Uncertain Moving Range Query Techniques in Road Networks

Gu, Yu; Guo, Na; Yu, Ge

doi:10.3724/sp.j.1001.2013.04320

Cited by 1 publication

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“…Hua and Pei [31] considered the spatial query problem based on the assumption of uncertain network edge weights on road network. On the basis of the general probability distribution function, Gu et al [32] proposed a probabilistic query incremental processing model and a query optimization method based on the segmentation interval.…”

Section: Index For Range Query Based On Processing Batchmentioning

confidence: 99%

A Hybrid Aggregate Index Method for Trajectory Data

Shi

Huang

Zheng

et al. 2019

Mathematical Problems in Engineering

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The aggregate query of moving objects on road network keeps being popular in the ITS research community. The existing methods often assume that the sampling frequency of the positioning devices like GPS or roadside radar is dense enough, making the result’s uncertainty negligible. However, such assumption is not always tenable, especially in the extreme occasions like wartime. Regarding this issue, a hybrid aggregate index framework is proposed in this paper, in order to perform aggregate queries on massive trajectories that are sampled sparsely. Firstly, this framework uses an offline batch processing component based on the UPBI-Sketch index to acquire each object’s most likely position between two continuous sampling instants. Next, it introduces the AMH+-Sketch index to processing the aggregate operation online, making sure each object is counted only once in the result. The experimental results show that the hybrid framework can ensure the query accuracy by adjusting the parameters L and U of AMH+-Sketch index and its space storage advantage becomes more and more obvious when the data scale is very large.

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Section: Index For Range Query Based On Processing Batchmentioning

confidence: 99%