Skip to main content

Match a trace of locations to a map

Project description

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

example

Reference:

Meert Wannes, Mathias Verbeke, “HMM with Non-Emitting States for Map Matching”, European Conference on Data Analysis (ECDA), Paderborn, Germany, 2018.

Installation and usage

$ pip install leuvenmapmatching

More information and examples:

leuvenmapmatching.readthedocs.io

Dependencies

Required:

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

  • matplotlib: For visualisation

  • smopy: For visualisation

  • nvector: For latitude-longitude computations

  • gpxpy: To import GPX files

  • pykalman: So smooth paths using a Kalman filter

  • pyproj: To project latitude-longitude coordinates to an XY-plane

  • rtree: To quickly search locations

Contact

Developed with the support of Elucidata.be.

License

Copyright 2015-2018, KU Leuven - DTAI Research Group, Sirris - Elucidata Group
Apache License, Version 2.0.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

leuvenmapmatching-0.5.2.tar.gz (2.8 MB view hashes)

Uploaded Source

Built Distribution

leuvenmapmatching-0.5.2-py3-none-any.whl (69.3 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page