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Semi-automatic point cloud method for making three-dimensional high-definition road map lane line

A lane line, semi-automatic technology, applied in the semi-automatic point cloud field of making 3D high-definition road map lane lines, to achieve the effect of reducing data complexity and calculation costs, overcoming uncertainty, and reducing time consumption

Pending Publication Date: 2018-11-27
厦门维斯云景信息科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there are still no or very few algorithms that can produce accurate and efficient results from large-scale data sets, and most methods still require some manual work
Therefore, creating 3D HD roadmaps for autonomous vehicles remains a big challenge

Method used

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  • Semi-automatic point cloud method for making three-dimensional high-definition road map lane line
  • Semi-automatic point cloud method for making three-dimensional high-definition road map lane line
  • Semi-automatic point cloud method for making three-dimensional high-definition road map lane line

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Experimental program
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Embodiment

[0058] Before describing this embodiment in detail, it should be pointed out that the semi-automatic point cloud method for making lane lines on a 3D high-definition road map provided by this embodiment is a semi-automatic method, using the roads in the 3D point cloud to create a road map .

[0059] see figure 1 , the invention provides a semi-automatic point cloud method for making lane lines of a three-dimensional high-definition road map, comprising the following steps:

[0060] S1. Preprocessing, transforming the coordinate system and removing non-ground points on the point cloud data to obtain ground points.

[0061] This step is specifically implemented through the following steps:

[0062] S11. Coordinate system transformation. The MLS system utilizes a right-handed orthogonal coordinate system with an arbitrary user-defined orientation and origin. Such a random coordinate system makes it more difficult to plot the relative positions of points. To reduce the comple...

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Abstract

The invention discloses a semi-automatic point cloud method for making a three-dimensional high-definition road map lane line. The which semi-automatic point cloud method comprises the following steps: S1, pre-processing, performing coordinate system transformation and non-ground point removal on point cloud data, and obtaining ground points; S2, performing road edge detection according to the obtained ground points, obtaining road boundaries and road surface points; S3, extracting road identifiers according to the obtained road surface points, wherein the road identifiers include arrows, symbols, and lane identifiers; S4, determining a centerline of the lane on the basis of the extracted lane identifiers; S5, and creating a 3D road map with the road boundaries, the lane identifiers, and the lane centerlines. The method can reduce the computational complexity and time cost of road surface identifier extraction, and improve the accuracy of creating a 3D high-definition road map of self-driving vehicles.

Description

technical field [0001] The invention relates to the field of unmanned vehicle navigation, in particular to a semi-automatic point cloud method for making lane lines of a three-dimensional high-definition road map. Background technique [0002] The automotive industry is rapidly evolving towards autonomous vehicles. The 3D high-definition road map is the most powerful tool to help self-driving vehicles plan the correct driving strategy. 3D HD roadmaps could ease the burden of self-navigation for self-driving vehicles by helping the car's computer estimate the route it will take and improving the vehicle's ability to understand the situation it is facing. Unlike traditional road maps, 3D high-definition road maps can provide lane-level navigation with centimeter-level accuracy. However, there are still no or very few algorithms that can produce accurate and efficient results from large-scale datasets, and most methods still require some manual work. Therefore, creating 3D H...

Claims

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Application Information

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IPC IPC(8): G06T17/20G06T5/00G06T7/13G06T7/181
CPCG06T5/002G06T7/13G06T7/181G06T17/20G06T2207/30108
Inventor 不公告发明人
Owner 厦门维斯云景信息科技有限公司
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