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Addressing the Need for Map-Matching Speed: Localizing Globalb Curve-Matching Algorithms
18th International Conference on Scientific and Statistical Database Management (SSDBM'06)
Tracking data becomes an increasingly available sensor data resource that can be used in a range of applications related to traffic assessment and prediction. Of critical importance in this context is the amount of (i) historic and (ii) current tracking data available (data per spatial area). Using data of varying quality (sampling rate and accuracy) requires sophisticated map-matching algorithms. Having current data requires fast algorithms. Currently only fast Incremental and slow Global
doi:10.1109/ssdbm.2006.11
dblp:conf/ssdbm/WenkSP06
fatcat:xv7gd7c2rbdgvg3ily5u2erjfa