Optimization and Evaluation of a High-Performance Open-Source Map-Matching Implementation

Conference paper
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Map matching, i.e. matching a moving entity’s position trajectory to an underlying transport network, is a crucial functionality of many location-based services. During the last decade, numerous map-matching algorithms have been proposed, tackling challenging aspects like sparse trajectory data or online matching. This work describes GraphiumMM, an open-source map-matching implementation combining and optimizing geometrical and topological matching concepts from previous works. The implementation aims at highly accurate and performant map matching in online and offline mode taking trajectories with average sampling intervals between 1 and 120 s as input. For evaluating its runtime performance and matching quality, results are compared to results from the open-source map-matcher Barefoot. Results indicate better matching quality and runtime performance especially for sampling intervals from 1 to 15 s in offline and online mode.

Keywords

Map matching Trajectories Evaluation Open source 

Notes

Acknowledgements

This work has been partly funded by the Austrian Ministry for Transportation, Innovation and Technology (bmvit).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Salzburg Research Forschungsgesellschaft mbHSalzburgAustria

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