Tuesday 18 November 2025 marked the final day of the four-day AiMTT course Data, AI and Multimodal Traffic Management in Delft. More than 30 mobility professionals and PhD researchers explored how artificial intelligence and data can be applied to manage complex, multimodal traffic systems.
The course was held in two blocks: 2–3 October and 17–18 November. Participants received an intensive yet accessible introduction to the key functions of traffic management—such as traffic state estimation, short- and long-term prediction, anomaly detection, real-time control, and optimisation—and learned how modern AI methods can support these tasks.
Group Assignments
Through a mix of thematic lectures, hands-on data sessions, and collaborative group work, participants gained both theoretical understanding and practical insight into the role of AI in mobility. Real-world use cases, contributed by professionals, formed the basis for group assignments in which practitioners and PhD researchers worked together to address traffic challenges using AI-based approaches. During the period between the two course blocks, participants continued working on their assignments. On the final afternoon, they presented the results of their work.
Knowledge Capsules
A distinctive element of the course were the Knowledge Capsules: short, focused modules developed and presented by teams of PhD researchers. These capsules introduced core AI topics—such as clustering, reinforcement learning, and explainable AI—in formats directly relevant to traffic management applications. Some of these capsules will also serve as the basis for tutorials on this website.