Try to match realtime transit data (e.g. from GTFS Realtime (GTFS-RT)) with GTFS Static data, even if they don't share an ID.
This repo uses @derhuerst/stable-public-transport-ids to compute IDs from transit data itself:
gtfs-via-postgresis used to import the GTFS Static data into the DB.- It computes these "stable IDs" for all relevant items in the GTFS Static data and store them in the DB.
- When given a pice of realtime data (e.g. from a GTFS Realtime feed), compute its "stable IDs" and check if they match those stored in the DB.
npm install match-gtfs-rt-to-gtfsNote: match-gtfs-rt-to-gtfs needs PostgreSQL >=14 to work, as its dependency gtfs-via-postgres needs that version. You can check your PostgreSQL server's version with psql -t -c 'SELECT version()'.
Let's use gtfs-to-sql CLI from the gtfs-via-postgres to import our GTFS data into PostgreSQL:
gtfs-to-sql path/to/gtfs/*.txt | psql -bTo some extent, match-gtfs-rt-to-gtf fuzzily matches stop/station & route/line names (more on that below). For that to work, we need to tell it how to "normalize" these names. As an example, we're going to do this for the VBB data:
// normalize.js
const normalizeStopName = require('normalize-vbb-station-name-for-search')
const slugg = require('slugg')
const normalizeLineName = (name) => {
return slugg(name.replace(/([a-zA-Z]+)\s+(\d+)/g, '$1$2'))
}
module.exports = {
normalizeStopName,
normalizeLineName,
// With VBB vehicles, the headsign is almost always the last stop.
normalizeTripHeadsign: normalizeStopName,
}We're going to create two files that specify how to handle the GTFS-RT & GTFS (Static) data, respectively:
// gtfs-rt-info.js
const {
normalizeStopName,
normalizeLineName,
normalizeTripHeadsign,
} = require('./normalize.js')
module.exports = {
endpointName: 'vbb-hafas',
normalizeStopName,
normalizeLineName,
normalizeTripHeadsign,
}// gtfs-info.js
const {
normalizeStopName,
normalizeLineName,
normalizeTripHeadsign,
} = require('./normalize.js')
module.exports = {
endpointName: 'vbb-gtfs',
normalizeStopName,
normalizeLineName,
normalizeTripHeadsign,
}Now, we're going to use match-gtfs-rt-to-gtfs/build-index.js to import additional data into the database that is needed for matching:
set -o pipefail
./build-index.js gtfs-rt-info.js gtfs-info.js | psql -bmatch-gtfs-rt-to-gtf does its job using fuzzy matching: As an example, it identifies two departure data points from GTFS-RT & GTFS – at the same time, at the same stop/station and with the same route/line name – as equivalent.
Now, let's match a departure against GTFS:
const createMatch = require('match-gtfs-rt-to-gtfs')
const gtfsRtInfo = require('./gtfs-rt-info.js') // see above
const gtfsInfo = require('./gtfs-info.js') // see above
const gtfsRtDep = {
tripId: '1|12308|1|86|7112020',
direction: 'Grunewald, Roseneck',
line: {
type: 'line',
id: 'm29',
fahrtNr: '22569',
name: 'M29',
public: true,
adminCode: 'BVB',
mode: 'bus',
product: 'bus',
operator: {
type: 'operator',
id: 'berliner-verkehrsbetriebe',
name: 'Berliner Verkehrsbetriebe'
},
},
stop: {
type: 'stop',
id: '900000013101',
name: 'U Moritzplatz',
location: {latitude: 52.503737, longitude: 13.410944},
},
when: '2020-11-07T14:55:00+01:00',
plannedWhen: '2020-11-07T14:54:00+01:00',
delay: 60,
platform: null,
plannedPlatform: null,
}
const {matchDeparture} = createMatch(gtfsRtInfo, gtfsInfo)
console.log(await matchDeparture(gtfsRtDep)){
tripId: '145341691',
tripIds: {
'vbb-hafas': '1|12308|1|86|7112020',
'vbb-gtfs': '145341691',
},
routeId: '17449_700',
direction: 'Grunewald, Roseneck',
line: {
type: 'line',
id: null,
fahrtNr: '22569',
fahrtNrs: {'vbb-hafas': '22569'},
name: 'M29',
public: true,
adminCode: 'BVB',
mode: 'bus',
product: 'bus',
operator: {
type: 'operator',
id: 'berliner-verkehrsbetriebe',
name: 'Berliner Verkehrsbetriebe'
},
},
stop: {
type: 'stop',
id: '070101002285',
ids: {
'vbb-hafas': '900000013101',
'vbb-gtfs': '070101002285',
},
name: 'U Moritzplatz',
location: {latitude: 52.503737, longitude: 13.410944},
},
when: '2020-11-07T14:55:00+01:00',
plannedWhen: '2020-11-07T14:54:00+01:00',
delay: 60,
platform: null,
plannedPlatform: null,
}const findShape = require('match-gtfs-rt-to-gtfs/find-shape')
const someTripId = '24582338' // some U3 trip from the HVV dataset
await findShape(someTripId)findShape resolves with a GeoJSON LineString:
{
type: 'LineString',
coordinates: [
[10.044385, 53.5872],
// …
[10.074888, 53.592473]
],
}gtfs-via-postgres adds a view arrivals_departures, which contains every arrival/departure of every trip in the GTFS static dataset. This repo adds another view arrivals_departures_with_stable_ids, which combines the data with the "stable IDs" stored in separate tables. It is then used for the matching process, which works essentially like this:
SELECT *
FROM arrivals_departures_with_stable_ids
WHERE (
stop_stable_ids && ARRAY['stop-id1', 'stop-id2']
OR station_stable_ids && ARRAY['station-id1', 'station-id2']
)
AND route_stable_ids && ARRAY['route-id1', 'route-id2']
AND t_departure > '2020-10-16T22:20:48+02:00'
AND t_departure < '2020-10-16T22:22:48+02:00'Because PostgreSQL executes this query quite efficiently, we don't need to store a pre-computed list index of all arrivals/departures, but just an index of their stable stop/station/route IDs.
The size of this additional index depends on how many stable IDs your logic generates for each stop/station/route. Consider the 2020-09-25 VBB GTFS Static feed as an example: Without shapes.txt, it is 356MB as CSV files, ~2GB as imported & indexed in the DB by gtfs-via-posgres; match-gtfs-rt-to-gtfs's stable IDs indices add another
- 300MB with few stable IDs per stop/station/route, and
- 3GB with 10-30 stable IDs each.
{
endpointName: string,
normalizeStopName: (name: string, stop: FptfStop) => string,
normalizeLineName(name: string, line: FptfLine) => string,
normalizeTripHeadsign(headsign: string) => string,
}Note: This repos blends two families of techinical terms – GTFS-related ones and FPTF-/hafas-client-related ones –, which makes the code somewhat confusing.
If you have a question or need support using match-gtfs-rt-to-gtfs, please double-check your code and setup first. If you think you have found a bug or want to propose a feature, use the issues page.
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