https://github.com/wannesm/leuvenmapmatching

Leuven.MapMatching toolbox for aligning GPS measurements to locations on a map.
https://github.com/wannesm/leuvenmapmatching

hmm map-matching non-emitting-states silent-states

Last synced: 4 days ago
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Leuven.MapMatching toolbox for aligning GPS measurements to locations on a map.

• Host: GitHub
• URL: https://github.com/wannesm/leuvenmapmatching
• Owner: wannesm
• License: other
• Created: 2018-07-05T09:40:52.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2024-02-11T19:53:27.000Z (10 months ago)
• Last Synced: 2024-12-11T05:13:03.892Z (11 days ago)
• Topics: hmm, map-matching, non-emitting-states, silent-states
• Language: Python
• Size: 360 KB
• Stars: 228
• Watchers: 5
• Forks: 44
• Open Issues: 29
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Leuven.MapMatching

[![PyPi Version](https://img.shields.io/pypi/v/leuvenmapmatching.svg)](https://pypi.org/project/leuvenmapmatching/)

[![Documentation Status](https://readthedocs.org/projects/leuvenmapmatching/badge/?version=latest)](https://leuvenmapmatching.readthedocs.io/en/latest/?badge=latest)

Align a trace of GPS measurements to a map or road segments.

The matching is based on a Hidden Markov Model (HMM) with non-emitting 

states. The model can deal with missing data and you can plug in custom

transition and emission probability distributions.

![example](http://people.cs.kuleuven.be/wannes.meert/leuvenmapmatching/example1.png?v=2)

Main reference:

> Meert Wannes, Mathias Verbeke, "HMM with Non-Emitting States for Map Matching",

> European Conference on Data Analysis (ECDA), Paderborn, Germany, 2018.

Other references:

> Devos Laurens, Vandebril Raf (supervisor), Meert Wannes (supervisor),

> "Traffic patterns revealed through matrix functions and map matching",

> Master thesis, Faculty of Engineering Science, KU Leuven, 2018

## Installation and usage

    $ pip install leuvenmapmatching

More information and examples:

[leuvenmapmatching.readthedocs.io](https://leuvenmapmatching.readthedocs.io)

## Dependencies

Required:

- [numpy](http://www.numpy.org)

- [scipy](https://www.scipy.org)

Optional (only loaded when methods are called to rely on these packages):

- [matplotlib](http://matplotlib.org):

    For visualisation

- [smopy](https://github.com/rossant/smopy):

    For visualisation

- [nvector](https://github.com/pbrod/Nvector):

    For latitude-longitude computations

- [gpxpy](https://github.com/tkrajina/gpxpy):

    To import GPX files

- [pykalman](https://pykalman.github.io):

    So smooth paths using a Kalman filter

- [pyproj](https://jswhit.github.io/pyproj/):

    To project latitude-longitude coordinates to an XY-plane

- [rtree](http://toblerity.org/rtree/):

    To quickly search locations

## Contact

Wannes Meert, DTAI, KU Leuven  

[email protected]  

https://dtai.cs.kuleuven.be

Mathias Verbeke, Sirris  

[email protected]  

http://www.sirris.be/expertise/data-innovation

Developed with the support of [Elucidata.be](http://www.elucidata.be).

## License

Copyright 2015-2022, KU Leuven - DTAI Research Group, Sirris - Elucidata Group  

Apache License, Version 2.0.