Digital Twin Traffic Testing for Authentic Autonomous Vehicle Validation

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Solution Overview

Problem

Traditional road tests for autonomous driving vehicles are resource-intensive, risky, and lack authenticity, hindering commercial application.

Innovation Solution

A hybrid traffic flow testing method and system based on digital twin and virtual-physical integration, which includes collecting data from realistic testing sites, creating virtual scenes, generating virtual and realistic vehicles with different driving styles, and implementing sensing, positioning, planning, control, and V2X communication methods to enhance the authenticity and safety of testing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional road tests are conducted for autonomous driving vehicles, then testing authenticity is improved, but resource consumption increases and safety risks arise

Engineering Contradiction:

Improvetesting authenticityVSAvoidresource consumption

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The patent creates virtual copies of real-world driving environments, vehicles, and traffic participants through digital twin technology. Virtual scenes are constructed by importing point cloud maps, 3D reconstructed scenes, and vehicle models from realistic testing sites, allowing autonomous vehicles to be tested in authentic scenarios without deploying physical resources.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent introduces a virtual-physical integration platform as an intermediary between pure simulation and real-road testing. This platform injects virtual traffic objects into real autonomous driving vehicles while maintaining bidirectional data flow, serving as a mediator that provides authentic testing experiences with reduced physical resource requirements.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If traditional road tests are conducted for autonomous driving vehicles, then testing authenticity is improved, but safety risks increase

Engineering Contradiction:

Improvetesting authenticityVSAvoidsafety risks

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent replaces dangerous physical test elements with virtual copies. Virtual traffic participants, including human-driven vehicles with different driving styles, are generated through AI models rather than using real vehicles and drivers, eliminating risks of vehicle damage and personnel injury while maintaining testing authenticity.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent converts the limitation of virtual environments (lack of authenticity) into a benefit by using digital twin technology to create highly realistic virtual scenes that mirror real-world conditions. This allows authentic testing to be conducted in a safe virtual space, turning the potential harm of unrealistic simulation into the benefit of realistic yet safe testing.

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

3Productivity

If single simulation tests are used for autonomous driving, then resource efficiency is improved, but testing authenticity deteriorates

Engineering Contradiction:

Improveresource efficiencyVSAvoidtesting authenticity

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent merges virtual simulation technology with physical autonomous driving vehicles in a virtual-physical integration platform. Virtual traffic objects are injected into the real vehicle's sensing system, combining the resource efficiency of simulation with the authenticity of physical testing, allowing closed-loop tests that leverage both virtual and real-world advantages.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent creates virtual copies of traffic participants and environments that are integrated into the physical testing space. These virtual objects are rendered through the vehicle's cameras and sensors, providing authentic visual feedback while maintaining the resource efficiency of simulation-based testing.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS20250319897A1Hybrid traffic flow testing method and system based on digital twin and virtual-physical integration

Publication Date: 2025.10.16 CHANGAN UNIV

AI summary

A hybrid traffic flow testing method and system based on digital twin and virtual-physical integration includes steps as follows. Data of a realistic testing site is collected, and a virtual scene is created based on the digital twin, interactions between a realistic environment and a virtual environment are set up to achieve a system configuration of a system based on the virtual-physical integration. Virtual human-driven vehicles are generated based on a data set of the system configuration, and realistic human-driven vehicles are generated based on data collected by driving simulators operated by realistic human drivers. Human-driven vehicles are formed by combining the virtual and realistic human-driven vehicles, and status and location information of the human-driven vehicles are acquired. A set of sensing, positioning, planning, control, and V2X communication methods are set up based on the status and the location information for CAVs, thereby achieving autonomous driving.