“Learning by Doing” to Develop AI Applications for Mobility
AiMTT aims to cultivate a highly skilled and diverse AI talent pool equipped to address the opportunities and challenges of AI in mobility, transport, and logistics. By combining real-world case studies with knowledge development, this initiative fosters deep expertise in the field.
Our project partners will build, test, and refine AI applications for mobility, transport, and logistics through seven real-world use cases. These tools will be ready for practical implementation. Equally important, however, is the learning process that comes with working hands-on with AI. To support this, AiMTT offers workshops, training programs, and co-creation sessions—ensuring continuous knowledge exchange and improvement.
More Than Twenty Partners
The AiMTT consortium brings together over twenty partners, carefully selected for their ability to address key mobility, transport, and logistics challenges, maximize impact, and create meaningful learning opportunities for stakeholders. This collaboration also offers strong potential for project-based training and education.
Learning Through Use Cases
AiMTT’s partners are learning and developing together through six use cases based on real-world challenges. The use cases range from crowd management at large events to smarter, more efficient solutions for inland shipping.
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LATEST NEWS
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Six Teams Explore the Potential of AI for Real-World Mobility Challenges
On 4 November, the first AI & Mobility Hackathon brought together students, researchers, public authorities and companies at Mondai House of AI in Delft. Six teams worked on practical mobility challenges, exploring how artificial intelligence can help address real-world problems in transport and mobility. The hackathon was organised by AiMTT, TU Delft and Mondai House…
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New: Python Notebooks Available for Learning Module Crowd Management
Our first AiMTT Learning Module, Crowd Management During Events, now includes several Python notebooks that can be run in Google Colab. These notebooks allow students, data scientists and crowd managers to explore the concepts and techniques presented in the video course in greater depth. The learning module includes 19 videos, in which experts from academia…