Autonomous Vehicle Simulation Divergence Attribution
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Solution Overview
Problem
The existing methods for simulating autonomous vehicle behaviors in a simulated environment are inefficient, requiring extensive manual inspection and resource consumption to identify divergences between simulation results and real-world results, due to the large amount of data generated during testing.
Innovation Solution
A method is introduced to compare the divergence between a baseline simulation and a modified simulation by accessing real-world data and running simulations, where the data is used to troubleshoot the baseline simulation by modifying the simulation template by removing processes and comparing the divergences, thereby isolating the cause of discrepancies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection methods are used to identify divergences between simulation results and real-world results, then measurement precision can be maintained, but time consumption and resource consumption increase significantly
Solution Approach 1:
The patent replaces manual inspection (mechanical human analysis) with automated computational methods. The system uses processing devices to automatically compare simulation outputs with real-world sensor data, identifying divergences through algorithmic analysis rather than human inspection. This substitution maintains measurement precision while dramatically reducing time consumption.
Solution Approach 2:
The patent introduces an intermediary computational system that acts as a mediator between simulation results and real-world data. This intermediary automatically processes and compares datasets, identifying divergences without requiring direct manual inspection. The intermediary layer preserves accuracy while eliminating the time-intensive nature of manual analysis.
2Reliability
If comprehensive simulation testing is performed to ensure reliability, then simulation accuracy improves, but resource consumption increases
Solution Approach 1:
The patent extracts and compares only the critical output parameters from comprehensive simulations with corresponding real-world measurements. Rather than analyzing entire datasets, the system identifies and focuses on key divergence points, maintaining simulation reliability assessment while reducing the computational resources required for analysis.
Solution Approach 2:
The patent performs partial analysis by focusing only on the necessary comparison elements rather than exhaustive examination of all simulation data. The system identifies divergences in critical subsystems without requiring complete re-simulation or full-data analysis, achieving sufficient reliability with reduced resource consumption.
3Measurement precision
If detailed process analysis is conducted to identify causes of divergence, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent segments the troubleshooting process into distinct automated modules: data collection, comparison, divergence identification, and cause analysis. Each module handles a specific aspect of the analysis, maintaining measurement precision through systematic processing while reducing overall system complexity through modular design. The segmented approach allows complex analysis to be performed through simple, standardized operations.
Data Source
AI summary
Aspects of the subject technology relate to systems, methods, and computer-readable media for troubleshooting a baseline simulation. A method can include accessing captured real-world data of performed behaviors of an autonomous vehicle in operation and running input data through a simulation template as part of a baseline simulation. The method can also include identifying a divergence of the baseline simulation between the performed behaviors of the AV and simulated behaviors in the baseline simulation of the AV. The method can include running the input data through a modified simulation template and identifying a divergence of the modified simulation between the performed behaviors of the AV and simulated behaviors in the modified simulation of the AV. The method can include troubleshooting the baseline simulation based on a comparison between the divergence of the modified simulation and the divergence of the baseline simulation.