Road network matching method, device and equipment and storage medium

Abstract

The embodiment of the invention discloses a road network matching method, device and equipment and a storage medium. When to-be-processed track data is collected for road network matching, a spatial index can be generated according to multiple track points included in the to-be-processed track data, and the spatial index reflects position information of line segments formed by the multiple track points; therefore, the candidate road network set corresponding to the to-be-processed trajectory data can be obtained according to the spatial index. The candidate road network set comprises a plurality of road networks, and the plurality of road networks have high possibility to be matched with the to-be-processed track data. And the matching probability of the to-be-processed trajectory data andthe road networks in the candidate road network set is is determined, and further a target road network matched with the to-be-processed trajectory data is determined according to the matching probability. Visibly, complete road network data does not need to be loaded in advance, the candidate road network set is selected by utilizing the spatial index, a road network matched with newly collectedand stored track data can be calculated and solved in real time in a light-weight and rapid manner, the used calculation resources are very small, and the calculation efficiency is improved.

Description

technical field [0001] The present application relates to the field of data processing, in particular to a road network matching method, device, equipment and storage medium. Background technique [0002] In today's era, digital maps are becoming more and more important for everyone. digitally Figure 1 Generally, it is constructed based on the trajectory data collected by the car driving on the road. Usually, the collected trajectory data can be matched with the stored road network data, and the current digital map can be detected, supplemented and updated according to the matching results. . [0003] At present, when performing road network matching, road network data and batch trajectory data to be calculated are loaded, and the road network and road network coverage matched by the trajectory data are calculated offline in batches through artificial intelligence (AI) and other models. [0004] However, this method takes a long time to load road network data and requires...

AI Technical Summary

Problems solved by technology

[0004] However, this method takes a long time to load road network data and requires a large amount of resources. Various AI model algorithms are relatively heavy, suitable for offline batch calculations, and it is difficult to achieve lightweight and real-time road network matching.

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