Estimation of Traffic Congestion Level via FN-DBSCAN Algorithm by Using GPS Data


Diker A. C., Nasibov E.

4th International Conference on Problems of Cybernetics and Informatics (PCI), Baku, Azerbaycan, 12 - 14 Eylül 2012, (Tam Metin Bildiri)

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/icpci.2012.6486279
  • Basıldığı Şehir: Baku
  • Basıldığı Ülke: Azerbaycan
  • Anahtar Kelimeler: data mining, clustering, FN-DBSCAN, intelligent transportation systems, traffic congestion
  • Dokuz Eylül Üniversitesi Adresli: Evet

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.