AI4CCAM: Trustworthy AI for Cooperative, Connected & Automated Mobility

Considering Artificial Intelligence (AI) capabilities and potential risks, and taking into account its limitations, AI4CCAM will develop an open environment for integrating trustworthy-by-design AI models of vulnerable road user behaviour anticipation. These models will be considered in urban traffic conditions, accounting for improved road safety and user acceptance. Leveraging the Trustworthy AI guidelines for general intelligent software systems and the ethics recommendations for connected automated vehicles, AI4CCAM will support AI-based scenarios management in which pedestrian/cyclist behaviour anticipation models integrate visual gaze estimation. These scenarios will include explainable ego car trajectory prediction models which are simulated with ethical dilemmas and multiplied with generative adversarial networks and metamorphic testing techniques.

The AI4CCAM open environment will include an interoperable digital framework for managing and generating AI-based urban-traffic scenarios in which trustworthy-by-design AI models can be tested. This environment will also feature an online participatory space to foster acceptance of AI in automated driving, determine AI risks and identify biases in datasets and cyber threats. Simulation scenarios of road users interacting with automated vehicles will be developed and evaluated in three complementary use cases covering the whole sense-plan-act paradigm and user acceptance. As such, the project will advance knowledge in building trustworthy-by-design AI-based solutions for connected, cooperative and automated mobility applications.

Simula is a coordinator for this project. 

Funding source

This project is funded by the Horizon Europe programme under Call CL5-2022-CCAM-D6-01-05 (external link to the call).

It is a Research & Innovation Action (RIA), Project 101076911.

All partners

Affiliated personnel: