GTFS Schedule Validation Report

This report was generated by the Canonical GTFS Schedule validator, version 7.1.0 at 2025-12-05T17:34:05Z,
for the dataset file:///shared/monsey-trails-us.zip. No country code was provided.

Use this report alongside our documentation.

Summary

Agencies included

Feed Info

Publisher Name:
Busmaps.com
Publisher URL:
https://busmaps.com
Feed Email:
alex@busmaps.com
Feed Language:
English
Feed Start Date:
2025-11-02
Feed End Date:
2026-01-15

Files included

  1. agency.txt
  2. calendar.txt
  3. feed_info.txt
  4. routes.txt
  5. shapes.txt
  6. stop_times.txt
  7. stops.txt
  8. trips.txt

Counts

  • Agencies: 1
  • Blocks: 0
  • Routes: 6
  • Shapes: 37
  • Stops: 50
  • Trips: 113

Specification Compliance report

22 notices reported (0 errors, 22 warnings, 0 infos)

Notice Code Severity Total
fast_travel_between_consecutive_stops WARNING 20

fast_travel_between_consecutive_stops

A transit vehicle moves too fast between two consecutive stops.

The speed threshold depends on route type:

Route type Description Threshold, km/h
0 Light rail 100
1 Subway 150
2 Rail 500
3 Bus 150
4 Ferry 80
5 Cable tram 30
6 Aerial lift 50
7 Funicular 50
11 Trolleybus 150
12 Monorail 150
- Unknown 200

You can see more about this notice here.

tripCsvRowNumber (?) The row number of the problematic trip. tripId (?) `trip_id` of the problematic trip. routeId (?) `route_id` of the problematic trip. speedKph (?) Travel speed (km/h). distanceKm (?) Distance between stops (km). csvRowNumber1 (?) The row number of the first stop time. stopSequence1 (?) `stop_sequence` of the first stop. stopId1 (?) `stop_id` of the first stop. stopName1 (?) `stop_name` of the first stop. departureTime1 (?) `departure_time` of the first stop. csvRowNumber2 (?) The row number of the second stop time. stopSequence2 (?) `stop_sequence` of the second stop. stopId2 (?) `stop_id` of the second stop. stopName2 (?) `stop_name` of the second stop. arrivalTime2 (?) `arrival_time` of the second stop.
21 "103322-0f63f221-ce20-4a54-a7e8-adc28ab99fe7" "103322-wfmu" 222.9222305562509 3.715370509270848 236 4 "103322-UNAZ" "N Airmont Rd & RT-59" "10:00:00" 237 5 "103322-07GK" "RT-59 & E Saddle River Rd" "10:00:00"
40 "103322-KJ-SL-F-01" "103322-wfmu" 222.9222305562509 3.715370509270848 513 4 "103322-UNAZ" "N Airmont Rd & RT-59" "09:10:00" 514 5 "103322-07GK" "RT-59 & E Saddle River Rd" "09:10:00"
87 "103322-090a7973-c687-455a-8cbe-865b34de25f5" "103322-wfmu" 222.9222305562509 3.715370509270848 1161 4 "103322-UNAZ" "N Airmont Rd & RT-59" "15:55:00" 1162 5 "103322-07GK" "RT-59 & E Saddle River Rd" "15:55:00"
18 "103322-KJ-SL-Su-01" "103322-wfmu" 222.9222305562509 3.715370509270848 203 4 "103322-UNAZ" "N Airmont Rd & RT-59" "10:55:00" 204 5 "103322-07GK" "RT-59 & E Saddle River Rd" "10:55:00"
22 "103322-5739228c-ae53-4489-a562-66aca40b6953" "103322-wfmu" 222.9222305562509 3.715370509270848 247 4 "103322-UNAZ" "N Airmont Rd & RT-59" "11:40:00" 248 5 "103322-07GK" "RT-59 & E Saddle River Rd" "11:40:00"
81 "103322-5a8f4ad0-8a8f-4256-9efe-8e31022e34c4" "103322-wfmu" 222.9222305562509 3.715370509270848 1077 4 "103322-UNAZ" "N Airmont Rd & RT-59" "11:50:00" 1078 5 "103322-07GK" "RT-59 & E Saddle River Rd" "11:50:00"
42 "103322-62aede57-4827-4959-a06e-5ad02625bce1" "103322-wfmu" 222.9222305562509 3.715370509270848 535 4 "103322-UNAZ" "N Airmont Rd & RT-59" "17:40:00" 536 5 "103322-07GK" "RT-59 & E Saddle River Rd" "17:40:00"
46 "103322-01-GHP-WD-725" "103322-w6tw" 2379.5681868145066 39.65946978024178 600 11 "103322-HMOK" "RT 45 and RT 59" "07:45:00" 601 12 "103322-2CZ9" "W 34th St & 9th Ave" "07:45:00"
19 "103322-KJ-SL-Su-02" "103322-wfmu" 222.9222305562509 3.715370509270848 214 4 "103322-UNAZ" "N Airmont Rd & RT-59" "12:10:00" 215 5 "103322-07GK" "RT-59 & E Saddle River Rd" "12:10:00"
20 "103322-KJ-SL-Su-05" "103322-wfmu" 222.9222305562509 3.715370509270848 225 4 "103322-UNAZ" "N Airmont Rd & RT-59" "19:25:00" 226 5 "103322-07GK" "RT-59 & E Saddle River Rd" "19:25:00"
41 "103322-47170ae3-c896-43d0-b460-a318649a66f7" "103322-wfmu" 222.9222305562509 3.715370509270848 524 4 "103322-UNAZ" "N Airmont Rd & RT-59" "19:25:00" 525 5 "103322-07GK" "RT-59 & E Saddle River Rd" "19:25:00"
39 "103322-ce0e1ecd-9326-4448-b6b0-f693a64ef4c4" "103322-wfmu" 222.9222305562509 3.715370509270848 502 4 "103322-UNAZ" "N Airmont Rd & RT-59" "15:55:00" 503 5 "103322-07GK" "RT-59 & E Saddle River Rd" "15:55:00"
45 "103322-01-HMP-WD-625" "103322-w6tw" 299.8410071535048 4.99735011922508 586 13 "103322-X0XF" "W 23rd St & 5th Ave" "07:35:00" 587 14 "103322-6WBL" "Bedford Ave & Hewes St" "07:35:00"
56 "103322-65847872-9051-4490-882a-b482766c3295" "103322-wfmu" 222.9222305562509 3.715370509270848 735 4 "103322-UNAZ" "N Airmont Rd & RT-59" "17:40:00" 736 5 "103322-07GK" "RT-59 & E Saddle River Rd" "17:40:00"
15 "103322-293055c8-9795-486e-be35-2c5fbb7c7a3c" "103322-wfmu" 222.9222305562509 3.715370509270848 168 6 "103322-UNAZ" "N Airmont Rd & RT-59" "20:35:00" 169 7 "103322-07GK" "RT-59 & E Saddle River Rd" "20:35:00"
16 "103322-KJ-BH-Su-01" "103322-wfmu" 222.9222305562509 3.715370509270848 181 6 "103322-UNAZ" "N Airmont Rd & RT-59" "20:35:00" 182 7 "103322-07GK" "RT-59 & E Saddle River Rd" "20:35:00"
25 "103322-KJ-SL-Su-03" "103322-wfmu" 222.9222305562509 3.715370509270848 284 4 "103322-UNAZ" "N Airmont Rd & RT-59" "17:55:00" 285 5 "103322-07GK" "RT-59 & E Saddle River Rd" "17:55:00"
77 "103322-36f51b18-3ac1-46d7-b5ae-44c39b7a27de" "103322-wfmu" 222.9222305562509 3.715370509270848 1023 6 "103322-UNAZ" "N Airmont Rd & RT-59" "14:20:00" 1024 7 "103322-07GK" "RT-59 & E Saddle River Rd" "14:20:00"
79 "103322-03504ed9-90ac-49ad-8ecd-f8e43fbd0779" "103322-wfmu" 222.9222305562509 3.715370509270848 1053 6 "103322-UNAZ" "N Airmont Rd & RT-59" "21:40:00" 1054 7 "103322-07GK" "RT-59 & E Saddle River Rd" "21:40:00"
17 "103322-f8a819d9-672f-45c3-98cc-fb4239428c48" "103322-wfmu" 222.9222305562509 3.715370509270848 194 6 "103322-UNAZ" "N Airmont Rd & RT-59" "08:50:00" 195 7 "103322-07GK" "RT-59 & E Saddle River Rd" "08:50:00"
fast_travel_between_far_stops WARNING 1

fast_travel_between_far_stops

A transit vehicle moves too fast between two far stops.

Two stops are considered "far" if they are more than 10 km apart. This normally indicates a more serious problem than too fast travel between consecutive stops.

The speed threshold depends on route type and are the same as fast_travel_between_consecutive_stops.

You can see more about this notice here.

tripCsvRowNumber (?) The row number of the problematic trip. tripId (?) `trip_id` of the problematic trip. routeId (?) `route_id` of the problematic trip. speedKph (?) Travel speed (km/h). distanceKm (?) Distance between stops (km). csvRowNumber1 (?) The row number of the first stop time. stopSequence1 (?) `stop_sequence` of the first stop. stopId1 (?) `stop_id` of the first stop. stopName1 (?) `stop_name` of the first stop. departureTime1 (?) `departure_time` of the first stop. csvRowNumber2 (?) The row number of the second stop time. stopSequence2 (?) `stop_sequence` of the second stop. stopId2 (?) `stop_id` of the second stop. stopName2 (?) `stop_name` of the second stop. arrivalTime2 (?) `arrival_time` of the second stop.
46 "103322-01-GHP-WD-725" "103322-w6tw" 2379.5681868145066 39.65946978024178 600 11 "103322-HMOK" "RT 45 and RT 59" "07:45:00" 601 12 "103322-2CZ9" "W 34th St & 9th Ave" "07:45:00"
mixed_case_recommended_field WARNING 1

mixed_case_recommended_field

This field has customer-facing text and should use Mixed Case (should contain upper and lower case letters).

This field contains customer-facing text and should use Mixed Case (upper and lower case letters) to ensure good readability when displayed to riders. Avoid the use of abbreviations throughout the feed (e.g. St. for Street) unless a location is called by its abbreviated name (e.g. “JFK Airport”). Abbreviations may be problematic for accessibility by screen reader software and voice user interfaces.

Good examples:
Field Text Dataset
"Schwerin, Hauptbahnhof" Verkehrsverbund Berlin-Brandenburg
"Red Hook/Atlantic Basin" NYC Ferry
"Campo Grande Norte" Carris
Bad examples:
Field Text
"GALLERIA MALL"
"3427 GG 17"
"21 Clark Rd Est"

You can see more about this notice here.

filename (?) Name of the faulty file. fieldName (?) Name of the faulty field. fieldValue (?) Faulty value. csvRowNumber (?) The row number of the faulty record.
"stops.txt" "stop_name" "RT 45 and RT 59" 34