Abstract: Clustering results often depend on density and similarity critically, and its complexity often changes along with the augment of sample dimensionality. This paper refers to classical shared nearest neighbor clustering algorithm (SNN) and refined shared nearest neighbor clustering algorithm (RSNN). By applying this RSNN algorithm on freeway traffic data set, we settled several problems existed in SNN algorithm, such as outliers, statistic, core points, computation complexity and so on. Experiment results prove that this refined algorithm has better clustering results on multi-dimensional data set than SNN algorithm.