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A comparison and evaluation of map construction algorithms using vehicle tracking data

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Abstract

Map construction methods automatically produce and/or update street map datasets using vehicle tracking data. Enabled by the ubiquitous generation of geo-referenced tracking data, there has been a recent surge in map construction algorithms coming from different computer science domains. A cross-comparison of the various algorithms is still very rare, since (i) algorithms and constructed maps are generally not publicly available and (ii) there is no standard approach to assess the result quality, given the lack of benchmark data and quantitative evaluation methods. This work represents a first comprehensive attempt to benchmark such map construction algorithms. We provide an evaluation and comparison of seven algorithms using four datasets and four different evaluation measures. In addition to this comprehensive comparison, we make our datasets, source code of map construction algorithms and evaluation measures publicly available on http://mapconstruction.org.. This site has been established as a repository for map construction data and algorithms and we invite other researchers to contribute by uploading code and benchmark data supporting their contributions to map construction algorithms.

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Notes

  1. The degree assumption is only a technical requirement for the theoretical quality guarantees, and the authors have shown [3] that similar approximation guarantees appear to hold in practice as well.

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Acknowledgements

This work has been supported by the National Science Foundation grant CCF-1301911, the NGA NURI grant HM02101410004, and the European Union Seventh Framework Programme - Marie Curie Actions, Initial Training Network GEOCROWD (www.geocrowd.eu) under grant agreement No. FP7-PEOPLE-2010-ITN-264994.

We thank James Biagioni for making the source code for the graph sampling-based distance measure [7] available to us, for implementing the map construction algorithms by [8, 11, 16, 17] and for making them publicly available. We thank Xiaoyin Ge and Yusu Wang for running their map construction algorithm [23] on our benchmark datasets. Associated data and software will be made available at mapconstruction.org.

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Authors and Affiliations

  1. University of Texas at San Antonio, San Antonio, TX, USA

    Mahmuda Ahmed

  2. National Technical University of Athens, Athens, Greece

    Sophia Karagiorgou

  3. George Mason University, Fairfax, VA, USA

    Dieter Pfoser

  4. Tulane University, New Orleans, LA, USA

    Carola Wenk

Authors
  1. Mahmuda Ahmed
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  2. Sophia Karagiorgou
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  3. Dieter Pfoser
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  4. Carola Wenk
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Corresponding author

Correspondence to Dieter Pfoser.

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Ahmed, M., Karagiorgou, S., Pfoser, D. et al. A comparison and evaluation of map construction algorithms using vehicle tracking data. Geoinformatica 19, 601–632 (2015). https://doi.org/10.1007/s10707-014-0222-6

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  • DOI: https://doi.org/10.1007/s10707-014-0222-6

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