A direction-sensing k-nearest neighbor inquiry method of the road network moving object

Abstract

A direction-sensing k-nearest neighbor inquiry method of the road network moving object comprises the following steps: step 1, evaluating the inquiry range; 2, constructing a local road network; 3, expanding that direction perceived road network; 4, iteratively expanding the query range; The invention loads a local road network from the road network and predicts the road network distance from thelocal road network node to the inquiry point, thereby realizing the high efficiency of the algorithm. The invention considers the relatively stable 'static' characteristic of the road network and thefrequently updated 'dynamic' characteristic of the moving object, and combines R-Tree efficient and stable query performance and grid index update insensitive characteristics, reasonable use of R-Treeindex road network data, simple grid index moving object, dual index structure to achieve the purpose of rapid updating and efficient query.

Description

technical field [0001] The invention relates to a query method for k nearest neighbors of a mobile object in a road network. Background technique [0002] With the widespread popularity of smart mobile devices and the rapid development of location-based services (Location-based Services, LBS), more and more applications use spatial database technology to meet people's various needs. As one of the most basic query types in spatial databases, k-nearest neighbor query is widely used in real life. For example, the user searches for the nearest k cars to rent a car through taxi-hailing software, which is a typical application of k-nearest neighbor query technology. [0003] K-nearest neighbor query has experienced from simple static object query based on Euclidean distance to complex mobile object query based on road network distance. However, most of the existing k-nearest neighbor queries use distance as the only selection criterion for neighbor objects, without considering t...

AI Technical Summary

Problems solved by technology

Among the few query methods that consider the movement direction of moving objects, most of them are based on Euclidean distance query processing, which cannot judge whether the moving object is moving towards the query point on a large-scale and complex road.

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