Bay Area 511 Fairfield and Suisun Transit Schedule

Bay Area 511 Fairfield and Suisun Transit Schedule#

GTFS Stop Time Updates Bay Area 511 Fairfield and Suisun Transit 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

Bay Area 511 Fairfield and Suisun Transit 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)
2025-06-02 859,149 98.8% 82.4% 0.1 3.0 100.0% 73.0% 3.8 1.6 0.6
2025-06-03 868,260 98.8% 79.7% 0.1 3.0 100.0% 76.0% 4.4 1.8 0.8
2025-06-04 840,309 98.8% 80.3% 0.1 3.0 97.0% 75.0% 4.4 1.7 0.7
2025-06-05 867,624 98.8% 78.9% 0.1 3.0 100.0% 74.0% 4.2 1.9 0.8
2025-06-06 839,856 98.7% 78.1% 0.1 3.0 100.0% 74.0% 5.1 2.0 0.7
2025-06-07 248,163 98.7% 74.5% 0.1 3.0 100.0% 72.0% 5.3 2.3 0.9
2025-06-09 813,516 98.8% 86.1% 0.1 3.0 100.0% 71.0% 3.2 1.4 0.5
2025-06-10 821,976 98.9% 84.3% 0.1 3.0 100.0% 73.0% 3.6 1.5 0.6
2025-06-11 762,267 98.8% 83.2% 0.1 3.0 95.0% 70.0% 3.9 1.5 0.5
2025-06-12 780,690 97.8% 79.6% 0.1 2.9 100.0% 72.0% 4.4 1.8 0.6
2025-06-13 761,586 98.8% 81.6% 0.1 3.0 96.0% 69.0% 4.1 1.7 0.6
2025-06-14 251,175 98.9% 80.6% 0.1 3.0 100.0% 65.0% 4.0 1.8 0.5