GTFS - General Transit Feed Specification - began life in 2005 as the
“Google Transit Feed Specification,” and was renamed to “General” in
2009. It provides a standardised scheme for representing data on public
transport services, routes, frequencies, and timetables. A GTFS data set
consists of several comma-delimited (.csv) files detailing
routes, stops, trips, transfers, and other aspects, all bundled in a
single .zip-compressed archive file. For full details, see
the relevant google developer
site.
There are currently two other R packages which handle GTFS data:
gtfsr,
hosted by rOpenSci, developed by Danton Noriega, but no
longer under active development.tidytransit,
which began as a fork of gtfsr,
and currently represents its successor. This package can be used to,
“map transit stops and routes, calculate transit frequencies, and
validate transit feeds [as well as to read] the General Transit Feed
Specification into tidyverse and simple features dataframes.”The one thing neither of these packages enable is the use of GTFS
data for transit routing. The gtfsrouter package enables
both one-to-one and one-to-many routing. Functionality is demonstrated
here through the sample data set included with the package, provided by
the “Verkehrsverbund Berlin-Brandenburg” (VBB; or Transport Network
Berlin-Brandenburg). The berlin_gtfs data represents a
reduced version of the full GTFS data, containing only six tables, and a
timetable reduced to the single hour between 12:00-13:00. Like all GTFS
software including tidytransit,
this package is designed to work directly with GTFS data in
.zip-archived format, and so includes a helper function,
berlin_gtfs_to_zip(), which exports the internal data set
to a locally-stored .zip archive in the
tempdir() of the current R session. These
data can be exported and re-imported with:
berlin_gtfs_to_zip ()## /tmp/RtmpOtCvKQ/vbb.zipf <- file.path (tempdir (), "vbb.zip")
file.exists (f)## [1] TRUEgtfs <- extract_gtfs (f)## ▶ Unzipping GTFS archive✔ Unzipped GTFS archive
## ▶ Extracting GTFS feed✔ Extracted GTFS feed
## ▶ Converting stop times to seconds✔ Converted stop times to seconds
## ▶ Converting transfer times to seconds✔ Converted transfer times to secondsThat simply re-creates the original package data,
berlin_gtfs (although the extracted data differ through
having a couple of additional attributes defining it as a
gtfs object).
The primary routing function is gtfs_route(), the
example of which uses the gtfs data for the VBB created as
described above. In simplest form, routing requires a start and end
point, defaulting to the current time as desired start time, and routing
for the current day of the week.
from <- "Innsbrucker Platz"
to <- "Alexanderplatz"
gtfs_route (
gtfs,
from = from,
to = to
)## Day not specified; extracting timetable for wednesday| route_name | trip_name | stop_name | arrival_time | departure_time |
|---|---|---|---|---|
| U4 | U Nollendorfplatz | S+U Innsbrucker Platz (Berlin) | 12:06:00 | 12:06:00 |
| U4 | U Nollendorfplatz | U Rathaus Schoneberg (Berlin) | 12:07:00 | 12:07:00 |
| U4 | U Nollendorfplatz | U Bayerischer Platz (Berlin) | 12:08:30 | 12:08:30 |
| U4 | U Nollendorfplatz | U Viktoria-Luise-Platz (Berlin) | 12:10:00 | 12:10:00 |
| U4 | U Nollendorfplatz | U Nollendorfplatz (Berlin) | 12:12:00 | 12:12:00 |
| U2 | S+U Pankow | U Nollendorfplatz (Berlin) | 12:17:00 | 12:17:00 |
| U2 | S+U Pankow | U Bulowstr. (Berlin) | 12:18:30 | 12:18:30 |
| U2 | S+U Pankow | U Gleisdreieck (Berlin) | 12:20:30 | 12:20:30 |
| U2 | S+U Pankow | U Mendelssohn-Bartholdy-Park (Berlin) | 12:22:00 | 12:22:00 |
| U2 | S+U Pankow | S+U Potsdamer Platz (Bln) [U2] | 12:23:30 | 12:23:30 |
| U2 | S+U Pankow | U Mohrenstr. (Berlin) | 12:25:00 | 12:25:00 |
| U2 | S+U Pankow | Berlin, U Stadtmitte U2 | 12:26:00 | 12:26:00 |
| U2 | S+U Pankow | U Hausvogteiplatz (Berlin) | 12:27:30 | 12:27:30 |
| U2 | S+U Pankow | U Spittelmarkt (Berlin) | 12:29:00 | 12:29:00 |
| U2 | S+U Pankow | U Markisches Museum (Berlin) | 12:30:00 | 12:30:00 |
| U2 | S+U Pankow | U Klosterstr. (Berlin) | 12:31:30 | 12:31:30 |
| U2 | S+U Pankow | S+U Alexanderplatz (Berlin) [U2] | 12:33:30 | 12:33:30 |
Both the start time and day of the week can be explicitly specified:
route <- gtfs_route (
gtfs,
from = from,
to = to,
start_time = "12:00:00",
day = "Sunday"
)The gtfsrouter package uses the Connection Scan Algorithm,
which requires converting the “stop_times” table to a column-wise
timetable. The “stop_times” table has row-wise entries for each distinct
“trip_id”, with consecutive rows for a given value of “trip_id” holding
sequential values for stops and associated times (and potentially
additional variables). In contrast, the timetables processed by this
package have separate columns for departure and arrival stations and
times. All routing queries pre-process the original GTFS data with the
gtfs_timetable() function, which appends this timetable
data, along with two single-column tables of stop and trip ID values.
(The timetable itself contains strictly integer values for stops and
trips, which are indices into these latter tables.)
The only important point of that from a user’s perspective is that
routing queries will be faster if this pre-processing step is explicitly
implemented with gtfs_timetable() prior to calling
gtfs_route(). This is easy to demonstrate using the sample
data:
gtfs <- extract_gtfs (f)## ▶ Unzipping GTFS archive✔ Unzipped GTFS archive
## ▶ Extracting GTFS feed✔ Extracted GTFS feed
## ▶ Converting stop times to seconds✔ Converted stop times to seconds
## ▶ Converting transfer times to seconds✔ Converted transfer times to secondsfrom <- "Innsbrucker Platz"
to <- "Alexanderplatz"
system.time (
gtfs_route (
gtfs,
from = from,
to = to,
start_time = "12:00:00",
day = "Sunday"
)
)## user system elapsed
## 0.054 0.000 0.054names (gtfs)## [1] "calendar" "routes" "trips" "stop_times" "stops"
## [6] "transfers"# explicit pre-processing to extract timetable for Sunday
gtfs <- gtfs_timetable (gtfs,
day = "Sunday"
)
names (gtfs)## [1] "calendar" "routes" "trips" "stop_times" "stops"
## [6] "transfers" "timetable" "stop_ids" "trip_ids"system.time (gtfs_route (
gtfs,
from = from,
to = to,
start_time = "12:00:00"
))## user system elapsed
## 0.042 0.000 0.043Note that the day parameter is used to extract the
timetable, after which it is no longer required in the actual call to
gtfs_route().
It is also possible to filter by desired mode of transport. This is
done by matching the pattern to those given in the
route_short_name column of the gtfs$route
table:
head (gtfs$route)| route_id | agency_id | route_short_name | route_long_name | route_type | route_color | route_text_color | route_desc |
|---|---|---|---|---|---|---|---|
| 10141_109 | 1 | S1 | 109 | E64DFF | FFFFFF | ||
| 10142_109 | 1 | S1 | 109 | E64DFF | FFFFFF | ||
| 10143_109 | 1 | S2 | 109 | 00B300 | FFFFFF | ||
| 10144_109 | 1 | S2 | 109 | 00B300 | FFFFFF | ||
| 10145_109 | 1 | S25 | 109 | ||||
| 10148_109 | 1 | S3 | 109 |
These short names will differ for each GTFS, with the two primary
train systems in Berlin being the underground trains denoted “U”
(although not always travelling underground), and street-level trains
denoted “S”. The default route from Innsbrucker Platz to Alexanderplatz
above was via two “U” services. We can also specify that we’d prefer to
travel by “S” services, noting that the route_pattern = "S"
specifies a route_short_name that starts with
("^") “S”:
gtfs_route (
gtfs,
from = from,
to = to,
start_time = "12:00:00",
day = "Sunday",
route_pattern = "^S"
)| route_name | trip_name | stop_name | arrival_time | departure_time |
|---|---|---|---|---|
| S42 | S Sudkreuz Bhf | S+U Innsbrucker Platz (Berlin) | 12:06:42 | 12:07:12 |
| S42 | S Sudkreuz Bhf | S Schoneberg (Berlin) | 12:08:18 | 12:08:48 |
| S42 | S Sudkreuz Bhf | S Sudkreuz Bhf (Berlin) | 12:10:12 | 12:10:12 |
| S2 | S Buch | S Sudkreuz Bhf (Berlin) | 12:16:18 | 12:16:54 |
| S2 | S Buch | S+U Yorckstr. S2 S25 S26 U7 (Berlin) | 12:19:00 | 12:19:30 |
| S2 | S Buch | S Anhalter Bahnhof (Berlin) | 12:21:42 | 12:22:12 |
| S2 | S Buch | S+U Potsdamer Platz Bhf (Berlin) | 12:23:48 | 12:24:18 |
| S2 | S Buch | S+U Brandenburger Tor (Berlin) | 12:25:54 | 12:26:24 |
| S2 | S Buch | S+U Friedrichstr. Bhf (Berlin) | 12:27:36 | 12:28:24 |
| S7 | S Ahrensfelde Bhf | S+U Friedrichstr. Bhf (Berlin) | 12:30:36 | 12:31:24 |
| S7 | S Ahrensfelde Bhf | S Hackescher Markt (Berlin) | 12:32:54 | 12:33:24 |
| S7 | S Ahrensfelde Bhf | S+U Alexanderplatz Bhf (Berlin) | 12:34:36 | 12:35:24 |
The above route with the “S” services leaves one minute later, and
arrives two minutes later. Importantly, gtfs_route()
searches by default for the service which arrives at the nominated
destination station at the earliest time. This may not always be the
first available service departing from the nominated start station.
Routing with the earliest departing service, instead of the
earliest arriving service, can be specified with the binary
earliest_arrival parameter:
from <- "Alexanderplatz"
to <- "Pankow"
gtfs_route (
gtfs,
from = from,
to = to,
start_time = "12:00:00",
day = "Sunday",
earliest_arrival = FALSE
)| route_name | trip_name | stop_name | arrival_time | departure_time |
|---|---|---|---|---|
| S7 | S Potsdam Hauptbahnhof | S+U Alexanderplatz Bhf (Berlin) | 11:59:54 | 12:00:42 |
| S7 | S Potsdam Hauptbahnhof | S Hackescher Markt (Berlin) | 12:01:54 | 12:02:24 |
| S7 | S Potsdam Hauptbahnhof | S+U Friedrichstr. Bhf (Berlin) | 12:03:54 | 12:04:42 |
| S2 | S Buch | S+U Friedrichstr. Bhf (Berlin) | 12:07:36 | 12:08:24 |
| S2 | S Buch | S Oranienburger Str. (Berlin) | 12:09:42 | 12:10:12 |
| S2 | S Buch | S Nordbahnhof (Berlin) | 12:11:42 | 12:12:12 |
| S2 | S Buch | S Humboldthain (Berlin) | 12:14:24 | 12:14:54 |
| S2 | S Buch | S+U Gesundbrunnen Bhf (Berlin) | 12:16:12 | 12:16:54 |
| S2 | S Buch | S Bornholmer Str. (Berlin) | 12:18:24 | 12:18:54 |
| S2 | S Buch | S+U Pankow (Berlin) | 12:20:42 | 12:21:18 |
And the earliest-departing route arrives at Pankow at 12:20:42, departing Alexanderplatz at 12:00:42. In contrast, the earliest-arriving service is:
gtfs_route (
gtfs,
from = from,
to = to,
start_time = "12:00:00",
day = "Sunday",
earliest_arrival = TRUE
)| route_name | trip_name | stop_name | arrival_time | departure_time |
|---|---|---|---|---|
| U2 | S+U Pankow | S+U Alexanderplatz (Berlin) [U2] | 12:09:00 | 12:09:00 |
| U2 | S+U Pankow | U Rosa-Luxemburg-Platz (Berlin) | 12:11:00 | 12:11:00 |
| U2 | S+U Pankow | U Senefelderplatz (Berlin) | 12:12:30 | 12:12:30 |
| U2 | S+U Pankow | U Eberswalder Str. (Berlin) | 12:14:30 | 12:14:30 |
| U2 | S+U Pankow | S+U Schonhauser Allee (Berlin) | 12:16:30 | 12:16:30 |
| U2 | S+U Pankow | U Vinetastr. (Berlin) | 12:19:00 | 12:19:00 |
| U2 | S+U Pankow | S+U Pankow (Berlin) | 12:20:30 | 12:20:30 |
This service departs 8min, 18s later at 12:09:00, and arrives 12
seconds earlier at 12:20:30. The earliest-arriving service thus entails
8min, 30s less travel time than the earliest departing service. It is
nevertheless important to note that queries for earliest-arriving
services require two full routing runs, whereas earliest-departing
services can be executed in a single run. This, bulk queries for
analytic purposes will generally be up to twice as first with
earliest_arrival = FALSE.
go_home() and
go_to_work()The gtfsrouter package is intended both to enable
statistical analyses of GTFS data sets, as well as for personal,
pragmatic purposes. In the latter regard, the package provides two
“convenience” functions to allow single-call queries for next available
services to “home” and “work” stations. These functions require some
initial set-up through specifying environmental variables, but once done
can be executed as single calls from any R session to
return the next available service.
go_home ()## route_name trip_name stop_name
## 1 S7 S Potsdam Hauptbahnhof S+U Alexanderplatz Bhf (Berlin)
## 2 S7 S Potsdam Hauptbahnhof S Hackescher Markt (Berlin)
## 3 S7 S Potsdam Hauptbahnhof S+U Friedrichstr. Bhf (Berlin)
## 4 S2 S Lichtenrade S+U Friedrichstr. Bhf (Berlin)
## 5 S2 S Lichtenrade S+U Brandenburger Tor (Berlin)
## 6 S2 S Lichtenrade S+U Potsdamer Platz Bhf (Berlin)
## 7 S2 S Lichtenrade S Anhalter Bahnhof (Berlin)
## 8 S2 S Lichtenrade S+U Yorckstr. S2 S25 S26 U7 (Berlin)
## 9 S2 S Lichtenrade S Sudkreuz Bhf (Berlin)
## 10 S46 S Westend S Sudkreuz Bhf (Berlin)
## 11 S46 S Westend S Schoneberg (Berlin)
## 12 S46 S Westend S+U Innsbrucker Platz (Berlin)
## arrival_time departure_time
## 1 12:19:54 12:20:42
## 2 12:21:54 12:22:24
## 3 12:23:54 12:24:42
## 4 12:28:00 12:28:42
## 5 12:29:54 12:30:24
## 6 12:31:54 12:32:24
## 7 12:34:00 12:34:30
## 8 12:36:42 12:37:12
## 9 12:39:18 12:39:54
## 10 12:43:00 12:43:42
## 11 12:45:12 12:45:42
## 12 12:46:54 12:47:24The complementary function, go_to_work() routes in the
reverse direction. These functions are intended to allow real-time
queries of public transport schedules from within the comfort of an
R session, and will generally be much quicker – and
hopefully easier – than the arguably burdensome necessity of switching
attention from productive R programming to the usual
app or website otherwise needed to answer the simple question of when I
ought to leave today?
Successfully calling that function requires setting three environmental variables:
Sys.setenv ("gtfs_home" = "<my home station>")
Sys.setenv ("gtfs_work" = "<my work station>")
Sys.setenv ("gtfs_data" = "/full/path/to/gtfs.zip")along with execution of the single command:
process_gtfs_local ()This command attempts to reduce the size of the locally-stored GTFS
data to the minimum required for local routing, and saves the result as
an internal .Rds object in the same location as the
gtfs_data environmental variable. Having done that,
go_home() will search for the next available service from
the nominated work station to the nominated home station, while
go_to_work() will search for connections in the other
direction.
An even easier way to use these functions is to automatically load
those environmental variables at the start of each R
session, which can be achieved simply by creating a file named
.Renviron in the user’s root directory (or opening if it
already exists), and pasting or appending the definitions to that file -
in this case, without the R-specific
Sys.setenv() calls:
gtfs_home = "<my home station>"
gtfs_work = "<my work station>"
gtfs_data = "/full/path/to/gtfs.zip"Of course, this function will only route using locally-stored data,
so it is up to the user to ensure their local copy of
gtfs.zip is kept up to date.
The functions include one additional feature. Having found the next
service with go_home(), I may suspect that I can keep
working until the following service. The simple parameter
wait enables searching for that following service:
go_home (wait = 1)## route_name trip_name stop_name arrival_time
## 1 U8 S+U Hermannstr. S+U Alexanderplatz (Berlin) [U8] 12:23:30
## 2 U8 S+U Hermannstr. S+U Jannowitzbrucke (Berlin) 12:25:00
## 3 U8 S+U Hermannstr. U Heinrich-Heine-Str. (Berlin) 12:26:30
## 4 U8 S+U Hermannstr. U Moritzplatz (Berlin) 12:28:00
## 5 U8 S+U Hermannstr. U Kottbusser Tor (Berlin) 12:30:00
## 6 U8 S+U Hermannstr. U Schonleinstr. (Berlin) 12:31:30
## 7 U8 S+U Hermannstr. U Hermannplatz (Berlin) 12:33:30
## 8 U8 S+U Hermannstr. U Boddinstr. (Berlin) 12:35:00
## 9 U8 S+U Hermannstr. U Leinestr. (Berlin) 12:36:30
## 10 U8 S+U Hermannstr. S+U Hermannstr. (Berlin) 12:37:30
## 11 S41 S Sudkreuz Bhf S+U Hermannstr. (Berlin) 12:39:24
## 12 S41 S Sudkreuz Bhf S+U Tempelhof (Berlin) 12:43:12
## 13 S41 S Sudkreuz Bhf S Sudkreuz Bhf (Berlin) 12:46:12
## 14 S41 S Sudkreuz Bhf S Schoneberg (Berlin) 12:47:42
## 15 S41 S Sudkreuz Bhf S+U Innsbrucker Platz (Berlin) 12:49:24
## departure_time
## 1 12:23:30
## 2 12:25:00
## 3 12:26:30
## 4 12:28:00
## 5 12:30:00
## 6 12:31:30
## 7 12:33:30
## 8 12:35:00
## 9 12:36:30
## 10 12:37:30
## 11 12:39:54
## 12 12:43:42
## 13 12:46:12
## 14 12:48:12
## 15 12:49:54The service after that can be retrieved with
go_home (wait = 2), and so on.