Mountain Transit GMV Schedule

Mountain Transit GMV Schedule#

GTFS Stop Time Updates Mountain Transit GMV 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

Mountain Transit GMV 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)
2025-06-01 509,265 95.2% 69.3% 0.4 1.6 92.0% 53.0% 6.2 2.8 0.0
2025-06-02 810,993 95.7% 72.0% 0.3 1.6 99.0% 53.0% 5.0 2.6 0.0
2025-06-03 821,310 95.9% 67.6% 0.4 1.6 99.0% 55.0% 6.0 3.0 0.0
2025-06-04 719,427 95.6% 72.7% 0.3 1.5 94.0% 57.0% 5.0 2.5 0.1
2025-06-05 676,029 95.9% 73.8% 0.3 1.6 87.0% 56.0% 4.8 2.5 0.0
2025-06-06 547,458 92.8% 67.5% 0.3 1.2 99.0% 58.0% 5.8 2.9 0.0
2025-06-07 649,869 95.3% 75.4% 0.3 1.9 97.0% 56.0% 4.4 2.3 0.0
2025-06-08 523,992 95.4% 74.6% 0.4 1.4 78.0% 56.0% 4.3 2.6 0.1
2025-06-09 716,154 96.1% 70.0% 0.3 1.6 82.0% 55.0% 5.4 2.8 0.0
2025-06-10 690,153 96.4% 65.8% 0.3 1.8 85.0% 56.0% 6.1 3.1 0.1
2025-06-11 797,760 96.0% 75.1% 0.3 1.5 96.0% 59.0% 4.4 2.5 0.2
2025-06-12 784,977 94.6% 70.4% 0.3 1.6 100.0% 55.0% 5.2 2.8 0.0
2025-06-13 846,699 96.2% 70.3% 0.3 1.7 99.0% 55.0% 5.4 2.7 0.0
2025-06-14 776,091 95.8% 70.4% 0.3 1.5 99.0% 56.0% 5.2 2.8 0.1
2025-06-15 308,175 95.6% 69.7% 0.3 1.6 97.0% 56.0% 7.0 2.6 0.0