Map Quality Verification via Regional Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The implementation of system-level verification testing for high-accuracy maps in autonomous vehicles is too onerous and expensive to be conducted on an ongoing basis, necessitating efficient solutions for map data collection, change detection, and quality assessment.
Innovation Solution
A comprehensive map maintenance and verification system comprising a surveillance system for determining data collection cadence, a change detection system for prioritizing map change signals, and a verification system for assessing map quality, utilizing dynamic statistical models and machine learning algorithms to ensure map accuracy and precision across different geographic regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If system-level verification testing is conducted for high-accuracy maps, then map quality and accuracy are improved, but cost and operational burden increase significantly
Solution Approach 1:
The verification system divides the map into multiple geographic regions and assesses quality metrics for each region separately. This segmentation allows the system to manage verification complexity by handling smaller, manageable portions of the map independently, while still ensuring overall map accuracy through aggregated regional assessments.
Solution Approach 2:
The system determines quality metrics (accuracy, precision, recall) specific to each geographic region rather than applying a uniform verification approach across the entire map. This local quality assessment allows verification resources to be allocated efficiently to regions where they are most needed, reducing overall verification burden while maintaining high accuracy standards.
2Measurement precision
If comprehensive map verification is performed across all geographic regions, then overall map quality is improved, but computational resources and processing time increase
Solution Approach 1:
The map verification process is divided into multiple independent geographic region assessments that can be performed in parallel. Each region's quality metrics are determined separately, allowing computational resources to be distributed across multiple regions simultaneously, thereby reducing total verification time while maintaining comprehensive coverage.
Solution Approach 2:
The system determines quality metrics for each geographic region independently, which may result in some regions receiving more verification attention than strictly necessary. This partial or excessive action ensures that no region is overlooked and overall map quality is maintained, while the modular approach prevents unnecessary verification of already-sufficient regions from dominating the process.
Data Source
AI summary
Techniques are disclosed for evaluating digital map quality. A process includes steps for receiving change data indicating one or more feature discrepancies associated with one or more geographic regions of a digital map, analyzing the change data to determine which of the one or more feature discrepancies resulted in verified updates to the digital map, and generating a quality score for each of the geographic map regions based on the verified updates. Systems and machine-readable media are also provided.