Estimation of traffic congestion level via FN-DBSCAN algorithm by using GPS data
Bildiriler > Tam Metin Bildiri
Yazarlar: Ahmet Can Diker, Elvin Nasibov
2012 IV International Conference "Problems of Cybernetics and Informatics" (PCI), , , Uluslararası, Tam Metin Bildiri, ss 1-4
DOI: 10.1109/icpci.2012.6486279
Özet
Determination of traffic congestion level is one of the fundamental problems in Intelligent Transportation Systems (ITS). In this paper, fuzzy based data mining technique, namely, Fuzzy Neighborhood Density-Based Spatial Clustering of Applications with Noise (FN-DBSCAN) was performed to cluster road segments with traffic congestion level. Data were collected from portable navigation device in probe car on selected roads in Izmir. Six clusters were obtained as a result of experimental study and these clusters were named traffic congestion levels. It is considered that this paper will provide a contribution to related work.