GTFS Schedule Validation Report

block_trips_with_overlapping_stop_times

Trips with the same block id have overlapping stop times.

You can see more about this notice here.

csvRowNumberA (?) The row number from `trips.txt` of the first faulty trip.	tripIdA (?) The id of first faulty trip.	serviceIdA (?) The service id of the first faulty trip.	csvRowNumberB (?) The row number from `trips.txt` of the second faulty trip.	tripIdB (?) The id of the other faulty trip.	serviceIdB (?) The service id of the other faulty trip.	blockId (?) The `trips.block_id` of the overlapping trip.	intersection (?) The overlapping period.
333	"58696039"	"8-17-127"	16	"58696086"	"2-17-127"	"8001"	"20240207"
38	"540177df-8339-463d-8c0e-1788d711d1e8"	"3-17-127"	368	"b65a01a3-1858-4160-b04b-f4f19b91cee8"	"2-17-127"	"7001"	"20240201"
375	"58696104"	"2-17-127"	94	"58695815"	"2-17-127"	"5001"	"20240201"
378	"58696107"	"2-17-127"	98	"58695819"	"2-17-127"	"5001"	"20240201"
103	"58695824"	"2-17-127"	104	"58695825"	"2-17-127"	"5001"	"20240201"
438	"0f68c560-4a1b-410f-96e5-ec35f0ffa4e1"	"3-17-127"	196	"7ca337d0-42f5-4b56-b865-5870f4675e0b"	"2-17-127"	"2001"	"20240201"
341	"58696048"	"3-17-127"	351	"58696065"	"3-17-127"	"30001"	"20240201"

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.
498	"2cd1b7ad-40b7-4f30-b97f-6109bd4c7105"	"32"	156.0707244768764	5.2023574825625465	9045	21	"161272"	"Eglise Vieille Verrerie"	"07:41:00"	9046	22	"161214"	"Avenue de Stiring"	"07:42:00"
310	"37bebb5f-c96c-4f8f-8435-f30bbe062c36"	"32"	312.1414489537528	5.2023574825625465	5610	4	"161214"	"Avenue de Stiring"	"16:54:00"	5611	5	"161272"	"Eglise Vieille Verrerie"	"16:54:00"

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.
310	"37bebb5f-c96c-4f8f-8435-f30bbe062c36"	"32"	154.52245285732207	12.876871071443505	5607	1	"161089"	"Lycée Condorcet"	"16:50:00"	5611	5	"161272"	"Eglise Vieille Verrerie"	"16:54:00"

leading_or_trailing_whitespaces

The value in CSV file has leading or trailing whitespaces.

This notice is emitted for values protected with double quotes since whitespaces for non-protected values are trimmed automatically by CSV parser.

The validator strips whitespaces from protected values. We do not see any use case when such a whitespace may be needed. On the other hand, some real-world feeds use trailing whitespaces for some values and omit them for the others. This is causing the largest problem when a primary key and a foreign key differ just by a whitespace: it is clear that they are intended to be the same, that is why we always strip whitespaces.

You can see more about this notice here.

filename (?) The name of the faulty file.	csvRowNumber (?) The row of the faulty record.	fieldName (?) Faulty record's field name.	fieldValue (?) Faulty value.
"stops.txt"	322	"stop_name"	"Gare "

missing_recommended_column

A recommended column is missing in the input file.

You can see more about this notice here.

filename (?) The name of the faulty file.	fieldName (?) The name of the missing column.
"stop_times.txt"	"timepoint"

missing_recommended_file

A recommended file is missing.

You can see more about this notice here.

filename (?) The name of the faulty file.
"feed_info.txt"

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"	"ALLEE DE LA FORET"	341
"stops.txt"	"stop_name"	"THEDING EBRING"	411
"stops.txt"	"stop_name"	"FORBACH POMPIER"	415
"stops.txt"	"stop_name"	"CROISEMENT RUE DE LA GARE"	437
"stops.txt"	"stop_name"	"HOTEL DE VILLE"	442
"stops.txt"	"stop_name"	"PLACE WENDEL"	458
"stops.txt"	"stop_name"	"RUE SAINT HENRI"	471
"stops.txt"	"stop_name"	"rue de la cartonnerie ADT"	492
"stops.txt"	"stop_name"	"centre commercial oeting"	498
"stops.txt"	"stop_name"	"aire de repos"	592
"stops.txt"	"stop_name"	"aire de repos"	593
"trips.txt"	"trip_headsign"	"aire de repos"	147

route_long_name_contains_short_name

Long name should not contain short name for a single route.

In routes.txt, route_long_name should not contain the value for route_short_name, because when both are provided, they are often combined by transit applications. Note that only one of the two fields is required. If there is no short name used for a route, use route_long_name only.

Good examples:

route_short_name/route_long_name	Dataset
"N"/"Judah"	Muni San Fransisco
"6"/"ML King Jr Blvd"	Trimet Portland Streetcar
"55"/"Boulevard Saint Laurent"	STM Montreal
"1"/"Rangiora/Cashmere"	Metro Christchurch

Bad examples:

route_short_name/route_long_name
"604"/"604"
"14"/"Route 14"
"2"/"Route 2: Bellows Falls In-Town"

You can see more about this notice here.

routeId (?) The id of the faulty record.	csvRowNumber (?) The row number of the faulty record.	routeShortName (?) The faulty record's `route_short_name`.	routeLongName (?) The faulty record's `route_long_name`.
"LIGNE-11"	32	"Ligne 11"	"Ligne 11"