Parallel Road Graph Merging for Wide-Area Coverage
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Solution Overview
Problem
Existing methods for creating road graphs from images face challenges in scalability and efficiency, particularly when merging multiple road graphs to cover wide areas.
Innovation Solution
A computer-implemented method for merging multiple road graphs that partially overlap, involving acquisition, labeling, and parallel merging processes to combine road graphs efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple road graphs are merged sequentially to cover wide areas, then the completeness of the road graph increases, but the processing time increases proportionally
Solution Approach 1:
The patent divides the large-scale road graph merging task into multiple independent groups, where each group processes a subset of road graphs in parallel. This segmentation allows the system to maintain large coverage area while reducing total processing time by eliminating sequential dependencies between groups.
Solution Approach 2:
The patent introduces a grouping dimension to the merging process, transforming it from a single-dimensional sequential operation into a multi-dimensional parallel operation. By organizing road graphs into groups that can be processed simultaneously, the system achieves both wide coverage and efficient processing.
2Productivity
If road graphs are divided into sub-areas for processing, then the processing efficiency improves, but boundary effects and discontinuities occur
Solution Approach 1:
The patent merges overlapping road graphs within each group to eliminate boundary discontinuities. By identifying and combining duplicate or adjacent graph segments, the system maintains continuous road networks across group boundaries while preserving parallel processing efficiency.
Solution Approach 2:
The patent performs preliminary labeling and organization of road graphs into groups before the merging process. This preliminary action ensures that boundary relationships are identified in advance, allowing for seamless integration of sub-area results while maintaining overall graph continuity.
3Manufacturing precision
If the merging process is performed sequentially for all road graphs, then the merging precision is maintained, but the scalability to large areas is limited
Solution Approach 1:
The patent segments the road graph set into multiple independent groups that can be processed in parallel while maintaining merging precision within each group. This segmentation enables scalability to large areas without sacrificing the quality of individual merges.
Solution Approach 2:
The patent uses grouping as an intermediary structure that enables parallel processing while maintaining precision. Each group acts as an independent processing unit with its own merging logic, allowing precise local merges to be combined into a large-scale result without losing accuracy.
Data Source
AI summary
A computer-implemented method for combining a plurality of road graphs that partially overlap with an adjacent area, the method comprising: an acquisition step of acquiring a plurality of road graphs; a labeling step of grouping the plurality of road graphs into groups, and assigning a label to each of the road graphs in each of the groups; and a merging step of selecting one label and executing, in parallel for the groups, a process of merging a first road graph to which the selected label is assigned and a second road graph adjacent to the first road graph, wherein the merging step is repeated, with selecting a different label in each repetition, until all of the plurality of road graphs are merged.