Gtfsrouter
Routing and analysis engine for GTFS (General Transit Feed Specification) data
Install / Use
npx skills add UrbanAnalyst/gtfsrouterInstalls into whichever agent you are using.
README
gtfsrouter <a href='https://UrbanAnalyst.github.io/gtfsrouter/'><img src='man/figures/logo.png' align="right" height=210 width=182/></a>
R package for public transport routing with GTFS (General Transit Feed Specification) data.
Installation
You can install latest stable version of gtfsrouter from CRAN with:
install.packages ("gtfsrouter")
Alternatively, the current development version can be installed using any of the following options:
# install.packages("remotes")
remotes::install_git ("https://git.sr.ht/~mpadge/gtfsrouter")
remotes::install_git ("https://codeberg.org/UrbanAnalyst/gtfsrouter")
remotes::install_bitbucket ("urbananalyst/gtfsrouter")
remotes::install_gitlab ("UrbanAnalyst/gtfsrouter")
remotes::install_github ("UrbanAnalyst/gtfsrouter")
To load the package and check the version:
library (gtfsrouter)
packageVersion ("gtfsrouter")
## [1] '0.1.4.8'
Main functions
The main functions can be demonstrated with sample data included with
the package from Berlin (the “Verkehrverbund Berlin Brandenburg”, or
VBB). GTFS data are always stored as .zip files, and these sample data
can be written to the temporary directory (tempdir()) of the current R
session with the function berlin_gtfs_to_zip().
filename <- berlin_gtfs_to_zip ()
print (filename)
## /tmp/RtmpTnlacm/vbb.zip
For normal package use, filename will specify the name of a local GTFS
.zip file.
gtfs_route
Given the name of a GTFS .zip file, filename, routing is as simple
as the following code:
gtfs <- extract_gtfs (filename)
gtfs <- gtfs_timetable (gtfs, day = "Wed") # A pre-processing step to speed up queries
gtfs_route (gtfs,
from = "Tegel",
to = "Berlin Hauptbahnhof",
start_time = 12 * 3600 + 120
) # 12:02 in seconds
gtfs_traveltimes
The gtfs_traveltimes()
function`
calculates minimal travel times from any nominated stop to all other
stops within a feed. It requires the two parameters of start station,
and a vector of two values specifying earliest and latest desired start
times. The following code returns the fastest travel times to all
stations within the feed for services which leave the nominated station
(“Alexanderplatz”) between 12:00 and 13:00 on a Monday:
gtfs <- extract_gtfs (filename)
gtfs <- gtfs_timetable (gtfs, day = "Monday")
x <- gtfs_traveltimes (gtfs,
from = "Alexanderplatz",
start_time_limits = c (12, 13) * 3600
)
The function returns a simple table detailing all stations reachable with services departing from the nominated station and start times:
head (x)
Further details are provided in a separate vignette.
gtfs_transfer_table
Feeds should include a “transfers.txt” table detailing all possible
transfers between nearby stations, yet many feeds omit these tables,
rendering them unusable for routing because transfers between services
can not be calculated. The gtfsrouter package also includes a
function,
gtfs_transfer_table(),
which can calculate a transfer table for a given feed, with transfer
times calculated either using straight-line distances (the default), or
using more realistic pedestrian times routed through the underlying
street network.
This function can also be used to enable routing through multiple adjacent or overlapping GTFS feeds. The feeds need simply be merged through binding the rows of all tables, and the resultant aggregate feed submitte
Related Skills
ai-context-hierarchy
10Three-level context hierarchy for AI coding agents — featured in Graphify v5.0 roadmap. Stop re-explaining your codebase every session. Works with Claude Code, Cursor, Codex, Gemini CLI, Claude Desktop.
sm
🌊 **Scrum Master** | Facilitator > Use for user story creation from PRD, story validation and completeness checking, acceptance criteria definition, story refinement, sprint planning, backlog grooming, retrospectives, daily standup facilitation, and local branch management (create/switch/list/delet…
product-manager-skills
138PM skill for Claude Code, Codex, Cursor, and Windsurf: diagnose SaaS metrics, critique PRDs, plan roadmaps, run discovery, and coach PM career transitions.
openclaw-4656-a-b-rollout-governance
A/B Rollout Governance for product management execution
