Digital Road Map Matching with Semantic Object Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for matching digital road maps to digital reference maps are inefficient due to misassociations between objects with different semantic information, leading to inconsistent delta-pose hypotheses.
Innovation Solution
The method employs semantic and geometric information to associate only objects with the same information, using a branch-and-bound-based algorithm with a joint compatibility test to ensure efficient matching, and employs a KD tree for nearest neighbor searches to optimize the process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If semantic information is used to associate objects between road maps, then matching accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by performing semantic filtering and geometric pre-matching before the main association process. Objects are pre-grouped by semantic category and geometric properties, which reduces the search space for subsequent matching operations. This preliminary organization enables accurate semantic-based matching while reducing computational complexity by avoiding exhaustive comparisons across all object pairs.
2Reliability
If all object pairs are evaluated for association, then completeness of matching is improved, but processing time increases
Solution Approach 1:
The patent applies segmentation by dividing the matching process into distinct stages: semantic filtering, geometric pre-matching, and final association evaluation. This segmentation allows the system to quickly eliminate incompatible object pairs through semantic and geometric filters before performing detailed association analysis, thereby maintaining completeness while reducing overall processing time.
Solution Approach 2:
The patent implements partial action by evaluating only those object pairs that pass the semantic and geometric pre-filters, rather than evaluating all possible pairs. This selective evaluation approach maintains matching completeness for valid pairs while significantly reducing processing time by skipping obviously incompatible pairs.
3Measurement precision
If semantic filtering is applied to restrict object associations, then matching quality is improved, but the number of valid associations decreases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the strictness of semantic filtering based on the matching context and confidence levels. The system can modify semantic matching thresholds and geometric tolerance parameters to balance matching quality with the number of valid associations, allowing flexible adaptation to different operational requirements.
Data Source
AI summary
A method for matching a digital road map to a digital reference road map, wherein the two road maps in each case include semantic information about objects represented on the two road maps. The method includes: associating objects on the road map with objects on the reference road map on the basis of the respective semantic information such that only objects with the same semantic information are associated with one another; matching the road map to the reference road map on the basis of the association, wherein the matching comprises creating a delta pose between the road map and the reference road map. A device, a computer program, and a machine-readable storage medium are also described.