Map Data Correction via Coordinate Transformation
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Solution Overview
Problem
Existing map data systems face challenges in maintaining accurate position coordinates due to crustal movements, leading to errors that are not cost-effectively corrected, especially when used for self-driving applications where precision is critical.
Innovation Solution
A map data providing system that uses a vehicle unit to detect position deviations, calculate correction amounts, and update reference point coordinates dynamically, allowing for continuous correction of map data without the need for frequent re-surveying.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If map data is updated by performing communication between center and navigation device, then map data can be updated to reflect changed portions, but position coordinate errors due to crustal movements are not effectively corrected
Solution Approach 1:
The patent replaces traditional mechanical surveying methods with a computational approach using coordinate transformation formulas. Instead of physically re-surveying locations, the system uses mathematical transformations (Equation 1 and Equation 2) to calculate corrected map data from reference point coordinates and deviation amounts, substituting mechanical measurement with computational processing.
Solution Approach 2:
The navigation device performs self-correction of map data by calculating deviation amounts between actual positions and map data positions, then applying correction amounts to generate corrected map data. This self-service mechanism eliminates the need for frequent external surveying operations while maintaining position precision.
2Measurement precision
If frequent re-surveying is performed to correct position coordinates, then position accuracy is maintained, but costs associated with data updates and surveying work increase
Solution Approach 1:
The patent performs preliminary coordinate transformation calculations to establish the relationship between actual positions and map data positions. By pre-calculating deviation amounts and correction amounts, the system prepares correction data that can be applied without requiring frequent re-surveying, thus reducing surveying costs while maintaining precision.
Solution Approach 2:
The system creates corrected map data as a computational copy of the original map data, transformed using coordinate transformation formulas. This copying approach allows the system to generate updated position information without physically re-surveying locations, significantly reducing surveying costs while maintaining accuracy.
3Loss of information
If absolute coordinates are used for all map elements, then position information is complete, but data processing complexity and correction requirements increase
Solution Approach 1:
The patent segments map data into multiple sections, each with its own reference point. This segmentation allows the system to manage coordinate transformations locally for each section rather than processing all map elements globally, reducing data processing complexity while maintaining complete position information through the use of relative coordinates within each section.
Solution Approach 2:
The system applies different coordinate systems to different parts of the map data: absolute coordinates for reference points and relative coordinates for map elements within each section. This local quality approach optimizes data processing by using relative coordinates for most elements while maintaining absolute position accuracy through reference points, reducing overall processing complexity.
Data Source
AI summary
A map data providing system stores map data including multiple section data in which a reference point indicated by absolute coordinates is set for each of multiple sections, and a map element is represented by relative coordinates to the reference point of the section to which the map element belongs, detects position coordinates of the vehicle based on a navigation signal, employs a difference between absolute coordinates of the map element indicated by the map data and absolute coordinates of the map element identified based on the relative position of the map element and the position coordinates of the vehicle as a deviation amount, calculates a correction amount based on the deviation amount, corrects the position information of the reference point by using the correction amount, and creates corrected map data indicating position coordinates of the map element.