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A feature based method for trajectory dataset segmentation and profiling

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Abstract

The pervasiveness of location-acquisition and mobile computing techniques has generated massive spatial trajectory data, which has brought great challenges to the management and analysis of such a big data. In this paper, we focus on the sub-trajectory dataset profiling problem, and aim to extract the representative sub-trajectories from the raw trajectory as a subset, called profile, which can best describe the whole dataset. This problem is very challenging subject to finding the most representative sub-trajectories set by trading off the size and quality of the profile. To tackle this problem, we model the features of the trajectory dataset from the aspects of density, speed and the direction flow. Meanwhile we present our two-step method to select the representative trajectories based on the feature model. First, a novel trajectory segmentation algorithm is applied on a raw trajectory to identify the representative segments concerning their feature representativeness and automatically estimate the number of segments and the segment borders. Then, a sub-trajectory profiling method is performed to yield the most representative sub-trajectories in the dataset, based on a local heuristic evolution strategy. We evaluate our method based on extensive experiments by using two real-world trajectory datasets generated by over 12,000 taxicabs in Beijing and Shanghai. The results demonstrate the efficiency and effectiveness of our methods in different applications.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant Nos. 61572335, 61402312, and 61402313, the Natural Science Foundation of Jiangsu Province of China under Grant No. BK20151223, the Natural Science Foundation of Jiangsu Provincial Department of Education of China under Grant No. 12KJB520017, and Collaborative Innovation Center of Novel Software Technology and Industrialization, Jiangsu, China.

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Authors and Affiliations

  1. Soochow University, Suzhou, 215006, People’s Republic of China

    Wei Jiang, Jie Zhu, Jiajie Xu, Zhixu Li, Pengpeng Zhao & Lei Zhao

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  1. Wei Jiang
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  2. Jie Zhu
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  3. Jiajie Xu
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  4. Zhixu Li
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  5. Pengpeng Zhao
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  6. Lei Zhao
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Correspondence to Lei Zhao.

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Jiang, W., Zhu, J., Xu, J. et al. A feature based method for trajectory dataset segmentation and profiling. World Wide Web 20, 5–22 (2017). https://doi.org/10.1007/s11280-016-0396-y

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