130 lines
4.9 KiB
Markdown
130 lines
4.9 KiB
Markdown
[](geo/schweiz_ex.png?raw=true)
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*Left: station-to-station path of a single train through Switzerland obtained from official schedule data. Right: path of the same train map-matched by pfaedle.*
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[](geo/stuttgart_ex.png?raw=true)
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*Left: station-to-station path of a single bus through Stuttgart obtained from official schedule data. Right: path of the same bus map-matched by pfaedle.*
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[](https://travis-ci.org/ad-freiburg/pfaedle)
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# pfaedle
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Precise map-matching for public transit schedules ([GTFS](https://developers.google.com/transit/gtfs/reference/) data).
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Implementation and evaluation code for our paper [Sparse Map-Matching in Public Transit Networks with Turn Restrictions](http://ad-publications.informatik.uni-freiburg.de/SIGSPATIAL_Sparse%20map%20matching%202018.pdf).
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## Requirements
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* `cmake`
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* `gcc >= 4.9` (or `clang >= 5.0`)
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## Building and Installation
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Fetch this repository and init submodules:
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```
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git clone --recurse-submodules https://github.com/ad-freiburg/pfaedle
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```
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```
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mkdir build && cd build
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cmake ..
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make -j
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```
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To install, type
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```
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make install
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```
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# General Usage
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## Generating shapes for a GTFS feed
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```
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pfaedle -x <OSM FILE> <GTFS INPUT FOLDER>
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```
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A shape'd version of the input GTFS feed will be written to `./gtfs-out`.
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By default, shapes are only calculated for trips that don't have a shape in the
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input feed. To drop all existing shapes, use the `-D` flag.
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For example, you may generate (and replace existing, see -D parameter) shapes for the GTFS dataset for Freiburg like this:
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```
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$ wget https://fritz.freiburg.de/csv_Downloads/VAGFR.zip && unzip VAGFR.zip
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$ wget http://download.geofabrik.de/europe/germany/baden-wuerttemberg/freiburg-regbez-latest.osm.bz2 && bunzip2 freiburg-regbez-latest.osm.bz2
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$ pfaedle -D -x freiburg-regbez-latest.osm .
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```
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## Generating shapes for a specific MOT
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To generate shapes for a specific mot only, use the `-m` option. Possible
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values are either `tram`, `bus`, `coach`, `rail`, `subway`, `ferry`, `funicular`,
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`gondola`, `all` (default) or GTFS vehicle type codes (0, 1, 2, 3, 4, 5, 6, 7).
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Multiple values can be specified (comma separated).
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## OSM filtering
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`pfaedle` comes with the ability to filter OpenStreetMap data. If you specify
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the `-X` flag, `pfaedle` will filter the input OSM file and output a new OSM
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file which contains exactly the data needed to calculate the shapes for the
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input GTFS feed and the input configuration.
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This can be used to avoid parsing (for example) the entire `planet.osm` on each
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run.
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## Debugging
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The following flags may be useful for debugging:
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* `-T <GTFS TRIP ID>` only calculate shape for a single trip (specified via its GTFS trip id) and output it as GeoJSON to
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`<dbg-path>/path.json`
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* `--write-graph` write the graph used for routing as GeoJSON to
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`<dbg-path>/graph.json`
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* `--write-cgraph` if `-T` is set, write the combination graph used for
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routing as GeoJSON to `<dbg-path>/combgraph.json`
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* `--write-trgraph` write the complete network graph to `<dbg-path>/trgraph.json`
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# Configuration
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A default configuration file `pfaedle.cfg` can be found in this repo and will be installed with `make install`. Custom configuration files can be specified with the `-c` flag. If no `-c` flag is set, `pfaedle` will parse and merge the following cfg files in the given order (if present): `<install prefix>/etc/pfaedle/pfaedle.cfg`, `$HOME/.config/pfaedle/pfaedle.cfg`, `<CWD>/pfaedle.cfg`. Values given in later files will overwrite earlier defined values.
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# Evaluation
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You may run an entire evaluation of our testing datasets Vitoria-Gasteiz, Paris, Switzerland and
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Stuttgart with
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```
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mkdir build && cd build
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cmake ..
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make -j
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make eval
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```
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*Notes:*
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* this will download, and filter, the entire OSM files for Spain and the
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Stuttgart region. Make sure you have enough space left on your hard drive.
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* in evaluation mode, pfaedle needs significantly more time, because the
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calculation of the similarity measurements between shapes are expensive
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* if you are only interested in the end results of a single dataset, run
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`make <dataset>.lighteval` in `/eval`. For example, `make paris.lighteval`
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generates a shaped version of the paris dataset, without doing extensive
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comparisons to the ground truth.
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* similarily, if you want to run the extensive evaluation for a single dataset,
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run `make <dataset>.eval` in `/eval`.
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## Evaluation requirements
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* zlib
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On Debianesque systems, type
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```
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sudo apt-get install zlib1g-dev
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```
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to install the dependencies.
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