Road Lane Elevation Processing Using Point Cloud Confidence Fusion
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Solution Overview
Problem
Current trajectory-based road network matching methods for elevation information processing in high-precision maps suffer from inaccuracies due to the limited information in vehicle trajectories and GPS positioning errors, making it difficult to improve the upper limit of accuracy.
Innovation Solution
An elevation information processing method that utilizes point cloud recognition to determine sampling points, performs plane fitting to remove noise, and fuses candidate elevation values based on confidence to optimize effective elevation values, leveraging topological relationships between roads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If trajectory-based road network matching method is used for elevation processing, then processing can be automated, but accuracy is limited by GPS positioning errors and trajectory information scarcity
Solution Approach 1:
The patent introduces point cloud data as an intermediary to bridge the gap between trajectory-based automation and accurate elevation measurement. Point cloud recognition results serve as a mediator that provides rich spatial information without relying solely on GPS trajectories, enabling both automation and high precision simultaneously
Solution Approach 2:
The patent transitions from one-dimensional trajectory data to three-dimensional point cloud data. By utilizing spatial points with coordinates (x, y, z) and their topological relationships, the system gains additional dimensional information that enables accurate elevation extraction while maintaining automated processing
2Extent of automation
If GPS positioning is used for elevation estimation, then automation is achieved, but measurement precision deteriorates due to installation location variations and positioning errors
Solution Approach 1:
The patent creates a digital copy of the physical environment through point cloud recognition. Instead of relying on direct GPS measurements that suffer from installation location variations, the system constructs a virtual representation of the road surface and its elevation characteristics, enabling automated processing with high precision
Solution Approach 2:
The patent replaces the mechanical GPS positioning system with a vision-based point cloud recognition system. By substituting mechanical positioning with optical/electromagnetic field-based recognition, the system eliminates the limitations of GPS while maintaining automation
3Device complexity
If trajectory information is used for elevation processing, then processing simplicity is maintained, but information completeness deteriorates due to limited trajectory data
Solution Approach 1:
The patent merges trajectory information with point cloud recognition results to create a comprehensive elevation processing system. By combining the simplicity of trajectory-based processing with the information richness of point cloud data, the system achieves both processing simplicity and information completeness
Data Source
AI summary
An elevation information processing method includes: sampling lane data of a road in a target region to obtain a plurality of sampling points; determining, from a plurality of point cloud recognition results, a plurality of sample points and candidate elevation values for each of the plurality of elevation values, the candidate elevation values for a sampling point forming a candidate elevation value set; fitting the plurality of sampling points to obtain a fitting result, and determining one or more target sampling points in the plurality of sampling points based on the fitting result; and for a candidate elevation value set of each target sampling point: determining a confidence of each candidate elevation value in the candidate elevation value set of the target sampling point, and determining an effective elevation value of the target sampling point based on the confidence of each candidate elevation value.