Method and system for preprocessing multi-road segment data of lane line crowdsourcing data

Abstract

The present invention relates to a method and system for preprocessing multi-road segment data of lane line crowdsourcing data. The method includes: step 1, according to the size of an axial coordinate of the shape points in a single lane line in the road segment data Sort; step 2, judge shape point p n Whether the difference between the direction of the point and the connection direction of the head and tail points exceeds the set threshold; yes, delete the point p n+1 , no, add 1 to n; among them, the shape point p n The direction of the shape point p n and shape point p n+1 The connection direction of the line; step 3, execute step 2 in a loop until the value of n is the total number of shape points, and perform linear fitting optimization on the shape points of each lane line respectively. Sorting the shape points in each lane line according to the collinear relationship between points, filtering out abnormal outliers, effectively preprocessing the lane line data collected by crowdsourcing collection vehicles, and improving the efficiency of subsequent optimization processing Effect and efficiency, in order to obtain high-precision lane line map data that meets the accuracy requirements.

Description

technical field [0001] The present invention relates to the field of high-precision maps, in particular to a method and system for preprocessing multi-road segment data of lane line crowdsourcing data. Background technique [0002] In the field of autonomous driving, in order to accurately control the driving of vehicles, the drawing of high-precision maps is often involved. High-precision maps can be drawn after long-term data collection by expensive surveying and mapping vehicles. However, due to high costs, long collection periods, and slow update The reason is that it is difficult to meet the high freshness requirements of high-precision maps. [0003] Compared with high-precision surveying and mapping vehicles, the cost of crowdsourcing collection vehicles is lower, and it is more suitable for extensive deployment to collect high-quality data and improve the update frequency of high-precision maps. Large and often wrong data points cannot be directly used for optimizat...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the technical problems existing in the prior art, the present invention provides a preprocessing method and system for multi-road segment data of lane line crowdsourcing data, and solves the problem of low accuracy of crowdsourcing data in the prior art

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