Autonomy Engine Performance Testing via Surrogate Modeling
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Solution Overview
Problem
Conventional methods for testing autonomous vehicle systems are inefficient due to the high number of parameters involved in simulating realistic missions, leading to lengthy simulation times and inability to effectively determine system performance in complex environments.
Innovation Solution
An adaptive search method using a surrogate model is employed to selectively generate test scenarios for simulation, clustering and ranking them based on performance score metric values to identify performance boundaries and prioritize scenarios for modification or real-world testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional simulation techniques are used to test all permutations of mission parameters, then complete understanding of system performance is achieved, but simulation time becomes excessively long (hours or days)
Solution Approach 1:
The patent creates a surrogate model (copy) of the autonomy software that replicates its performance characteristics. This surrogate model can be evaluated much faster than running full simulations, allowing rapid assessment of system performance across many parameter combinations without requiring exhaustive simulation of all permutations
Solution Approach 2:
The patent performs preliminary simulation runs to collect performance data and build the surrogate model before actual testing. This preliminary action captures the essential performance characteristics, enabling subsequent rapid evaluation of additional scenarios using the surrogate model rather than full simulations
2Reliability
If the number of test scenarios is increased to cover all possible outcomes, then system performance boundaries are fully characterized, but computational resources and time requirements become prohibitive
Solution Approach 1:
The patent uses clustering algorithms to analyze simulation results and identify performance boundaries and modes. This feedback mechanism automatically determines which regions of the parameter space are most informative for characterizing system performance, allowing the testing process to focus on critical boundaries rather than uniformly sampling all scenarios
Solution Approach 2:
The patent generates a surrogate model from a subset of simulation data that is sufficient to capture performance characteristics. Rather than requiring complete coverage of all possible scenarios, the surrogate model is built from representative samples, enabling efficient performance assessment without exhaustive testing
3Measurement precision
If exhaustive testing of all mission parameters is performed, then complete performance guarantees are obtained, but the complexity and cost of testing become unsustainable
Solution Approach 1:
The patent introduces a surrogate model as an intermediary between the actual autonomy software and the testing process. This intermediary captures the essential performance behavior of the complex system, allowing performance guarantees to be assessed through the simpler surrogate model without requiring direct exhaustive testing of the full system complexity
Data Source
AI summary
An example method for simulation testing an autonomy software is provided. The example method may include receiving, at processing circuitry, mission parameters indicative of a test mission, environmental parameters, and vehicle parameters. The method may further include performing, by the processing circuitry, an adaptive search using a surrogate model of the autonomy software under test to selectively generate test scenarios for simulation, and clustering the plurality of test scenarios based on performance score metric values to determine performance boundaries for the autonomy software under test. The method may further include ranking the plurality of test scenarios based on a respective distance to a performance boundary to identify test scenarios of interest for modification of the autonomy software or real-world field testing of an autonomous vehicle.