Track compression method and device, storage medium and electronic equipment

Abstract

The invention relates to a track compression method and device, a storage medium and electronic equipment, and relates to the field of application of geographic information systems. The method comprises the following steps of acquiring an azimuth angle of a vehicle at a first sampling moment; when the azimuth angle of the vehicle at the first sampling moment is judged to be within an intersectionof a first safety angle range corresponding to a second sampling moment and a second safety angle range corresponding to a third sampling moment, ignoring a position point of the vehicle at the firstsampling moment; and determining a next sampling moment of the first sampling moment as a new first sampling moment, and re-executing the step of acquiring the azimuth angle of the vehicle at the first sampling moment until the sampling is finished. According to the method, trajectory data can be compressed under a condition that an actual application effect is considered, the redundant data in the trajectory data is eliminated, the storage space consumption of the track data and the storage time consumption are reduced, and a visual effect after the track data is compressed can be guaranteed.

Description

technical field [0001] The present disclosure relates to the application field of geographic information systems, and in particular, relates to a trajectory compression method, device, storage medium and electronic equipment. Background technique [0002] The current online trajectory compression methods usually include the reservoir method and its derived sliding window method (SlidingWindow) and window opening method (Open Window), and the offset method (Threshold-Guided Sampling) of constructing a safe area according to the speed and direction. , SQUISH online compression algorithm and its upgraded SQUISH-E method, etc. These methods are often making different improvements for data compression capabilities, but they do not take the actual application effect into consideration. Therefore, these methods often appear There are many problems, for example, when the current point of a trajectory contains a small amount of information (non-key trajectory point), the current poin...

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Problems solved by technology

[0002] The current online trajectory compression methods usually include the reservoir method and its derived sliding window method (SlidingWindow) and window opening method (Open Window), and the offset method (Threshold-Guided Sampling) of constructing a safe area according to the speed and direction. , SQUISH online compression algorithm and its upgraded SQUISH-E method, etc. These methods are often making different improvements for data compression capabilities, but they do not take the actual application effect into consideration. Therefore, these methods often appear There are many problems, for example, when the current point of a trajectory contains a small amount of information (non-key trajectory point), the current point is discarded according to the above-mentioned methods, and it is not drawn, which negates the data in time and space. The corresponding relationship in two dimensions; secondly, the above-mentioned methods are not good enough for the compression strategy of circular trajectories (such as square turntables, overpass ramps, etc.), and circular trajectories are often compressed into a few points connected by In addition, in the above-mentioned various methods, every time a new data point arrives and data compression is required, all the remaining key trajectory points must be recalculated, which takes too much time. Long, the real-time performance of the compression algorithm cannot be guaranteed when the trajectory is long

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