High-Definition Map Building Using Key Node Layer
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Solution Overview
Problem
The high cost and large data volume of existing high-definition maps hinder their efficient loading and usage, particularly in navigation systems requiring lane-level precision for automatic driving, due to their complex and redundant data structures.
Innovation Solution
A method and apparatus that reduce the complexity of high-definition maps by introducing a key node layer based on key positions of lane attribute changes, allowing for the creation of a high-definition map with reduced data volume and production costs, utilizing key nodes such as lane start and end points, change points, and virtual lane lines to provide lane-level navigation information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a high-definition map is constructed with complete lane-level information and detailed road features, then navigation precision and automatic driving support are improved, but data volume increases to terabyte level or higher
Solution Approach 1:
The patent segments the high-definition map into two layers: a navigation map layer containing road-level information and a key node layer containing lane-level key position information. This segmentation allows the system to store only critical lane attributes at key nodes rather than complete lane geometry data, reducing data volume from terabyte level to manageable levels while maintaining lane-level navigation precision through selective key node representation
Solution Approach 2:
The patent extracts only the essential key node information (lane start/end points, lane change points, intersection points) from the complete lane-level map data and stores it separately in the key node layer. This extraction approach removes redundant detailed lane geometry while preserving the critical positional and attribute information needed for lane-level navigation and automatic driving, significantly reducing the overall data volume
2Loss of information
If a high-definition map includes comprehensive road details such as pedestrian crosswalks, flyovers, and traffic lights, then map information richness is improved, but production costs and data processing complexity increase
Solution Approach 1:
The patent applies local quality by storing detailed road sign information and lane attributes only at key nodes where such information is most critical for navigation decisions, rather than uniformly across the entire map. This allows comprehensive road details to be preserved at strategically important locations while avoiding redundant storage elsewhere, reducing overall map structure complexity while maintaining information completeness where needed
3Measurement precision
If complete lane-level map data is stored for every road segment, then navigation accuracy is improved, but loading speed and usage efficiency deteriorate due to large data volume
Solution Approach 1:
The patent segments map data into navigation-level and lane-level components stored in separate layers. The key node layer contains only essential lane position and attribute data at critical points, enabling the system to load and process lane-level information much faster while maintaining navigation accuracy through the structured key node representation that can be efficiently queried and interpolated
Data Source
AI summary
A high-definition map building method includes determining a key node describing information about a key position of a lane attribute change, determining a key node layer based on a position of the key node and an attribute of the key node, and determining a high-definition map based on a navigation map and the key node layer. The navigation map provides road-level navigation information, and the high-definition map provides lane-level navigation information.