Big Blue Bus Swiftly Schedule

Big Blue Bus Swiftly Schedule#

GTFS Stop Time Updates Big Blue Bus Swiftly Schedule Summary#

Generally, we want better transit user experience. Specifically, the performance metrics we can derive from GTFS RT Trip Updates distills into the following objectives:

  1. Increase prediction reliability and accuracy

  2. Increase the availability and completeness of GTFS RT

  3. Decrease the inconsistency and fluctuations of predictions

Big Blue Bus Swiftly Schedule
service_date # Stop Time Update Messages % Minutes with 2+ Stop Time Update Message % Minutes with Accurate Predictions Prediction Spread / Wobble (minutes) Avg Stop Time Updates per Minute % Scheduled Trips with Trip Updates Bus Catch Likelihood (early + ontime predictions) Prediction Padding (minutes added to avoid missing bus) Prediction Error IQR (75th - 25th percentile) (minutes) Prediction Error 50th percentile (minutes)
2025-06-02 7,626,477 98.6% 75.6% 0.2 3.0 0.0% 68.0% 5.4 2.4 0.7
2025-06-03 7,794,225 98.5% 76.1% 0.2 3.0 0.0% 65.0% 5.3 2.4 0.6
2025-06-04 7,828,242 98.5% 73.1% 0.2 3.0 0.0% 69.0% 5.8 2.6 0.8
2025-06-05 7,644,099 98.5% 73.9% 0.2 2.9 0.0% 67.0% 5.5 2.5 0.7
2025-06-06 7,289,340 98.6% 74.9% 0.2 3.0 0.0% 61.0% 5.1 2.5 0.4
2025-06-09 7,047,723 98.6% 76.9% 0.2 3.0 0.0% 60.0% 4.8 2.4 0.4
2025-06-10 7,390,965 98.6% 76.6% 0.2 2.9 0.0% 61.0% 5.1 2.4 0.4
2025-06-13 7,226,751 98.6% 74.1% 0.3 3.0 0.0% 57.0% 5.1 2.5 0.3