NNCluster: An Efficient Clustering Algorithm for Road Network Trajectories

With the advent of ubiquitous computing, we can easily acquire the locations of moving objects. This paper studies the clustering problem for trajectory data which are constrained by the road network. While many trajectory clustering algorithms have been proposed, they do not consider the spatial proximity over the road network. For such trajectory data, we propose a new distance measure that reflects the spatial proximity of trajectories on the road network, and an efficient clustering method that reduces the number of distance computations during the clustering process. Experimental results demonstrate that our proposed method correctly identifies clusters over the real-life trajectory data yet reduces up to 80% of distance computations from this baseline algorithm.