HD Map Validation via Parallel Test Case Segmentation
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Solution Overview
Problem
Current HD map validation techniques face inefficiencies due to the need for exhaustive route selection and lack of optimized route validation processes, leading to resource wastage and incomplete map coverage within limited testing time, especially when variability in maps is not considered.
Innovation Solution
A method and system for validating HD maps by generating a map graph, identifying variabilities, and optimizing test cases to execute in parallel execution instances, ensuring full or near-full map validation coverage within reasonable time, using a processor to compare HD maps to schemas, store data, and select optimized test cases based on map features and unvalidated segments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If exhaustive route selection is used for HD map validation, then complete map coverage is achieved, but testing time and resource consumption increase significantly
Solution Approach 1:
The validation process is segmented into multiple execution instances, each handling a subset of test cases. The system divides the comprehensive validation task into manageable chunks that can be processed in parallel, reducing overall testing time while maintaining complete map coverage through coordinated execution of all instances.
Solution Approach 2:
The system performs preliminary analysis to identify map variabilities and generate an optimized set of test cases before execution. By pre-processing the map data to detect variabilities and selecting only the necessary test cases, the system avoids exhaustive testing of all possible routes while ensuring complete validation coverage.
2Productivity
If map variabilities are identified and test cases are optimized, then testing efficiency improves, but system complexity increases
Solution Approach 1:
The system introduces an intermediary component that analyzes map variabilities and generates optimized test case selections. This intermediary layer processes the complex variability detection and test case optimization tasks, shielding the execution instances from complexity while enabling efficient validation through pre-computed optimal test sets.
3Loss of time
If parallel execution instances are used, then testing time is reduced, but coordination and management complexity increases
Solution Approach 1:
The execution instances are designed as universal, multi-functional units that can handle any subset of test cases. Each instance is self-contained and capable of independent execution, allowing flexible parallel processing without complex inter-instance coordination. The standardized interface and uniform structure simplify management while enabling efficient parallel validation.
Data Source
AI summary
Systems and methods for validating maps for use with autonomous vehicles are provided. Variabilities between an HD map and previous versions of the HD map may be identified. Test cases may be generated based on the HD map, testing requirements, and previously validated lane segments. An optimized set of test cases may be selected based on variabilities and unvalidated lane segments in the HD map. The optimized set of test cases may be subdivided among a plurality of execution instances which may be executed in parallel.