Abstract
Trajectory prediction (TP) of moving objects has grown rapidly to be a new exciting paradigm. However, existing prediction algorithms mainly employ kinematical models to approximate real world routes and always ignore spatial and temporal distance. In order to overcome the drawbacks of existing TP approaches, this study proposes a new trajectory prediction algorithm, called HDTP (Hotspot Distinct Trajectory Prediction). It works as: (1) mining the hotspot districts from trajectory data sets; (2) extracting the trajectory patterns from trajectory data; and (3) predicting the location of moving objects by using the common movement patterns. By comparing this proposed approach to E3TP, the experiments show HDTP is an efficient and effective algorithm for trajectory prediction, and its prediction accuracy is about 14.7% higher than E3TP.
Supported by the National Science Foundation of China under Grant No.60773169,the 11th Five Years Key Programs for Sci. and Tech. Development of China under grant No.2006BAI05A01, the National Science Foundation for Post-doctoral Scientists of China under Grant No.20090461346.
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Li, H., Tang, C., Qiao, S., Wang, Y., Yang, N., Li, C. (2010). Hotspot District Trajectory Prediction. In: Shen, H.T., et al. Web-Age Information Management. WAIM 2010. Lecture Notes in Computer Science, vol 6185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16720-1_7
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DOI: https://doi.org/10.1007/978-3-642-16720-1_7
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