Review of the Research Progresses in Trajectory Clustering Methods
Luo Ming · 地理科学进展 · 2011
A trajectory is a sequence of the location and timestamp of a moving object.It is not only an impor-tant type of spatio-temporal data,but also a critical source of information.Extracting patterns from different tra-jectory data can help people understand the drives and outcomes of individual and collective spatial dynamics,such as human behavior patterns,transport and logistics,emergency evacuation management,animal behavior,and marketing.Recently,a larger number of trajectory data are available for analyzing the temporal and spatial pattern,as the result of the improvements of tracking facilities and sensor networks.Therefore,clustering analy-sis needs to be used to find the implicit patterns in it.Based on the characteristics and the similarity measure-ments of trajectory data,this paper reviewed the research progresses in trajectory clustering methods.Firstly,the significance of research on trajectory data and its clustering methods was presented.Then the definition,models as well as several visualization methods of trajectories were summarized.After that,the authors classified the ex-isting trajectory clustering methods into 6 main categories according to the similarity measurement of them,and analyzed each of the trajectory clustering methods,along with their respective pros and cons by category.Final-ly,some research challenges and future directions were discussed.