World Model Scene Generation for Realistic Autonomous Driving Tests
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Solution Overview
Problem
Conventional intelligent driving function tests rely heavily on real-world road testing, which is resource-intensive and requires skilled drivers, and existing scene simulation methods fail to generate scenes with sufficient realism.
Innovation Solution
A method and apparatus for information processing that acquires initial scene information, generates target scene information using a world model, and includes a device with a processor and memory to execute instructions for simulating realistic driving scenarios by enhancing scene realism through 3D modeling and data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-world road testing is used for intelligent driving function tests, then test reliability is improved, but resource consumption increases and skill requirements increase
Solution Approach 1:
The patent creates virtual copies of real-world driving scenes through scene simulation technology. The simulation system reconstructs road environments, vehicles, pedestrians, and traffic conditions into digital representations that can be repeatedly tested without consuming physical resources. This copying approach maintains test reliability while eliminating the need for actual road testing resources.
Solution Approach 2:
The patent replaces the mechanical physical testing system with a computational simulation system. Instead of using actual vehicles and roads for testing, the system uses computer-generated environments and virtual sensors to simulate driving scenarios. This substitution eliminates resource consumption while maintaining testing capability through software-based simulation.
2Reliability
If real-world road testing is used for intelligent driving function tests, then test reliability is improved, but driver skill requirements increase
Solution Approach 1:
The patent creates virtual copies of real-world driving scenes through scene simulation technology. The simulation system reconstructs road environments, vehicles, pedestrians, and traffic conditions into digital representations that can be repeatedly tested without consuming physical resources. This copying approach maintains test reliability while eliminating the need for actual road testing resources.
Solution Approach 2:
The patent replaces the mechanical physical testing system with a computational simulation system. Instead of using actual vehicles and roads for testing, the system uses computer-generated environments and virtual sensors to simulate driving scenarios. This substitution eliminates resource consumption while maintaining testing capability through software-based simulation.
3Quantity of substance
If existing scene simulation methods are used, then resource consumption is reduced, but scene realism is insufficient
Solution Approach 1:
The patent implements feedback mechanisms in the scene simulation system by continuously comparing generated virtual scenes with real-world observations. The system uses sensor data from virtual sensors to validate and adjust scene parameters, ensuring high realism. Feedback loops allow the simulation to self-correct and improve the accuracy of generated environments.
Solution Approach 2:
The patent employs parameter changes to enhance scene realism by dynamically adjusting multiple parameters including lighting conditions, material properties, geometric dimensions, and environmental factors. The system modifies these parameters based on input data and simulation requirements to generate highly realistic scenes that accurately represent real-world conditions.
Data Source
AI summary
The present application provides a method for information processing, an apparatus, a device, a computer-readable storage medium, and a computer program product. The method includes that: initial scene information of a to-be-tested road section is acquired, where the initial scene information includes a scene image or a point cloud of a scene; and target scene information of a target vehicle traveling on the to-be-tested road section is generated according to the initial scene information by using a world model.


