Autonomous Vehicle Simulation Stack for Hybrid Closed-Course Stress Testing
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Solution Overview
Problem
Testing complex autonomous vehicle (AV) scenarios in closed-course environments is challenging due to the difficulty in recreating diverse real-world conditions, resource-intensive setup, and limitations of simulated scenarios, which fail to replicate real-world physics and sensor data accurately.
Innovation Solution
A combined AV and simulation stack is used to execute simulations concurrently with real-world AV operations, allowing for the injection of virtual entities into a closed-course environment, thereby enhancing the testing of AV responses to various scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If simulated scenarios are used for testing, then resource consumption is reduced, but the accuracy of replicating real-world physics and sensor data deteriorates
Solution Approach 1:
The patent uses virtual entities as digital copies of real-world objects (pedestrians, vehicles, obstacles) to create simulated test scenarios. These virtual copies replicate the essential characteristics and behaviors of real objects without requiring physical resources, thereby reducing resource consumption while maintaining testing accuracy through faithful reproduction of real-world scenarios.
Solution Approach 2:
The system introduces a simulation environment as an intermediary between the autonomous vehicle and real-world testing. This intermediary layer allows testing of AV responses to various scenarios without direct interaction with physical objects, reducing resource consumption while preserving the ability to evaluate AV performance through carefully designed virtual scenarios that mirror real-world conditions.
2Adaptability or versatility
If diverse real-world conditions are recreated in closed-course environments, then testing comprehensiveness is improved, but setup complexity and resource requirements increase
Solution Approach 1:
The patent segments the testing environment into virtual entities that can be independently created, configured, and positioned within the closed-course environment. Each virtual entity represents a discrete element (pedestrian, vehicle, obstacle) that can be individually managed, allowing comprehensive testing scenarios to be built from modular components without proportionally increasing overall system complexity.
Solution Approach 2:
The system enables diverse testing conditions by changing parameters of virtual entities (position, speed, behavior patterns, physical characteristics) rather than requiring physical modification of the test environment. This allows comprehensive testing of various real-world conditions through software-based parameter adjustments, avoiding the complexity and resource requirements of physical setup changes.
3Adaptability or versatility
If virtual entities are injected into real-world test courses, then scenario diversity is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal virtual entity system that can represent multiple types of objects (pedestrians, vehicles, obstacles, animals) using a common framework. This multi-functional approach allows diverse scenarios to be created without proportionally increasing system complexity, as the same underlying infrastructure supports various entity types through configurable parameters and behaviors.
Data Source
AI summary
Disclosed are embodiments for facilitating purposeful stress testing of autonomous vehicle response time with simulation. In some aspects, an embodiment includes receiving a request to launch a simulation scenario on an autonomous vehicle (AV) that is to operate on a real-world test course; initiating a simulation derived from the simulation scenario using a simulation driver that is executing on the AV; engaging operation of the AV on the real-world test course; coordinating a simulated AV position in the simulation with a physical AV position of the AV on the real-world test course; combining virtual entities from the simulation with physical entities on the real-world test course into a list of tracked objects for the AV; and causing the AV to respond to the list of tracked objects including the virtual entities and the physical entities during the operation of the AV on the real-world test course.