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  1. Proceedings of the 7th ACM SIGSPATIAL International Workshop on Computational Transportation Science (IWCTS '14)
  2. Euler histogram tree: a spatial data structure for aggregate range queries on vehicle trajectories
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NormSTAD flight analysis: visualizing air traffic patterns over the United States
Sensor-based trip-separation method based on ergodic HMM
Euler histogram tree: a spatial data structure for aggregate range queries on vehicle trajectories
Deriving driver-centric travel information by mining delay patterns from single GPS trajectories
Better transit routing by exploiting vehicle GPS data
Realtime response of shortest path computation
TeleAgro+: analysis framework for agricultural telematics data
A before and after study for travel time of unconventional intersections using probe data
Toward dynamic path recommender system based on social network data
A marketplace for spatio-temporal resources and truthfulness of its users
UPDetector: sensing parking/unparking activities using smartphones

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Euler histogram tree: a spatial data structure for aggregate range queries on vehicle trajectories

Content Provider ACM Digital Library
Author Trajcevski, Goce Scheuermann, Peter Tanin, Egemen Fanaeepour, Maryam Xie, Hairuo Kulik, Lars
Abstract 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 consistently outperforms the leading histogram-based approach.
Starting Page 18
Ending Page 24
Page Count 7
File Format PDF
ISBN 9781450331388
DOI 10.1145/2674918.2674921
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2014-11-04
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Aggregate query Spatial histogram Hierarchical data structure
Content Type Text
Resource Type Article
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