Financing: Other Funding Agencies (OTHER)

Project reference Nr.: 0000124-KUL
Start: 2021-04-01
End: 2023-03-31

Description:

We aim to extend the range of use cases in which automated vehicles can operate safely and effectively to those where state-of-the-art approaches are still insufficient. Such cases include scenarios involving dense traffic and strong interactions with potentially unpredictable traffic participants (e.g., pedestrians and cyclists). To this end, we plan to extend the risk-averse MPC methodology being developed in KUL00023 project, to account for interaction between the AV and human-driven vehicles, pedestrians or cyclists.  We shall develop MPC strategies that are able to learn from data how to safely and optimally interact in real time, in the highly uncertain context of automated driving. We will obtain a SW framework with support for embedded code generation (Matlab/Simulink & Python) for risk-averse MPC.

SMC people involved in the project:

• Panagiotis Patrinos (Promoter)