Application of spatial data mining for traffic management: case study of a city of Calgary street

The flow of data coming from modern sensing devices enables the development of novel research techniques related to data management and knowledge extraction. In this research, the investigation is on the analysis of traffic movement in a road network using the density based clustering algorithm, DBSCAN. The objective of this research is to present a methodology that can aid city authorities in the optimization of traffic flow by identifying congestion within the street network. In this paper, it has been focused on the spatial characteristics of traffic movement, which provides insight into the flow of traffic within the street network. A case study was conducted to illustrate the use of densitybased cluster analysis. Experimental results illustrate the applicability and usefulness of the proposed approach.

کلیدواژه ها:

Spatial data mining ، DBSCAN ، Traffic management ، clustering.