Roadside Key-Point Positioning Data for Low-Volume HD Localization
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Solution Overview
Problem
Existing positioning technologies for vehicles face challenges with large data volumes that are not suitable for storage and usage, particularly in high-precision positioning applications.
Innovation Solution
Extracting laser point data of key points from laser point cloud data, specifically from road objects with stable attributes such as ground markings, road edges, and upright objects, and using these as positioning data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If laser point cloud data is used for high-precision positioning, then positioning accuracy is improved, but data volume increases making storage and usage difficult
Solution Approach 1:
The patent extracts only the essential laser point data representing key features (road edges, ground markings, upright objects) from the complete laser point cloud data. This selective extraction maintains positioning accuracy by preserving critical geometric features while removing redundant information, directly resolving the contradiction between high positioning accuracy and manageable data volume
Solution Approach 2:
The patent segments the road environment into distinct feature categories (road edges, ground markings, upright objects) and processes each segment separately. By dividing the complex point cloud data into manageable feature segments with stable attributes, the system achieves high-precision positioning while reducing overall data complexity and volume
2Reliability
If complete laser point cloud data is stored, then positioning reliability is improved, but storage requirements and processing complexity increase
Solution Approach 1:
The patent applies local quality by focusing processing efforts on specific regions containing stable features (road edges, ground markings, upright objects) rather than processing the entire point cloud uniformly. This localized approach maintains positioning reliability by ensuring critical features are accurately captured while reducing overall processing complexity through selective attention to high-value regions
3Measurement precision
If all road objects are included in positioning data, then positioning accuracy is improved, but data transmission efficiency decreases
Solution Approach 1:
The patent extracts only the essential geometric features of road objects (key points representing road edges, ground markings, and upright objects) rather than transmitting complete object models or full point cloud data. This extraction approach maintains positioning accuracy by preserving critical spatial information while dramatically reducing data transmission volume, thereby improving transmission efficiency
Data Source
AI summary
A positioning data generation method, an apparatus, and an electronic device are provided. The method comprises: obtaining laser point cloud data in a preset regional range on or by either side of the road; extracting laser point data of key points of a target object on or by either side of the road from the laser point cloud data, wherein the target object is a road object with a stable attribute on or by either side of the road; and storing the extracted laser point data of the key points of the target object as a piece of a plurality of pieces of positioning data of the road, the plurality of pieces of positioning data corresponding to a plurality of target objects on or by either side of the road.