, Volume 19, Issue 3, pp 601–632 | Cite as

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

  • Mahmuda Ahmed
  • Sophia Karagiorgou
  • Dieter PfoserEmail author
  • Carola Wenk


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 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.


Tracking data Map construction Quality measures Algorithms Performance 



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 ( 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


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Mahmuda Ahmed
    • 1
  • Sophia Karagiorgou
    • 2
  • Dieter Pfoser
    • 3
    Email author
  • Carola Wenk
    • 4
  1. 1.University of Texas at San AntonioSan AntonioUSA
  2. 2.National Technical University of AthensAthensGreece
  3. 3.George Mason UniversityFairfaxUSA
  4. 4.Tulane UniversityNew OrleansUSA

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