Addressing Mobility Challenges with AI
The mobility sector never stands still; there are always challenges. Traffic jams, crowds at major events, disruptions caused by roadwork, and well-organized public transportation. The AiMTT (AI Learning Initiative for Multi-modal Traffic and Transportation) Learning Community develops AI applications to address these issues and helps train the professionals and students who will be working with them.
AI in Traffic, Transportation, and Logistics
AI processes large amounts of data in real time, assesses the condition of the traffic network, simulates future scenarios, and helps optimize measures. AI also provides greater insight into traveler behavior and the mobility system as a whole. In this way, AI contributes to improved traffic safety, more efficient public and demand-responsive transportation, smarter container transport, safe visitor flows at major events, and reduced disruption during large-scale roadwork.
About the AiMTT Learning Community
The consortium consists of more than twenty partners from education and research, government, consulting, technology, and trade media. TU Delft serves as the lead partner. Participants include Rotterdam University of Applied Sciences, TU/e, Rijkswaterstaat, the Province of North Holland, the City of Amsterdam, NDW, Technolution, Deloitte, and Siemens. NM Magazine and WE Labs share the results and lessons learned with the sector.
Workshops, training programs, and co-creation sessions facilitate knowledge exchange among the partners. On the AiMTT learning hub, you’ll find tutorials and introductory modules, and students contribute to the use cases through their graduation projects.
