Occlusion Data Caching for Autonomous Vehicle Simulation
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Solution Overview
Problem
Autonomous vehicle simulation systems face inefficiencies due to the need to recalculate occlusion data for static objects in each simulation scenario, leading to increased computational resources and time, especially when dynamic objects occlude sensors, resulting in incomplete log data.
Innovation Solution
A pre-simulation component caches occlusion data for static objects by executing a three-dimensional simulation without dynamic objects, then uses this data for subsequent two-dimensional simulations, reducing computational load and filling gaps in occluded regions to provide more accurate and efficient scenario testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If occlusion data is recalculated for each simulation scenario, then measurement precision is improved, but productivity deteriorates due to increased computational time and resources
Solution Approach 1:
The system performs a pre-simulation step before the actual simulation to calculate and cache occlusion data for all static objects in advance. This preliminary calculation stores the occlusion information in a data structure that can be quickly accessed during simulation execution, eliminating the need to recalculate occlusion data for each scenario and thus improving simulation throughput while maintaining accuracy
Solution Approach 2:
The system creates a cached copy of occlusion data from the pre-simulation and uses this copy during actual simulation execution. Instead of repeatedly calculating the same occlusion relationships, the system references the pre-computed copy, significantly reducing computational load while preserving the precision of occlusion measurements
2Loss of information
If three-dimensional simulation is executed without dynamic objects, then loss of information is reduced by identifying occluded areas, but use of energy increases due to computational requirements
Solution Approach 1:
The system extracts and removes dynamic objects from the simulation environment during the pre-simulation phase. By creating a simplified scene without dynamic objects, the system can efficiently calculate occlusion data for static objects alone, reducing computational complexity while still identifying all occluded areas that will be relevant when dynamic objects are present
Solution Approach 2:
The system performs the energy-intensive occlusion calculation in advance during a dedicated pre-simulation phase. By completing this computationally demanding task before the actual simulation, the system reduces the energy consumption during runtime while ensuring complete and accurate occlusion detection for all static objects
Data Source
AI summary
Techniques associated with improving performance and realism of simulation instances associated with simulation testing of autonomous vehicles. In some cases, a simulation system may be configured to run a pre-simulation test to identify and store occlusion data to improve the performance of subsequent simulations associated with a shared scene or route.