Fresno Schedule#

GTFS Stop Time Updates Fresno 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

Fresno 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 18,796,014 98.6% 74.8% 0.2 3.0 99.0% 69.0% 5.7 2.4 0.5
2025-06-03 18,716,814 98.7% 73.4% 0.2 3.0 100.0% 69.0% 6.0 2.5 0.6
2025-06-04 18,424,611 98.8% 73.3% 0.1 3.0 99.0% 68.0% 6.2 2.5 0.5
2025-06-05 18,949,083 98.8% 74.6% 0.2 3.0 99.0% 68.0% 6.0 2.4 0.5
2025-06-06 17,700,858 98.7% 73.4% 0.2 3.0 94.0% 67.0% 6.0 2.4 0.5
2025-06-07 12,203,412 98.7% 75.5% 0.2 3.0 98.0% 69.0% 5.7 2.3 0.5
2025-06-08 11,595,018 98.6% 78.1% 0.2 3.0 98.0% 69.0% 5.3 2.0 0.5
2025-06-09 18,117,738 98.6% 74.6% 0.2 3.0 98.0% 67.0% 5.7 2.4 0.5
2025-06-10 18,701,934 98.6% 75.4% 0.2 3.0 99.0% 67.0% 5.8 2.3 0.5
2025-06-11 18,391,572 98.7% 74.5% 0.2 3.0 98.0% 68.0% 5.9 2.4 0.5
2025-06-12 17,999,118 98.5% 76.7% 0.1 2.9 99.0% 67.0% 5.4 2.2 0.4
2025-06-13 18,713,691 98.8% 79.3% 0.1 3.0 99.0% 69.0% 5.1 2.0 0.4
2025-06-14 13,131,948 98.8% 74.6% 0.3 3.0 100.0% 69.0% 5.9 2.3 0.5
2025-06-15 8,961,402 98.7% 78.5% 0.2 3.0 100.0% 71.0% 5.0 2.0 0.5