Deliverable 4.2 of the AIthena project, titled ‘Report on physical set-up, digital twin and hybrid testing approaches’, offers a thorough overview of the integration of physical testing infrastructures, digital twins, and hybrid methodologies to enhance the reliability and robustness of AI-driven mobility systems.

This deliverable, developed under Work Package 4 (WP4), establishes the testing methodologies required to validate AI-enabled CCAM solutions in simulated and real-world environments.

AITHENA’s integrated concept

Deliverable 4.2 is based on the overarching AIthena concept of developing trustworthy, explainable and accountable AI systems for CCAM. The report reiterates the project’s commitment to structured evaluation processes combining physical experimentation and advanced simulation tools to ensure safety and performance in complex traffic scenarios.

The deliverable clarifies how Work Package 4 contributed to these goals by focusing on:

• Establishing physical testing facilities tailored for CCAM.

• Designing and calibrating a digital twin framework capable of mirroring real-world behaviour with high fidelity.

• Implementing hybrid (mixed reality) testing that blends digital and physical elements to accelerate validation cycles.

The report provides detailed preparation steps for the physical test environments required to validate AI components in real-world conditions. This includes defining scenarios, test tracks, instrumentation and interfaces for integrating AIthena components into controlled experiments.

The full AITHENA D4.2 report can be found at AITHENA-D4.2-Report-on-physical-set-up-digital-twin-and-hybrid-testing-approaches.pdf