Autonomous Vehicle Simulation Timing for Realism Metric Calibration
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Solution Overview
Problem
Challenges exist in creating simulations that accurately replicate the behavior of autonomous vehicles, particularly in determining the optimal start and engage times for software control to ensure realistic testing scenarios.
Innovation Solution
A method involving multiple simulations with adjusted timing requirements is employed, comparing results to logged data to generate a realism metric that defines the best timing for future simulations, ensuring accurate simulation of vehicle behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If simulations are run with fixed timing requirements, then the simulation process is simple and fast, but the simulation realism and accuracy deteriorate
Solution Approach 1:
The patent applies dynamics by making the simulation timing requirements adjustable and adaptive rather than fixed. The system dynamically modifies start times, engage times, and message timing parameters based on comparisons with log data, allowing the simulation to adapt its timing characteristics to match real-world vehicle behavior while maintaining a structured simulation framework
Solution Approach 2:
The patent implements parameter changes by systematically varying timing parameters (start time, engage time, message timing) across multiple simulation versions. By changing these temporal parameters and comparing results with log data, the system identifies optimal timing values that enhance simulation realism without requiring complete redesign of the simulation architecture
2Measurement precision
If multiple versions of simulation are run with different timing requirements, then the simulation realism improves, but the testing time and computational resources increase
Solution Approach 1:
The patent applies partial action by running multiple simulation versions with selectively adjusted timing parameters rather than completely redesigning each simulation. By modifying only the critical timing parameters (start time, engage time, message timing) while keeping other simulation aspects constant, the system achieves improved timing accuracy without proportionally increasing the overall testing burden
Solution Approach 2:
The patent implements feedback by comparing simulation results with actual log data and using this comparison to identify optimal timing parameters. The feedback loop involves running simulations, comparing outcomes with recorded vehicle behavior, analyzing discrepancies, and adjusting timing parameters accordingly, which efficiently converges on accurate timing requirements without exhaustive testing of all possible parameter combinations
3Measurement precision
If the simulation starts at different times relative to log data, then the realism of vehicle behavior improves, but the complexity of determining optimal start time increases
Solution Approach 1:
The patent applies preliminary action by pre-defining a structured set of candidate start times relative to log data entry points. Rather than searching for the optimal start time arbitrarily, the system establishes predetermined timing offsets (e.g., starting simulation at the same time as log recording, or at fixed intervals before/after) and systematically evaluates them, making the determination process more manageable and reproducible
4Measurement precision
If timing requirements are adjusted to match log data, then the simulation realism improves, but the ease of operation decreases
Solution Approach 1:
The patent implements self-service by enabling the simulation system to automatically adjust its own timing parameters based on log data comparisons. The system autonomously identifies optimal start times, engage times, and message timing by comparing simulation outputs with recorded vehicle behavior, reducing the need for manual timing calibration while maintaining high synchronization accuracy
Data Source
AI summary
The disclosure relate to determining a realism metric for testing software for operating a vehicle in an autonomous driving mode. For instance, a plurality of versions of a simulation may be run using log data collected by a vehicle operating in an autonomous driving mode. The plurality of versions may be run using the software to control a simulated vehicle, and each of the plurality of versions may have a set of timing requirements different from the set of timing requirements of other of the plurality of versions. Results of the plurality of versions may be compared to the log data. A realism metric defining timing requirements for one or more future simulations may be generated based on the comparison.