Probe Data Partitioning for Map Matching Accuracy
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Solution Overview
Problem
Conventional digital mapping systems face challenges in keeping up with frequent changes in roadways and traffic routes due to the vast number of miles of roads and ongoing road projects, leading to inaccuracies in route information.
Innovation Solution
A method that partitions probe data into subsets, performs map-matching on each subset, and establishes routes based on the map-matched data, using a predetermined ratio of subsets to determine the most probable route and calculating uncertainty from the remaining subsets to ensure accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional digital mapping systems use static map data, then map data can be updated and revised, but the systems struggle to keep up with frequent changes in roadways and traffic routes due to the vast number of miles of roads and ongoing road projects
Solution Approach 1:
The patent segments the large-scale map data into multiple partitions or zones, allowing parallel processing and updating of different road segments independently. This enables the system to handle frequent roadway changes more efficiently by updating only affected partitions rather than entire map datasets, thus improving both update speed and maintaining reliability.
Solution Approach 2:
The system performs preliminary actions by pre-processing and organizing map data into structured partitions with predefined update mechanisms. This preparation allows rapid response to roadway changes by having the infrastructure ready to accept and integrate probe data quickly, improving productivity while maintaining data reliability.
2Measurement precision
If probe data points are processed individually, then detailed route information can be captured, but the computational complexity and processing time increase significantly
Solution Approach 1:
The patent divides probe data into multiple partitions based on spatial or temporal criteria. Each partition is processed independently through map-matching algorithms, reducing the computational burden on any single processing unit while maintaining overall route determination accuracy. The segmented approach allows parallel processing, decreasing complexity and processing time.
Solution Approach 2:
The system applies partial processing by focusing computational resources on processing subsets of probe data that are most relevant or uncertain. Rather than exhaustively processing every single data point with equal depth, the system strategically processes critical partitions, achieving sufficient accuracy without excessive computational complexity.
3Reliability
If all probe data subsets are used to establish routes, then comprehensive route coverage is achieved, but the uncertainty in route determination increases due to data variability
Solution Approach 1:
The patent selects a predetermined ratio of probe data subsets for route establishment rather than using all available data. This selective approach filters out noisy or less reliable data while maintaining sufficient route coverage. By processing only the necessary proportion of subsets, the system reduces uncertainty in route determination while achieving comprehensive enough coverage for reliable navigation.
Data Source
AI summary
A method is provided for partitioning probe data into a plurality of subsets, map matching a portion of the subsets and establishing a route based on the map-matched subsets of probe data. A method is provided that includes: receiving probe data points from a plurality of probes, where an uncertainty of the measurement of the probe data is a first distance; partitioning the probe data from the plurality of probes into subsets of probe data, where the subsets are created by ensuring each subset has probe data points that are at least two times the first distance apart from one another; performing map-matching on each subset of probe data; and establishing a route for each subset based on the map-matching of each subset of probe data. Establishing a route for each subset may include determining a route according to at least one of the shortest, fastest, or simplest routes.