Conference Proceedings

Euler Histogram Tree: A Spatial Data Structure for Aggregate Range Queries on Vehicle Trajectories

Hairuo Xie, Egemen Tanin, Lars Kulik, Peter Scheuermann, Goce Trajcevski, Maryam Fanaeepour, X Chen (ed.)

Proceedings of the 7th ACM SIGSPATIAL International Workshop on Computational Transportation Science | ACM | Published : 2014


This work addresses the problem of aggregation of trajectories data. Specifically, we propose a tree-based data structure for counting vehicle trajectories by mapping them into a set of spatial histograms with different granularities. We also present an approach for processing spatio-temporal range queries by aggregating the histograms in the query rectangles. The proposed methodology can be used for preserving the privacy of vehicle drivers by maintaining aggregated trajectory data. In addition, as we show, it can be used to handle the well-known distinct counting problem. Experimental results show that the new data structure achieves a high level of accuracy in query results and consistent..

View full abstract

Citation metrics