LiDAR Layered Shape Analysis for Accurate Vehicle Heading
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Solution Overview
Problem
LiDAR systems face reliability issues in autonomous driving due to incorrect information about target vehicles, particularly when selecting inappropriate layers for analyzing point data, which affects the accuracy of object heading determination.
Innovation Solution
A method and device for analyzing object shapes using LiDAR that determine shape flags and confidence scores for each layer, prioritizing shape types like L-shapes and I-shapes based on specific parameters and weights, to accurately determine the object's heading.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple layers of LiDAR points are obtained for object analysis, then the completeness of object shape information is improved, but the complexity of layer selection and shape determination increases
Solution Approach 1:
The patent segments the LiDAR point cloud data into multiple layers based on height information, with each layer representing a different vertical level of the object. This segmentation allows comprehensive capture of object shape information across different heights while enabling independent analysis of each layer's characteristics, thus resolving the contradiction between information completeness and analysis complexity.
Solution Approach 2:
The patent introduces a vertical dimension by dividing the three-dimensional point cloud into multiple horizontal layers at different heights. This dimensional approach allows the system to analyze object shapes at various elevation levels simultaneously, improving shape information completeness while maintaining manageable complexity through layer-by-layer processing.
2Productivity
If a specific layer is selected for heading determination, then the processing efficiency is improved, but the accuracy of heading determination deteriorates if the layer selection is inappropriate
Solution Approach 1:
The patent implements a feedback mechanism where shape flags and confidence scores are calculated for each layer, and this information feeds back into the layer selection process. The system uses the shape analysis results to determine which layer provides the most reliable heading information, ensuring both processing efficiency and accuracy by selecting only the most appropriate layers for final heading determination.
Solution Approach 2:
The patent changes the parameter of layer selection from a static, predetermined choice to a dynamic selection based on calculated confidence scores and shape characteristics. By adjusting the selection criteria according to the actual data quality and shape flags of each layer, the system optimizes both processing efficiency and heading determination accuracy.
3Reliability
If shape flags and confidence scores are calculated for each layer, then the reliability of object shape analysis is improved, but the computational complexity increases
Solution Approach 1:
The patent applies partial action by calculating shape flags and confidence scores for only the necessary layers rather than all possible layers. The system identifies and focuses computational resources on layers that contribute most to accurate shape and heading determination, improving reliability while avoiding unnecessary computational complexity from analyzing all layers equally.
4Measurement precision
If outer points are used for confidence score calculation, then the precision of shape characterization is improved, but the sensitivity to noise and outliers increases
Solution Approach 1:
The patent applies local quality by differentiating the treatment of different points within each layer. Instead of uniformly processing all points, the system specifically identifies and uses outer points (boundary points) for shape characterization while applying different processing to inner points. This localized approach improves shape precision while the confidence score calculation mechanism filters out noisy outer points, reducing sensitivity to outliers.
Data Source
AI summary
The present disclosure relates to a method of analyzing a shape of an object and a device for tracking an object with LiDAR. A method for analyzing a shape of an object by use of LiDAR, according to an embodiment of the present disclosure, comprises obtaining a plurality of layers of LiDAR points for the object by use of the LiDAR, determining a shape flag for each of the layers by use of at least a part of LiDAR points thereon according to a plurality of predetermined shape types, calculating a confidence score for the shape flag determined for each of the layers by use of the at least part of LiDAR points; and determining a shape flag of the object by use of the shape flags determined for the plurality of layers and the confidence scores.