Autonomous Vehicle Scenario Tagging From Log Data Analytics
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Solution Overview
Problem
Current systems for autonomous vehicles lack an efficient method to determine and analyze operating scenarios based on log data, which hinders performance measurement, simulation testing, and fleet management.
Innovation Solution
A computer-implemented method and system that extracts attributes from log data to identify and categorize scenarios, enabling the generation of autonomous vehicle operation analytics, and facilitating scenario-based simulation testing and performance measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual methods are used to analyze autonomous vehicle log data, then detailed scenario analysis can be performed, but the process is time-consuming and resource-intensive
Solution Approach 1:
The patent replaces manual mechanical analysis methods with automated computer-implemented methods. The system automatically extracts attributes from log data, determines scenarios based on attribute combinations, and generates analytics without human intervention, thereby reducing processing time while maintaining analysis accuracy
Solution Approach 2:
The system enables self-service analysis by automatically processing log data through attribute extraction, scenario determination, and analytics generation. The automated pipeline serves the analysis needs without requiring manual human resources, making the process efficient and scalable
2Reliability
If comprehensive log data analysis is performed to identify all scenario variations, then complete performance measurement is achieved, but computational resources and processing complexity increase
Solution Approach 1:
The patent segments the complex analysis task into distinct components: attribute extraction, scenario determination based on attribute combinations, and analytics generation. Each component handles a specific aspect of the analysis, reducing overall system complexity while maintaining comprehensive coverage of scenario variations
Solution Approach 2:
The system changes parameters by extracting specific attributes from log data and using combinations of these attributes to determine scenarios. This parameter-based approach allows comprehensive analysis through structured attribute combinations rather than unstructured data processing
3Measurement precision
If extensive manual labeling of scenario data is performed, then high data quality is achieved, but resource requirements and costs increase
Solution Approach 1:
The patent replaces manual labeling operations with automated computer-implemented processes. The system automatically extracts attributes and determines scenarios from log data without human labeling, eliminating the need for extensive manual resources while maintaining consistent data quality through systematic attribute-based scenario determination
Data Source
AI summary
Systems and methods are directed to determining autonomous vehicle scenarios based on autonomous vehicle operation data. In one example, a computer-implemented method for determining operating scenarios for an autonomous vehicle includes obtaining, by a computing system comprising one or more computing devices, log data representing autonomous vehicle operations. The method further includes extracting, by the computing system, a plurality of attributes from the log data. The method further includes determining, by the computing system, one or more scenarios based on a combination of the attributes, wherein each scenario includes multiple scenario variations and each scenario variation comprises multiple features. The method further includes providing, by the computing system, the one or more scenarios for generating autonomous vehicle operation analytics.