Telemetry-Synchronized Autonomy Stack Comparison in Real-World Simulation
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Solution Overview
Problem
It is difficult to compare the responses of an updated autonomy stack with a previous stack in a simulation environment, making it challenging to assess how the updated stack performs in real-world scenarios.
Innovation Solution
A method is implemented to generate a real-time simulation using telemetry data from an autonomous vehicle, synchronizing an ego-vehicle with an updated autonomy stack, and displaying the simulation on a display device to compare responses to real-world stimuli.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If an updated autonomy stack is tested in a simulator using real-world telemetry data, then the ability to evaluate performance in real-world scenarios is improved, but the ability to directly compare responses with previous autonomy stacks deteriorates
Solution Approach 1:
The system pre-processes real-world telemetry data into structured simulation scenarios before testing the updated autonomy stack. By preparing reference scenarios in advance with known characteristics and outcomes, the system enables direct comparison between different autonomy stack versions while maintaining realistic evaluation conditions.
Solution Approach 2:
The system creates virtual copies of real-world driving scenarios by reconstructing environments, objects, and conditions from telemetry data. These copied scenarios serve as standardized test beds that can be reused across multiple autonomy stack versions, enabling consistent comparison while preserving real-world fidelity.
2Reliability
If real-world telemetry data is used to generate simulation environments, then the realism of the simulation is improved, but the complexity of setting up comparative tests with previous autonomy stacks increases
Solution Approach 1:
The system divides the complex telemetry data into structured segments representing different environmental elements (road geometry, weather conditions, traffic patterns, obstacles). Each segment can be independently processed and recombined, simplifying the setup of comparative tests while maintaining overall realism.
Solution Approach 2:
The system creates a universal scenario framework that can accommodate multiple autonomy stack versions and different test conditions. The standardized scenario structure serves multiple functions: it preserves real-world characteristics, enables version-to-version comparison, and supports various test configurations without requiring separate setup for each case.
Data Source
AI summary
The present invention relates to a computer-implemented method of comparing an autonomy stack with an updated autonomy stack in a simulator. The computer-implemented method comprising: retrieving a portion of telemetry data recorded by the autonomy stack, the telemetry data representing a real-world environment in which an autonomous vehicle operated, the autonomous vehicle controlled by the autonomy stack; generating a simulation of the real-world environment using the telemetry data; providing an ego-vehicle in the simulation at a position of the autonomous vehicle associated with the telemetry data, the ego-vehicle controlled in the simulation by the autonomy stack; providing an updated ego-vehicle in the simulation, the updated ego-vehicle controlled in the simulation by the updated autonomy stack; generating a real-time simulation by positionally synchronising the ego-vehicle with the updated ego-vehicle; and displaying the real-time simulation on a display device.