Intersection Identification via Road Boundary Topology
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Solution Overview
Problem
Current methods for identifying intersections in electronic maps, such as manual annotation and deep learning, are inefficient and prone to errors due to the need for extensive human intervention and large datasets, leading to low production efficiency and accuracy.
Innovation Solution
A method that acquires boundary information from electronic maps, determines the topological relationship between road boundaries, and identifies the distribution of intersections based on this relationship, reducing the reliance on specific positions and lengths of road boundaries, thereby improving efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual annotation is used to identify intersections in electronic maps, then the accuracy of intersection identification can be ensured, but the production efficiency becomes low due to extensive human intervention
Solution Approach 1:
The system performs self-service by automatically identifying intersections through topological relationship analysis of road boundaries, eliminating the need for manual annotation while maintaining high accuracy. The algorithm independently processes boundary information to determine intersection locations and types.
Solution Approach 2:
The patent replaces the mechanical manual annotation process with an automated computational system that analyzes topological relationships between road boundaries. This substitution eliminates human intervention while preserving identification accuracy through mathematical and logical operations.
2Extent of automation
If machine learning method is used to identify intersections, then the automation level is improved, but a large number of manually annotated samples are still required, resulting in low efficiency and uncertain accuracy
Solution Approach 1:
The patent extracts the essential topological relationship features from road boundary data, separating the critical identification criteria from complex manual annotation processes. By focusing only on topological relationships rather than full manual labeling, the system achieves automation without requiring large annotated datasets.
Solution Approach 2:
The system changes the parameters used for intersection identification from requiring extensive labeled samples to relying on topological relationship parameters such as the number of road boundaries and their spatial relationships. This parameter transformation enables efficient automated processing.
3Loss of information
If traditional methods rely on specific positions and lengths of road boundaries, then detailed information is captured, but the complexity of identification increases and efficiency decreases
Solution Approach 1:
The patent extracts only the essential topological relationship information from road boundaries, removing unnecessary details about specific positions and lengths. This extraction maintains sufficient information for accurate intersection identification while simplifying the data structure for efficient processing.
Solution Approach 2:
The system segments the boundary information into discrete topological relationship elements such as the number of road boundaries and their pairwise relationships. This segmentation transforms continuous geometric data into discrete topological features that are easier and faster to process.
Data Source
AI summary
A method and apparatus for identifying an intersection in an electronic map, and a computer readable medium are provided. An embodiment of the method includes: acquiring boundary information related to road boundaries from an electronic map; determining a topological relationship between the road boundaries in an area having a predetermined size in the electronic map based on the boundary information; and determining a distribution of an intersection in the area based on the topological relationship. The apparatus corresponding to the method, the device implementing the method of the present disclosure, and the computer readable medium are also provided. Through the technical solutions, the intersection may be automatically identified by detecting the road boundaries, which improves the efficiency of producing a high-precision map, and has the advantage of high accurate recall rate, strong universality, or simple method.