Discovery of convoys in trajectory databases

Hoyoung Jeung, Man Lung Yiu, Xiaofang Zhou, Christian S. Jensen, Heng Tao Shen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

345 Citations (Scopus)

Abstract

As mobile devices with positioning capabilities continue to proliferate, data management for so-called trajectory databases that capture the historical movements of populations of moving objects becomes important. This paper considers the querying of such databases for convoys, a convoy being a group of objects that have traveled together for some time. More specifically, this paper formalizes the concept of a convoy query using density-based notions, in order to capture groups of arbitrary extents and shapes. Convoy discovery is relevant for reallife applications in throughput planning of trucks and carpooling of vehicles. Although there has been extensive research on trajectories in the literature, none of this can be applied to retrieve correctly exact convoy result sets. Motivated by this, we develop three efficient algorithms for convoy discovery that adopt the wellknown filter-refinement framework. In the filter step, we apply linesimplification techniques on the trajectories and establish distance bounds between the simplified trajectories. This permits efficient convoy discovery over the simplified trajectories without missing any actual convoys. In the refinement step, the candidate convoys are further processed to obtain the actual convoys. Our comprehensive empirical study offers insight into the properties of the paper's proposals and demonstrates that the proposals are effective and efficient on real-world trajectory data.
Original languageEnglish
Pages (from-to)1068-1080
Number of pages13
JournalProceedings of the VLDB Endowment
Volume1
Issue number1
DOIs
Publication statusPublished - 1 Jan 2008
Externally publishedYes

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computer Science(all)

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