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Project cooperationUpdated on 30 January 2026

Generative AI for Cooperative CCAM in Mixed Traffic

Transfer manager at Technische Hochschule Ostwestfalen-Lippe

Lemgo, Germany

About

We are seeking partners for a Horizon Europe Cluster 5 Destination 6 RIA targeting HORIZON-CL5-2026-10-D6-03. Our Objective is to develop and validate generative perception and world-modelling with cooperative decision-making and trajectory planning among autonomous and non-autonomous participants in mixed traffic. Target environments include campus intersections, rail and road interfaces, station forecourts, and halt areas. Use cases include interactions between small autonomous rail vehicles such as MONOCAB, autonomous passenger cars, conventional cars, cyclists, and pedestrians.

We offer a research space with permanent sensing at complex intersections, an autonomous passenger-car platform, mobile sensor rigs for cyclists and pedestrian targets, high-fidelity maps, data management, simulation and driving-simulator links, and immersive visualisation. ATO competencies from enableATO, MONOCAB, and the DZM site Minden covering procedures and safety constraints for automated small rail vehicles at crossings and stations.

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