Project description
Simulation scenarios of road users interacting with automated vehicles
Cooperative, connected and automated mobility will play a big role in the future of transportation. A first stop in this journey is to consider the capabilities and potential risks of AI. In this context, the EU funded AI4CCAM project will carry out simulation scenarios of road users interacting with automated vehicles. It will develop an open environment for integrating trustworthy-by-design AI models of vulnerable road users’ behaviour anticipation in urban traffic conditions. Specifically, the project will support AI-based scenarios management in which pedestrian and cyclist behaviour anticipation models will integrate visual gaze estimation and where explainable ego car trajectory prediction models are simulated with ethical dilemmas.
Objective
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 in urban traffic conditions, and 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 will integrate visual gaze estimation and where explainable ego car trajectory prediction models 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 and 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 CCAM applications.
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HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
0164 Oslo
Norway