Abstract
This paper proposed a method of detecting taxi driving anomalous route using the GPS sampling data. After analyzing the characteristics of sampling data, such as discrete and uneven, and taking into account that the traditional anomaly detection methods are hard to be applied directly in this field as well as high computation complexity, the mapping trajectory is defined and the new anomaly detection method is proposed based on the grid concept, which doesn’t require measure the distance or density during anomaly detection procedure and thus alleviates the computing resource requirements. To validate the proposed method, the real-life GPS sampling dataset is used and the experimental results confirm that our proposed method is effective.
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Acknowledgments
This work is supported by the Open Project of Top Key Discipline of Computer Software and Theory in Zhejiang Provincial (ZC323014100, ZC323016038), the Doctoral Research Start-up Fund of Zhejiang Normal University(ZC304016020), Project of Science and Technology Department of Zhejiang Province (2015C33085), besides, we also thank the anonymous reviewers for their constructive suggestions to improve the quality of the paper.
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Ding, Z. (2017). Taxi Driving Anomalous Route Detection Using GPS Sampling Data. In: Yue, D., Peng, C., Du, D., Zhang, T., Zheng, M., Han, Q. (eds) Intelligent Computing, Networked Control, and Their Engineering Applications. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 762. Springer, Singapore. https://doi.org/10.1007/978-981-10-6373-2_31
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DOI: https://doi.org/10.1007/978-981-10-6373-2_31
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