Multi-Fidelity Mesh Simulation for Autonomous Vehicle Sensors
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Solution Overview
Problem
Autonomous vehicle simulations face challenges in generating real-time sensor data, particularly with high-complexity sensor models like LIDAR, which can be computationally intensive, leading to increased costs and decreased simulation performance.
Innovation Solution
The use of mesh data of different fidelities allows for the generation of synthetic sensor data from lower fidelity mesh objects, enabling real-time execution of AV simulations without additional computational resources, by decimating high-fidelity mesh data to maintain accurate object identification and reduce processing power requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-fidelity mesh data is used for sensor simulation, then object identification accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments mesh data into different fidelity levels (high-fidelity and low-fidelity) and assigns them to different sensor modalities. High-fidelity mesh data is used for camera simulations requiring visual detail, while low-fidelity mesh data is used for LIDAR simulations where computational efficiency is prioritized. This segmentation allows the system to optimize computational resources while maintaining accuracy where needed.
Solution Approach 2:
The patent applies local quality by using high-fidelity mesh data specifically for sensor modalities that benefit from detailed geometric representation (such as camera simulations), while using low-fidelity mesh data for modalities less sensitive to mesh detail (such as LIDAR). This localized application of quality ensures computational efficiency is improved without sacrificing object identification accuracy for critical sensors.
2Reliability
If high-fidelity mesh data is used for all sensor modalities, then simulation accuracy is improved, but simulation time increases
Solution Approach 1:
The patent divides sensor modalities into different groups based on their fidelity requirements and assigns corresponding mesh data levels. This segmentation enables parallel processing of different sensor simulations with appropriate fidelity levels, reducing overall simulation time while maintaining accuracy for modalities that require it.
Solution Approach 2:
The patent changes the fidelity parameter of mesh data based on the specific sensor modality being simulated. By adjusting this parameter dynamically according to sensor requirements, the system achieves optimal balance between simulation accuracy and execution speed, preventing unnecessary computational overhead.
3Measurement precision
If high-fidelity mesh data is used, then sensor data quality is improved, but processing power requirements increase
Solution Approach 1:
The patent applies high-quality mesh data only to sensor modalities where it directly impacts sensor data quality, such as camera simulations. For other modalities like LIDAR, lower-quality mesh data suffices, reducing processing power requirements without compromising overall system performance or sensor data quality where it matters most.
Data Source
AI summary
Systems and methods using different mesh fidelities for different sensor modalities in a vehicle simulation are provided. For instance, a computer-implemented system includes one or more processing units; and one or more non-transitory computer-readable media storing instructions, when executed by the one or more processing units, cause the one or more processing units to perform operations including generating synthetic sensor data based on low-fidelity mesh data representing an object; generating a synthetic driving scene including the object, the generating the synthetic driving scene is based at least in part on high-fidelity mesh data representing the object; and executing a vehicle compute process based on the synthetic driving scene and the synthetic sensor data.