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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.
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
$ pip install leuvenmapmatching
More information and examples:
leuvenmapmatching.readthedocs.io
Required:
Optional (only loaded when methods are called to rely on these packages):
Wannes Meert, DTAI, KU Leuven
wannes.meert@cs.kuleuven.be
https://dtai.cs.kuleuven.be
Mathias Verbeke, Sirris
mathias.verbeke@sirris.be
http://www.sirris.be/expertise/data-innovation
Developed with the support of Elucidata.be.
Copyright 2015-2022, KU Leuven - DTAI Research Group, Sirris - Elucidata Group
Apache License, Version 2.0.
FAQs
Match a trace of GPS positions to a locations and streets on a map
We found that leuvenmapmatching demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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