Map Creation Device Reducing Data Volume via Shared Attributes
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Solution Overview
Problem
Existing map technologies are not highly accurate enough to support safe and efficient operation of automated vehicles, as they lack detailed features necessary for precise navigation and data processing, and are not easily adaptable for use in both automated and non-automated systems.
Innovation Solution
A method and device that read in highly accurate map features, determine shared map feature attributes based on geometric and topological characteristics, and create a map with reduced complexity for use in both automated and non-automated systems, allowing for efficient data processing and operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If highly accurate map features with detailed geometric and topological data are used, then navigation precision and automated vehicle operation safety are improved, but data volume and processing complexity increase
Solution Approach 1:
The patent extracts only the essential geometric and topological features from highly accurate map data to create shared map feature attributes. This selective extraction maintains the necessary precision for automated vehicle navigation while significantly reducing the overall data volume by omitting redundant detailed information.
Solution Approach 2:
The map data is segmented into distinct feature types (geometric attributes, topological attributes, and shared attributes). This segmentation allows the system to process and store only the essential characteristics needed for both automated and non-automated vehicle operations, reducing processing complexity while maintaining accuracy.
2Measurement precision
If highly accurate map features with detailed data are used, then navigation precision is improved, but processing complexity and computational requirements increase
Solution Approach 1:
The patent extracts only the essential geometric and topological features from highly accurate map data to create shared map feature attributes. This selective extraction maintains the necessary precision for automated vehicle navigation while significantly reducing the overall data volume by omitting redundant detailed information.
Solution Approach 2:
The map data is segmented into distinct feature types (geometric attributes, topological attributes, and shared attributes). This segmentation allows the system to process and store only the essential characteristics needed for both automated and non-automated vehicle operations, reducing processing complexity while maintaining accuracy.
3Productivity
If maps are created with reduced data volume for non-automated vehicles, then processing efficiency is improved, but navigation accuracy for automated vehicles deteriorates
Solution Approach 1:
The patent creates shared map feature attributes that serve dual purposes: they provide sufficient detail for automated vehicle navigation while being computationally efficient for non-automated vehicle systems. This multi-functional attribute structure allows a single map representation to satisfy both accuracy and efficiency requirements.
Solution Approach 2:
The patent transforms detailed geometric and topological map features into simplified shared attributes by changing the representation parameters. This transformation maintains the essential spatial relationships and characteristics needed for accurate navigation while reducing the computational complexity for processing in both automated and non-automated systems.
4Manufacturing precision
If detailed geometric and topological map features are processed, then map accuracy is improved, but creation time and computational resources increase
Solution Approach 1:
The patent transforms detailed geometric and topological map features into simplified shared attributes by changing the representation parameters. This transformation maintains the essential spatial relationships and characteristics needed for accurate navigation while reducing the computational complexity for processing in both automated and non-automated systems.
Solution Approach 2:
The patent performs preliminary processing of map features to extract and store shared geometric and topological attributes in advance. This preliminary action prepares the data structure so that both highly accurate and simplified map representations can be quickly generated when needed, reducing real-time processing requirements.
Data Source
AI summary
In a method and a device for creating and providing a map, a highly accurate map that includes multiple highly accurate map features is obtained, a shared map feature attribute is determined as a function of the multiple highly accurate map features, a derivative map is created as a function of the shared map feature attribute, and the map is output.