Bay Area 511 AC Transit Schedule

Bay Area 511 AC Transit Schedule#

GTFS Stop Time Updates Bay Area 511 AC 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 AC 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)
2025-06-01 51,466,536 98.8% 80.7% 0.2 3.0 100.0% 65.0% 4.4 2.0 0.5
2025-06-02 64,167,732 98.8% 78.6% 0.2 3.0 100.0% 70.0% 4.9 2.1 0.7
2025-06-03 64,823,394 98.8% 76.6% 0.2 3.0 100.0% 73.0% 5.3 2.2 0.8
2025-06-04 65,006,802 98.8% 77.3% 0.2 3.0 100.0% 73.0% 5.2 2.2 0.8
2025-06-05 65,142,174 98.8% 76.9% 0.2 3.0 100.0% 73.0% 5.2 2.2 0.8
2025-06-06 65,069,220 98.8% 76.5% 0.2 3.0 99.0% 72.0% 5.2 2.3 0.8
2025-06-07 52,105,011 98.8% 78.5% 0.2 3.0 99.0% 62.0% 4.6 2.2 0.4
2025-06-08 51,666,369 98.8% 81.2% 0.1 3.0 99.0% 63.0% 4.3 2.0 0.4
2025-06-09 63,698,526 98.8% 80.0% 0.1 3.0 98.0% 71.0% 4.7 2.0 0.7
2025-06-10 65,411,448 98.8% 79.3% 0.1 3.0 100.0% 72.0% 4.9 2.1 0.8
2025-06-11 65,210,868 98.8% 78.9% 0.1 3.0 100.0% 72.0% 4.9 2.1 0.8
2025-06-12 62,047,764 98.2% 77.8% 0.2 2.9 99.0% 72.0% 5.0 2.2 0.8
2025-06-15 29,646,714 98.7% 78.5% 0.1 3.0 95.0% 68.0% 4.9 2.2 0.6