Intelligent sampling-based map data detection method and apparatus

Abstract

The invention relates to the technical field of map data processing and discloses an intelligent sampling-based map data detection method and apparatus. The method comprises the steps of receiving a target parameter of a detection sample set; according to the target parameter and current map data, calculating an optimal proportion; according to priories and connectivity of roads in the current map data, performing traversal, selecting the roads meeting the optimal proportion, and adding the selected roads to the detection sample set one by one; and performing field detection on the traversed roads in the detection sample set. According to the method and the apparatus, an optimal sampling result / target is obtained by automatically performing overall planning and calculation, and the roads which should be extracted are automatically reversely deduced according to the result / target, so that highly intelligent sampling detection is realized, the process is efficient and accurate, and map data detection closest to an objective ideal state can be realized.

Description

technical field [0001] The invention relates to the technical field of map data processing, in particular to a method and device for intelligently sampling and detecting map data. Background technique [0002] Due to the lack of resolution and image recognition capabilities of current satellite images, map data in the prior art (including traditional paper maps and electronic maps, etc.) still rely heavily on manual acquisition to a large extent. For example, in the complex environment of the city, to achieve ideal precision and recognition accuracy, a huge amount of data needs to be collected, which can only be collected manually at present. Professionals carry necessary equipment, take vehicles, boats and other vehicles or walk on the road network to collect information such as the shape of the road network (through GPS points), traffic signs on the road, and road attributes. [0003] In this case, the detection of map data that requires higher data quality can only be do...

AI Technical Summary

Problems solved by technology

Due to the huge amount of data, manual sampling cannot intuitively and accurately judge whether the extracted results meet expectations, nor can it judge whether the current sample is the optimal result. It can only rely on experience or through statistics to check the road ratio of each grade of the sampled roads. Artificial To judge whether the extraction result meets the extraction target

Therefore, the sampling detection of map data in the prior art has defects such as low efficiency, low precision, and inconsistent standards / results.

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