Virtual Object Injection for Autonomous Vehicle Testing
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Solution Overview
Problem
Testing autonomous vehicles in realistic scenarios is challenging, expensive, and potentially dangerous, especially when simulating interactions with real objects like pedestrians, as traditional methods involve using real people or expensive dummies and lack the unpredictability of real-world environments.
Innovation Solution
The method involves using virtual objects and fictitious sensor data to simulate real-world scenarios, allowing autonomous vehicles to maneuver and respond as if interacting with real objects, while logging responses and dynamics for evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real people or dummies are used to test autonomous vehicle reactions, then the testing scenario is more realistic, but it becomes dangerous and expensive
Solution Approach 1:
The patent creates virtual copies of real-world objects (pedestrians, vehicles, obstacles) that can be programmed to behave realistically without posing physical danger. These virtual objects are rendered in the sensor data stream to simulate real object interactions, allowing safe yet realistic testing of autonomous vehicle responses
Solution Approach 2:
The system introduces an intermediary layer between the autonomous vehicle and the real world by injecting virtual objects into the sensor data stream. This intermediary allows the vehicle to interact with simulated entities that mimic real-world behavior without the actual physical risks associated with using real people or expensive dummies
2Reliability
If real-life testing scenarios are set up, then the testing is more realistic, but it becomes expensive and time-consuming
Solution Approach 1:
Instead of physically constructing realistic test scenarios with real objects and environments, the system creates digital copies of these scenarios by injecting virtual objects into the sensor data stream. This eliminates the need for expensive and time-consuming physical setup while maintaining scenario realism
Solution Approach 2:
The system pre-programs virtual objects with realistic behaviors and characteristics before testing begins. These virtual objects can be configured to represent various real-world scenarios (jaywalkers, erratic vehicles, obstacles) without requiring actual physical setup, allowing rapid deployment of diverse test scenarios
3Object-affected harmful factors
If virtual objects are used to simulate real objects, then the testing becomes safe and cost-effective, but the virtual object may not fully represent the real object's behavior
Solution Approach 1:
The system dynamically adjusts parameters of virtual objects to match real-world object characteristics. Virtual objects can be configured with varying behaviors, speeds, trajectories, and sensor signatures to accurately represent different real-world scenarios while maintaining safety and cost-effectiveness
Solution Approach 2:
The system incorporates feedback mechanisms where the autonomous vehicle's responses to virtual objects are logged and analyzed. This feedback loop allows continuous refinement of virtual object behaviors to better match real-world patterns, improving representation accuracy over time while maintaining the safety and cost benefits of virtual testing
Data Source
AI summary
An autonomous vehicle is tested using virtual objects. The autonomous vehicle is maneuvered, by one or more computing devices, the autonomous vehicle in an autonomous driving mode. Sensor data is received corresponding to objects in the autonomous vehicle's environment, and virtual object data is received corresponding to a virtual object in the autonomous vehicle's environment. The virtual object represents a real object that is not in the vehicle's environment. The autonomous vehicle is maneuvered based on both the sensor data and the virtual object data. Information about the maneuvering of the vehicle based on both the sensor data and the virtual object data may be logged and analyzed.