Map Validation Test Generation via Route Segmentation
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Solution Overview
Problem
As autonomous vehicles rely on accurate maps for navigation, there is a need for automated validation of new and updated maps to ensure compatibility and safety, especially as the geographic regions they operate in expand.
Innovation Solution
A system that automatically generates map validation tests by segmenting routes into multiple test route subsections, identifying corresponding road features, and simulating an autonomous vehicle traversing these features to create validation tests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual validation testing is performed for new and updated maps, then validation thoroughness may be maintained, but time consumption and labor resources increase significantly
Solution Approach 1:
The system creates virtual copies of autonomous vehicles and road features in a simulated environment. Instead of physically testing with real vehicles, the system generates digital replicas that can be tested repeatedly and rapidly, significantly reducing validation time while maintaining thoroughness through multiple simulation iterations.
Solution Approach 2:
The system performs validation testing before actual map deployment. By segmenting routes into subsections and pre-identifying road features, the system conducts preliminary validation that catches issues early, preventing costly post-deployment problems while reducing overall validation time through proactive testing.
2Reliability
If comprehensive route validation is performed, then navigation safety improves, but computational resources and processing time increase
Solution Approach 1:
The system divides comprehensive route validation into smaller, manageable test route subsections. Each subsection is validated independently by identifying specific road features within it, reducing computational complexity while maintaining overall navigation safety through cumulative validation coverage.
Solution Approach 2:
The system focuses validation efforts on critical road features and high-risk route subsections rather than uniformly validating every segment. This partial action approach concentrates computational resources on areas most affecting navigation safety, reducing overall system complexity while maintaining adequate validation thoroughness.
3Productivity
If automated validation testing is implemented, then validation efficiency increases, but test accuracy and thoroughness may decrease
Solution Approach 1:
The system uses high-fidelity virtual copies of road features and vehicle behavior in simulation environments. These digital replicas maintain sufficient accuracy to detect real validation issues while enabling rapid automated testing, thus preserving measurement precision while dramatically improving validation efficiency.
Solution Approach 2:
The automated validation system incorporates feedback mechanisms where test results inform subsequent testing iterations. The system analyzes simulation outcomes to identify patterns, refine test cases, and focus future validation on problematic areas, maintaining high accuracy while sustaining automated efficiency through continuous improvement.
Data Source
AI summary
Systems and methods are provided for validating a map via automatic test generation for multiple test route subsections. Autonomous vehicles required accurate maps. As such, new maps may be added and/or maps map be updated frequently. Verifying these maps requires testing. Maps may be validated via automatic test generation by obtaining route information identifying a route in the map for an autonomous vehicle. The route may be segmented into multiple test route subsections. Features corresponding to one or more of the test route subsections may be identified. One or more validation tests corresponding to the test route subsections may be generated based on a simulated autonomous vehicle traversing the one or more road features. For example, multiple validation tests for corresponding test route subsections may be generated and executed in parallel.