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

被引：0

作者：

Diker, Ahmet Can ^{[1
]}

Nasibov, Elvin ^{[2
]}

机构：

[1] Dokuz Eylul Univ, Izmir, Turkey

[2] Ege Univ, Izmir, Turkey

来源：

2012 IV INTERNATIONAL CONFERENCE PROBLEMS OF CYBERNETICS AND INFORMATICS (PCI) | 2012年

关键词：

data mining; clustering; FN-DBSCAN; intelligent transportation systems; traffic congestion;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页数：4

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