In this paper we propose a map matching method to overcoming the limitations of standard best-match recon- struction strategies. We use a more flexible approach which consider the k-optimal alternative paths to reconstruct the trajectories from the GPS raw data. The preliminary results, obtained on a real dataset of car users in Milan area, suggest that our method leads to beneficial effects on the successive analysis to be performed such as KNN and clustering

K-BestMatch reconstruction and comparison of trajectory data

Nanni M;Trasarti R
2009

Abstract

In this paper we propose a map matching method to overcoming the limitations of standard best-match recon- struction strategies. We use a more flexible approach which consider the k-optimal alternative paths to reconstruct the trajectories from the GPS raw data. The preliminary results, obtained on a real dataset of car users in Milan area, suggest that our method leads to beneficial effects on the successive analysis to be performed such as KNN and clustering
2009
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-1-4244-5384-9
Spatio-temporal data
map matching
clustering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/58571
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