Abstract: With the rapid development of location-based service technology, a huge amount of vehicle trajectory data has been generated. To effectively compress and query large-scale vehicle trajectory data, this paper proposes a path spatial queries algorithm for compressed vehicle trajectories. The algorithm compresses the spatial data of trajectories based on the Stroke road hierarchical structure, compresses the temporal data of trajectories by extracting the key variable speed points, and constructs a hash coding for establishing the connection between trajectory spatial data and trajectory temporal data, so as to realize the integrated compression of spatio-temporal data of vehicle trajectories. The suffix array is used to construct the spatial index structure of the compression coding based on the Stroke segment of the vehicle trajectories. On this basis, the point information query algorithm, strict path query algorithm and similar path query algorithm of the corresponding path of vehicle trajectories are designed. The experimental results indicate that for the original trajectory point spatial data, the compression ratio of the proposed compression coding method can reach 97∶1. Compared with the conventional road segments-based coding mode, the proposed compression coding method has high path spatial queries performance. In the point information query of the path corresponding to the vehicle trajectory, the query efficiency can be increased by about 2 times. In the strict sub-path query of the vehicle trajectory, the query efficiency can be increased by about 8 times, and the growth rate of the query time is reduced by about 50% in the similar path query of the vehicle trajectory. This method plays a fundamental role in the data management of large-scale vehicle trajectories.

Key words: trajectory compression, Stroke hierarchical structure, strict path query, similar path query