Event: AI & Mobility Day 2026

Discover How AI Is Transforming Mobility

Join us at AI & Mobility Day on November 5, 2026, to discover the latest developments in AI for mobility, transport and logistics. During this one-day event, TU Delft AI Initiative, TU Delft Transport & Mobility Institute, Mondai House of AI, and AiMTT will present the latest research, demonstrate practical applications and share real-world case studies. Meet leading researchers and professionals, exchange ideas, and discover how AI is helping create smarter, safer and more sustainable mobility systems.

Whether you work for a government agency, a knowledge institute or a private company—or you are preparing for a career in mobility—AI & Mobility Day offers a unique opportunity to gain new insights, expand your network and explore the future of mobility.

Event Information

Date: November 5, 2026, 9:00 AM – 6:00 PM

Location: Mondai House of AI, Delft

Audience: Professionals and students in mobility, transport and logistics

Admission: Free of charge

Registration: REGISTER HERE!

Programme

09.00 h – Walk-in and Reception

09.30 h – Opening
Sascha Hoogendoorn-Lanser (TU Delft, AiMTT), Serge Hoogendoorn (TU Delft, AiMTT)

Why is AI the talk of the day in transport, mobility and logistics, and what do we want to achieve today: no hype, but an honest picture of what is possible, what is not yet possible and what it asks of us.

09.40 h – Responsible Use of AI in the Traffic, Mobility and Logistics Domain
Satish Ukkusuri (Purdue University)

An overview of the main AI methods and how they relate to questions in traffic, mobility and logistics: where the opportunities lie and where the risks and pitfalls are. This keynote lays the foundation and the shared vocabulary for the rest of the day.

10.20 h – What Has to Be Settled Before AI Decides?
Neil Young Smith (TU Delft), Diederick Blom (DB Consulting)

Autonomous inland vessels and AI-supported decisions are technically within reach, but adoption stalls somewhere else: practitioners don’t trust a result they can’t explain, and nobody wants the liability for a wrong one. Two projects examined different aspects of this challenge: on the one hand, they interviewed inland shipping experts and researchers about the real barriers to implementation; on the other hand, they considered who is accountable when an AI flags a vessel as a threat and entry is refused. Together, they map: what has to be settled before AI decides?

11.00 h – Coffee Break

11.15 h – Relevance of Traffic and Transportation Theory in the Era of AI
Ludovic Leclercq (Université Gustave Eiffel)

Does traffic and transportation science remain relevant now that AI seems able to learn from data everywhere? An argument for why domain knowledge is indispensable precisely now, and how theory and AI can strengthen each other.

11.55 h – Active Inference for Decentralised, Resilient and Cooperative Traffic Management
Olaf Vroom (NDW), Wouter Kouw (TU/e), Bert de Vries (TU/e), Dmitry Dagaev (TU/e), Xue Yao (TU Delft)

Active Inference approaches traffic management as a prediction process in which actors explicitly account for uncertainty and decide in a decentralised way, without losing sight of network-wide goals. Using concrete situations such as route choice, signal control and in-car advice, we explore what this framework means for road authorities and traffic control centres.

12.35 h – Lunch

13:30 h – Responsible Use of Explainable AI for Anticipatory Crowd Management 
Jeroen Steenbakkers (Argaleo), Hannah Louise Mulvihill (RUG), Isabel Franke (TU Delft), Tamara Dert (TU Delft), Ziteng Li (TU Delft)

AI can predict crowding and risk and support crowd managers in real time, but that only works if systems are explainable, privacy-proof and ethically responsible and the human stays in control. Using the AI-Compass pilots around events, demonstrations and busy days, we show how humans and AI reach better decisions together.

14:10 h – From Estimation and Prediction to Evaluation: AI for Traffic Management
Henk Taale (RWS), Erik-Sander Smits (Arane), Yanan Xin (TU Delft)

What do traffic management measures really achieve? Rijkswaterstaat has to answer that question, not only for their own operations, but also for policy purposes. However, this is difficult – the mobility system is dynamic and circumstances change all the time. This challenge is approached from different angles:

• Henk Taale introduces the problem from evaluation practice. Why is determining effects difficult but essential?
• Erik-Sander Smits shows how AI is used to estimate and predict the traffic state – queue lengths, travel times and the development of congestion – and why that is not yet enough to evaluate traffic management.
• Yanan Xin then shows how causal and counterfactual inference give more reliable effect estimates than purely predictive models, illustrated with the effect of traffic signalling on incidents.

14.50 h – Break

15.05 h – AI to the Rescue? The Maintenance and Replacement Challenge
Ministry of Infrastructure and Water Management, TU Delft

The Netherlands faces an enormous challenge in maintaining and replacing bridges, quay walls, locks and roads, while money and people are scarce. An exploratory session on where AI could help, from inspection with image recognition to prioritising investments to planning works to keep regions as accessible as possible: meant to spark curiosity, not to give ready-made answers.

15.45 h – The Future of AI and What It Means for Transportation, Logistics and Infrastructure
Deborah Nas (TU Delft)

Which AI developments are coming our way in the years ahead, and what do they mean for transport, logistics and infrastructure, and for the professional’s daily work? A thought-provoking look ahead.

16.25 h – AI & Mobility November 4th Hackathon Winner and Runner-up Pitches 

16.55 h – Close

The common thread of the day, a look back at the propositions, and the question to the audience: what will we do differently tomorrow?

17.05 h – Drinks

Register Early

Attendance is free, but the capacity of the Panorama XL Hall at Mondai House of AI is limited. Reserve your place early to avoid disappointment.