Map Geometry Verification Using Probe Data Statistical Analysis
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Solution Overview
Problem
Digital map geometry anomalies, such as erroneous road segment locations, are time-consuming and costly to correct due to frequent changes in road infrastructure and vast network sizes, making it challenging for mapping services to keep maps up-to-date.
Innovation Solution
A method involving probe data collection and analysis, where probe data points are matched to link segments to calculate differences, determine statistical means, and flag segments for manual review if the differences exceed a calculated error threshold, allowing for automated or semi-automated correction of map geometry anomalies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual correction methods are used for digital map geometry anomalies, then correction accuracy can be ensured, but the time and cost required for maintenance increase significantly
Solution Approach 1:
The system enables self-service by automatically detecting map geometry anomalies through probe data analysis and statistical testing. The automated anomaly detection process compares probe data against map geometry, calculates statistical metrics, and identifies anomalies without requiring continuous manual intervention, thus reducing maintenance time while preserving accuracy through systematic verification
Solution Approach 2:
The patent replaces manual mechanical correction processes with automated computational systems. Statistical tests, probability density calculations, and automated anomaly detection algorithms substitute for manual map verification, significantly reducing the time required while maintaining correction accuracy through rigorous mathematical analysis
2Reliability
If comprehensive manual verification of all road segments is performed, then map accuracy can be maintained, but the complexity and cost of the verification process increase
Solution Approach 1:
The system extracts only the essential statistical metrics needed for anomaly detection from probe data, rather than performing comprehensive verification of all road segments. By calculating specific statistical tests and probability density functions only for segments with potential anomalies, the system maintains reliability while reducing verification complexity
Solution Approach 2:
The patent changes the verification approach from comprehensive geometric checking to statistical parameter analysis. By using statistical metrics, standard deviations, and probability density functions to identify anomalies, the system maintains map accuracy through probabilistic methods while reducing the complexity of verification procedures
3Measurement precision
If statistical analysis with multiple probe data points is used to identify anomalies, then false positives can be reduced, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating statistical metrics and establishing baseline expectations for probe data distribution. By preparing statistical frameworks and probability density functions in advance, the system can quickly evaluate anomalies when probe data arrives, reducing processing time while maintaining detection accuracy through pre-established statistical criteria
Solution Approach 2:
The patent applies partial action by focusing statistical analysis only on road segments where anomalies are suspected based on initial probe data deviations. Rather than analyzing all road segments equally, the system applies rigorous statistical testing only where needed, reducing overall processing time while maintaining high detection accuracy through targeted analysis
Data Source
AI summary
A method is provided for verifying and/or updating map geometry based on a probe data. A method may include: receiving probe data from a plurality of probes within a region, where the probe data includes at least one of heading information and location information for each probe data point; matching the probe data to a link segment to generate map-matched probe data; calculating a difference between the at least one of heading information and location information of the map-matched probe data points and of the link segment; determining a statistical mean of the data; determining an error of the statistical mean of the data; and flagging the link segment for manual review in response to the statistical mean being greater than the error of the statistical mean multiplied by a biasing factor.