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

Map construction methods automatically produce and/or update road network 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 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 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. Mahmuda Ahmed University of Texas at San Antonio San Antonio, TX, USA E-mail: [email protected] Sophia Karagiorgou National Technical University of Athens, Greece E-mail: [email protected] Dieter Pfoser George Mason University Fairfax, VA, USA E-mail: [email protected] Carola Wenk Tulane University New Orleans, LA, USA E-mail: [email protected] ar X iv :1 40 2. 51 38 v1 [ cs .C G ] 1 9 Fe b 20 14 2 Mahmuda Ahmed et al.