Track compression method and device

Abstract

The invention discloses a track compression method. Aiming at the defects in the prior art, the solution thought of the method is to globally optimize a feature trajectory sub-chain obtained by simplifying and compressing a line segment based on a global optimization thought, and comprehensively consider various influence factors such as a deviation angle, a vertical Euclidean distance, a trajectory segmentation number and the like; evaluation indexes capable of comprehensively reflecting space and time characteristics of a compression result are established, so that the contradiction between the compression efficiency and effective information retention and the contradiction between the compression efficiency and the original track as similar as possible are well balanced. The invention further discloses a track compression device. Compared with the prior art, the method and the device have the advantages that off-line compression that all tracks contain a large amount of effective information and are high in accuracy can be achieved, and the accuracy and efficiency of overall operation of track compression are improved.

Description

technical field [0001] The invention relates to the technical field of big data processing, in particular to a trajectory compression method. Background technique [0002] With the rapid development of Location Based Services (LBS), Global Navigation Satellite System (GNSS) and Internet of Things (IoT), as well as the continuous popularization of mobile smart terminals, residents have accumulated a massive amount of travel. Movement trajectory data, which brings huge data foundation and application prospects for in-depth mining of potentially valuable travel information. The scale of moving trajectory data has increased exponentially, resulting in the consumption of a large amount of data storage resources, and the performance of analysis based on massive moving trajectory data has declined. Therefore, trajectory compression has become one of the current research hotspots. [0003] Trajectory compression is the premise of travel information mining, which helps managers unde...

AI Technical Summary

Problems solved by technology

On the one hand, line segments are processed offline, and important attribute information is seldom mined, resulting in trajectory feature distortion. Since different attribute information has different influences on trajectory compression and changes accordingly, only a single feature cannot fully measure the trajectory, which in turn affects the trajectory. Compression accuracy

On the other hand, offline compression relies on manual input parameters, but in practical applications, due to insufficient experience to set appropriate parameter thresholds, the expected compression effect cannot be achieved

There is a lack of gradual change analysis of trajectory point motion characteristic parameters, failure to establish an adaptive dynamic optimization model for trajectory internal and overall key characteristic parameters, and little research on the construction of multidimensional utility evaluation objective functions based on trajectory compression

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