An application-oriented multi-granularity vehicle trajectory data indexing structure based on concept lattice

Tao Xu; Zixiang Zhang; Xiaqing Ma; Jiaming Deng; Yingying Zhao; Xiang Li

doi:10.1117/12.2656783

20 October 2022 An application-oriented multi-granularity vehicle trajectory data indexing structure based on concept lattice

Tao Xu, Zixiang Zhang, Xiaqing Ma, Jiaming Deng, Yingying Zhao, Xiang Li

Author Affiliations +

Proceedings Volume 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022); 1245136 (2022) https://doi.org/10.1117/12.2656783
Event: 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 2022, Chongqing, China

Abstract

Massive amount of vehicle trajectory data is an important data source and has been widely used in many research fields. However, due to the huge volume and variety of application scenarios, it is still not easy to achieve the application-oriented and efficient retrieval of vehicle trajectory. The paper proposes a multi-granularity vehicle trajectory index method based on the concept lattice model. The method identifies the multi-granularity feature regions for application requirements to segment vehicle trajectory and employs the concept lattice model to maintain the complex relationships between vehicle trip and the feature regions, to realize the vehicle travel trajectory data retrieval for the multi-granularity feature regions. In this experiment, shanghai city is divided into 21 feature regions according to the county-level area of Shanghai, and the concept lattice index structure of vehicle trips is constructed. The availability and efficiency of the proposed method are verified by the comparative experimental results.

Citation Download Citation

Tao Xu, Zixiang Zhang, Xiaqing Ma, Jiaming Deng, Yingying Zhao, and Xiang Li "An application-oriented multi-granularity vehicle trajectory data indexing structure based on concept lattice", Proc. SPIE 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 1245136 (20 October 2022); https://doi.org/10.1117/12.2656783

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