Geospatial Feature Hashing for Consistent Road Network Maps
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Solution Overview
Problem
Existing mapping technologies face challenges in maintaining consistency and efficiency in identifying and managing geospatial features across diverse maps, leading to navigation errors and limitations in spatial analysis and decision-making.
Innovation Solution
A system and method that uses spatial analysis and similarity analysis to assign geospatial hashes to identical features across maps, incorporating location, attributes, and temporal information, ensuring consistent representation and enabling efficient route planning and temporal tracking of road network changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional mapping technologies are used to manage geospatial features, then map generation is possible, but consistency and accuracy in identifying identical features across diverse maps deteriorates
Solution Approach 1:
The patent creates a virtual copy of the road network through graph data structures that replicate spatial and topological relationships. This virtual model allows consistent identification of geospatial features across different map versions without relying on direct geographic coordinates, thereby improving both accuracy and consistency.
Solution Approach 2:
The patent introduces an intermediary layer between geographic coordinates and feature identification through the use of graph data structures and virtual road network models. This intermediary enables consistent feature matching across diverse maps by translating geographic references into graph-based identifiers that remain stable across time and version changes.
2Measurement precision
If manual methods are used to manage geospatial features, then detail accuracy is maintained, but processing time and efficiency deteriorate
Solution Approach 1:
The patent replaces manual feature identification and matching processes with automated computational algorithms that process graph data structures. The system automatically compares graph representations of road networks, identifies identical features through algorithmic analysis, and updates maps without human intervention, thereby maintaining accuracy while dramatically reducing processing time.
Solution Approach 2:
The system performs self-service by automatically detecting and correcting inconsistencies in geospatial features across multiple maps. The automated algorithms independently analyze graph data, identify matching features, and update map representations without requiring manual verification or intervention, enabling rapid processing while maintaining high accuracy.
3Adaptability or versatility
If diverse maps are created to represent the same area, then comprehensive coverage is achieved, but complexity in managing and comparing features increases
Solution Approach 1:
The patent creates a universal graph data structure that serves multiple functions: representing the road network topology, enabling feature identification, facilitating map comparisons, and supporting version management. This single multi-functional framework handles diverse map representations without increasing complexity, as all operations reduce to graph theoretical operations on the unified structure.
Solution Approach 2:
The patent segments the road network into discrete graph elements (nodes and edges) that can be independently managed and compared across different maps. This segmentation allows complex map comparisons to be broken down into simple element-by-element comparisons, reducing overall management complexity while maintaining comprehensive coverage through the segmented representation.
Data Source
AI summary
Disclosed apparatuses and methods for identifying map geospatial features include a processor operable to extract, through spatial analysis, geospatial features from map data of a road network at a location, determine, through a similarity analysis, whether two or more of the geospatial features have an identical score beyond an identical score threshold, in response to determining that the identical score of the two or more of the geospatial features is beyond the identical score threshold, assign the shared geospatial hash to the two or more geospatial features in maps of the road network. The geospatial features include the location, geospatial attributes, topological attributes, classification attributes, and temporal information.