Topological Map Matching With Separate Criteria for Complex Roads
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing navigation systems face challenges in accurately matching a device's current position to an electronic map due to dual uncertainty and inaccuracy in position samples and digital map representations, particularly in complex urban areas and highways with parallel or stacked roads.
Innovation Solution
A method and system that maintain a pool of candidate paths by expanding them based on positional data samples, identifying the best match to determine the device's estimated position on the electronic map, incorporating topological information to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional map matching algorithms are used, then the system can process position samples, but accuracy deteriorates in complex urban areas and highways with parallel or stacked roads due to dual uncertainty and inaccuracy
Solution Approach 1:
The patent segments the road network into discrete topological elements (nodes and segments) and processes position samples through multiple independent matching criteria (geometric distance, topological consistency, kinematic plausibility) rather than treating the map as a single unified structure. This segmentation allows the system to evaluate different aspects of position accuracy separately and combine results to overcome the limitations of any single criterion in complex environments with parallel or stacked roads.
2Measurement precision
If more position data samples are processed, then map matching accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing the road network into a topological structure with nodes and segments, and by pre-defining multiple matching criteria before position sample processing begins. This preliminary structuring allows the system to efficiently evaluate position samples against predetermined geometric, topological, and kinematic constraints without performing complex calculations in real-time, thus improving accuracy while managing computational complexity.
3Measurement precision
If multiple matching criteria are used, then map matching accuracy improves in complex environments, but the system complexity increases
Solution Approach 1:
The patent changes the parameters used for map matching by introducing multiple independent criteria (geometric distance, topological consistency, kinematic plausibility) instead of relying on a single parameter. Each criterion evaluates different aspects of position accuracy, and their combined results provide more robust matching in complex environments. The system manages the increased complexity by structuring these parameter evaluations as separate, modular assessments that can be independently computed and then integrated.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
An advanced map matching algorithm is disclosed, which embeds the road topology inherently in a set of path candidates. Road connectivity is maintained even in special situations such as U-turns, reverse driving, and tunnels. Careful path candidate management is designed to reduce the candidate count while preserving well-matching candidates. Paths are treated and evaluated independently using multiple criteria, which makes the algorithm reliable and robust in different scenarios.