IIAE CONFERENCE SYSTEM, The 5th IIAE International Conference on Industrial Application Engineering 2017 (ICIAE2017)

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Clustering Methods and Bound Value in Classify Density Traffic Accident Areas
Hsien-Tsung Chang, Hieu Nguyen

Last modified: 2017-02-21


Nowadays, Traffic accidents (TAs) causes a lot of damage in terms of human and asset. TAs records have been stored and published in many Open Data sources. In this article, we propose a method of using clustering algorithm Density-based Spatial Clustering of Applications with Noise (DBSCAN) to classify the TAs’ records in order to find the Density Traffic Accident Areas (DTAA). We also discuss about the optimal variables in DBSCAN that need to consider when applied in real urban areas. We emphasize the characteristics of DTAA by the Bound Value (BV) and modeling some important traffic characteristics. We then evaluate the performance and efficiency between DBSCAN and K-mean clustering methods. The result clusters and characteristics can be easily adapted to real traffic applications for increase the travel safety.


DBSCAN; Traffic Accident; Bound Value; Clustering; Density Traffic Accident Areas.

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