. Hover any hour for the full speed breakdown.

The conflict zone — speeds meet people in the road

Stacked bars: pedestrians and cyclists per hour. Red line: 85th-percentile speed of moving vehicles that hour. Yellow bands mark the peak conflict zones — when high pedestrian and bike volume overlaps with persistently high vehicle speeds.

2 · How fast are vehicles going?

Speed distribution

Vehicles in each speed bin. Numbers above each bar show share of all vehicles, plus per-day average.

Vehicle exposure vs pedestrian fatality risk

Cyan: share of College Ave vehicles traveling at or above each speed (falls right — fewer cars at higher speeds). Red: probability a struck pedestrian dies at that impact speed (Tefft 2011, rises right — lethality climbs sharply with speed). Read any speed on the x-axis to see both at once: how many cars travel that fast, and how deadly a pedestrian strike at that speed would be.

Speed percentiles by hour-of-day

Shaded band = 15th–85th percentile. Solid line = median. Magenta dashed = 95th. Red dashed = 25 mph residential limit. Magenta band at top = the 3 mph–wide speed bucket where the fastest cars (≥2 cars in the sample) actually fell — the real peak is somewhere inside that bucket, not exactly at any single number.

Speed percentiles by day

Same metric — shaded band = 15th–85th percentile, solid line = median, magenta dashed = 95th, magenta band at top = the 3 mph–wide bucket where the fastest cars actually fell — but plotted across each observed day instead of by hour. Weekend dates in cyan on the x-axis.

Speeders by hour-of-day

Share of vehicles exceeding 25 mph (≈40 km/h)

Egregious speeders by hour

Share of vehicles exceeding 31 mph (≈50 km/h) — 6+ over the limit

3 · When? — volume detail

Daily vehicle volume

Vehicles per day, with cars (cyan) and heavy vehicles (navy) stacked. Total per day labeled on top of each bar.

Daily pedestrian and bike volume

People on foot or bike per day, with cyclists (cyan) and pedestrians (light cyan) stacked. Total per day labeled on top of each bar.

Hourly profile

Average vehicles per hour-of-day, with cars and heavy stacked. Hover for the breakdown.

Day of week

Average vehicles per day by weekday. Weekends in cyan; cars and heavy stacked.

Conflict heatmap — when do vehicles and vulnerable users overlap?

Each cell's intensity = vehicles × (pedestrians + bikes) for that hour of that weekday. The darker the cell, the more vehicle–vulnerable interactions can happen. Hover any cell for the underlying counts.

low conflict
peak

4 · Is College Ave actually functioning as a bike boulevard?

NACTO bike boulevard compliance, day by day

College Ave is designated as a bicycle boulevard in the Menlo Park General Plan. The NACTO Urban Bikeway Design Guide sets the criteria for what that designation actually requires. Each row is one NACTO target criterion; each column is one observed day. = day met the target. = did not.

Source: NACTO, Urban Bikeway Design Guide — Bike Boulevards. NACTO uses the 95th percentile speed (which captures high-end speeders) rather than the 85th. NACTO does not specify a heavy-vehicle threshold.

Methodology. Volume counts ("vehicles") are cars + heavy vehicles, as reported by the sensor. Speed metrics use the per-hour passenger-car speed histogram that the sensor reports. Heavy-vehicle speeds aren't classified separately, so they're counted toward volume but not toward speed distributions. Percentiles are computed by linear interpolation within each km/h bin (converted to mph). The 25 mph reference reflects the standard California residential speed limit (CVC §22352). The pedestrian-fatality curve in Section 4 is interpolated from Tefft (AAA Foundation, 2011), modeling an average-aged adult struck by a passenger car. Heavy vehicles add a further 2–3× lethality multiplier per IIHS research, not reflected in the curve. Hours with zero recorded traffic are excluded from speed-percentile calculations.

Sample. The dashboard reflects .