Bay Area 511 ACE Schedule#
GTFS Stop Time Updates Bay Area 511 ACE 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:
Increase prediction reliability and accuracy
Increase the availability and completeness of GTFS RT
Decrease the inconsistency and fluctuations of predictions
| Bay Area 511 ACE 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 | 16,374 | 85.0% | 80.6% | 0.1 | 2.5 | 100.0% | 73.0% | 3.0 | 0.7 | 0.0 |
| 2025-06-03 | 21,078 | 87.8% | 67.4% | 0.2 | 3.0 | 67.0% | 73.0% | 7.3 | 2.0 | 0.0 |
| 2025-06-04 | 20,859 | 86.4% | 82.3% | 0.1 | 3.0 | 100.0% | 71.0% | 3.1 | 0.7 | 0.0 |
| 2025-06-05 | 21,921 | 87.9% | 65.0% | 0.1 | 3.0 | 100.0% | 74.0% | 8.8 | 2.8 | 0.1 |
| 2025-06-06 | 20,538 | 87.9% | 74.9% | 0.1 | 3.0 | 100.0% | 73.0% | 5.4 | 1.4 | 0.0 |
| 2025-06-09 | 20,304 | 87.1% | 83.4% | 0.1 | 3.0 | 100.0% | 72.0% | 3.4 | 0.7 | 0.0 |
| 2025-06-10 | 20,397 | 89.2% | 80.8% | 0.1 | 3.0 | 58.0% | 78.0% | 3.5 | 0.4 | 0.0 |
| 2025-06-11 | 20,253 | 89.4% | 74.1% | 0.1 | 3.0 | 88.0% | 75.0% | 5.2 | 0.6 | 0.0 |
| 2025-06-12 | 24,966 | 96.3% | 88.7% | 0.1 | 2.9 | 75.0% | 88.0% | 0.0 | 0.0 | 0.0 |