LA Metro Bus Schedule#

GTFS Stop Time Updates LA Metro Bus 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

LA Metro Bus 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)
2025-06-01 169,719,432 98.7% 78.5% 0.2 3.0 100.0% 69.0% 4.9 2.2 0.7
2025-06-02 239,222,703 98.8% 82.5% 0.2 3.0 100.0% 52.0% 3.8 2.1 0.0
2025-06-03 240,367,632 98.8% 81.5% 0.2 3.0 100.0% 53.0% 4.0 2.2 0.0
2025-06-04 238,748,193 98.6% 82.3% 0.2 3.0 100.0% 53.0% 3.9 2.1 0.0
2025-06-05 240,376,038 98.8% 81.5% 0.2 3.0 100.0% 53.0% 4.0 2.2 0.0
2025-06-06 236,860,935 98.8% 81.5% 0.2 3.0 100.0% 52.0% 3.9 2.2 0.0
2025-06-07 174,690,873 98.8% 79.2% 0.2 3.0 98.0% 64.0% 4.7 2.2 0.5
2025-06-08 166,646,532 98.7% 80.4% 0.2 3.0 98.0% 68.0% 4.7 2.1 0.6
2025-06-09 235,792,080 98.8% 82.5% 0.2 3.0 99.0% 48.0% 3.6 2.1 -0.0
2025-06-10 238,050,075 98.7% 82.5% 0.2 2.9 99.0% 49.0% 3.6 2.1 -0.0
2025-06-11 237,348,888 98.7% 82.8% 0.2 3.0 99.0% 47.0% 3.5 2.1 -0.1
2025-06-12 229,794,675 97.5% 82.8% 0.2 2.8 98.0% 46.0% 3.4 2.1 -0.1
2025-06-13 228,352,041 98.2% 82.2% 0.2 2.8 100.0% 48.0% 3.6 2.1 -0.0
2025-06-14 165,721,524 98.6% 79.0% 0.2 3.0 100.0% 64.0% 4.7 2.2 0.5
2025-06-15 114,221,589 98.8% 81.2% 0.2 3.0 100.0% 67.0% 4.5 2.0 0.6