zaciid / pyraptor

Python implementation of RAPTOR algorithm

PyRaptor

Python implementation of RAPTOR and McRAPTOR using GTFS data. Tested on Dutch GTFS data.

This repository contains four applications:

1. pyraptor/gtfs/timetable.py - Extract the timetable information for one operator from a GTFS dataset and write it to an optimized format for querying with RAPTOR.
2. pyraptor/query_raptor.py - Get the best journey for a given origin, destination and desired departure time using RAPTOR
3. pyraptor/query_range_raptor.py - Get a list of the best journeys to all destinations for a given origin and desired departure time window using RAPTOR
4. pyraptor/query_mcraptor.py - Get a list of the Pareto-optimal journeys to all destinations for a given origin and a departure time using McRAPTOR
5. pyraptor/query_range_mcraptor.py - Get a list of Pareto-optimal journeys to all destinations for a given origin and a departure time window using McRAPTOR

Installation

Install from PyPi using pip install pyraptor or clone this repository and install from source using pip.

Example usage

1. Create timetable from GTFS

python pyraptor/gtfs/timetable.py -d "20211201" -a NS --icd

2. Run (range) queries on timetable

Quering on the timetable to get the best journeys can be done using several implementations.

RAPTOR query

RAPTOR returns a single journey with the earliest arrival time given the query time.

Examples

python pyraptor/query_raptor.py -or "Arnhem Zuid" -d "Oosterbeek" -t "08:30:00"

python pyraptor/query_raptor.py -or "Breda" -d "Amsterdam Centraal" -t "08:30:00"

rRAPTOR query

rRAPTOR returns a set of best journeys with a given query time range. Journeys that are dominated by other journeys in the time range are removed.

Examples

python pyraptor/query_range_raptor.py -or "Arnhem Zuid" -d "Oosterbeek" -st "08:00:00" -et "08:30:00"

python pyraptor/query_range_raptor.py -or "Breda" -d "Amsterdam Centraal" -st "08:00:00" -et "08:30:00"

McRaptor query

McRaptor returns a set of Pareto-optimal journeys given multiple criterions, i.e. earliest arrival time, fare and number of trips.

Examples

python pyraptor/query_mcraptor.py -or "Breda" -d "Amsterdam Centraal" -t "08:30:00"

python pyraptor/query_mcraptor.py -or "Vlissingen" -d "Akkrum" -t "08:30:00"

python pyraptor/query_mcraptor.py -or "Obdam" -d "Akkrum" -t "08:30:00" -r 7

rMcRaptor query

Range version of McRaptor, i.e. it returns a set of Pareto-optimal journeys within a departure time window.

Examples

python pyraptor/query_range_mcraptor.py -or "Breda" -d "Amsterdam Centraal" -st "08:15:00" -et "08:30:00"

python pyraptor/query_range_mcraptor.py -or "Vlissingen" -d "Akkrum" -st "08:15:00" -et "08:30:00"

python pyraptor/query_range_mcraptor.py -or "Obdam" -d "Akkrum" -st "08:00:00" -et "09:00:00"

Notes

• The current version doesn't implement target pruning as we are interested in efficiently querying all targets/destinations after running RAPTOR algorithm.

References

Round-Based Public Transit Routing, Microsoft.com, Daniel Delling et al

Raptor, another journey planning algorithm, Linus Norton

Dutch GTFS feed, Transit Feeds