Spatial Data Structures for Efficient Trajectory-Based Queries

Spatial queries involving trajectories of moving objects a re fundamental in a variety of domains. For example, we may wish to determine which points o r regions to which an object passes “close.” In this paper, we consider a largescale version of this type of problem. Given many trajectories and spatial regions, we want to efficiently find all pairs of regions and trajectories such that the trajectory p asses through the region. Below we present several data structures and algorithms to e fficiently solve this problem. We adapt data structures and algorithms from track ing and computer graphics to work on higher dimensional data sets with nonlinear tr cks. These algorithms provide a significant speedup over a simple brute force appro ach. We also introduce a new data structure and algorithm that can significantly outp erform previous approaches for queries with many tracks. Further, we introduce a novel d ual-tree approach that combines the advantages of both an observation-based data s tructure and a track-based data structure to provide consistently good performance ov er a wide range of queries.