Dear Colleagues,
We would like to invite you to a one-week MIT course from July 27 - 31, 2026:
Modeling Future Transportation Systems: User-Centric, Green, Automated & AI-Driven
3.0 Continuing Education Credits (CEUs): The course includes 25 hours of lectures, 3.75 hours of discussion, and may be accompanied by a letter in support of ECTS credit transfer. Registered students will have the opportunity to propose relevant specific projects, research topics, or problems that they would like to be included in the course activities.
In addition, please join us for an Open House on Tuesday, April 14 at 12pm EDT (GMT-4) to hear more about the course and ask questions. Please contact Katie Rosa at krosa@mit.edu if you would like to attend.
Ready to face the revolutions in transportation systems and discover how disruptive innovations are reshaping the mobility sector? In this immersive five-day course, you will learn to model, analyze and optimize transportation systems using the latest research from MIT and beyond, delving into demand and network modelling, artificial intelligence, simulation, optimization and control. Innovative methods are explored for emerging systems that are still in an early stage of development and deployment, such as user-centric new smart mobility services, automated and AI-driven vehicles and alternative energy vectors for decarbonizing transportation. Through real-world case studies, transportation researchers and professionals from urban and mobility organizations, the automotive industry, logistics companies, and other transportation sectors can gain actionable insights to address current and future transportation challenges.
This course offers a comprehensive exploration of emerging transportation modeling and simulation techniques, with an emphasis on Smart Mobility, AI, and machine learning applications. Participants will delve into the latest advancements in traffic simulation models (microscopic, mesoscopic, and macroscopic), discrete choice modeling for travel behavior, and machine learning techniques for transport applications. The course addresses key themes such as managing on-demand and user-centric mobility, predicting and mitigating traffic congestion, and simulating future transportation systems, including connected and automated vehicles, and urban air mobility. It also covers green mobility, focusing on the adoption of electric vehicles, decarbonization strategies, and integrating active and micro-mobility options. By incorporating case studies and applications of big data, the course examines integrated transportation systems in this early stage of their deployment. Participants will gain insights into the societal and environmental implications of emerging technologies including equity and resiliency while exploring their transformative potential for transportation systems.
One full-tuition scholarship will be awarded to an outstanding doctoral student with an application deadline of June 30, 2026. Partial scholarships (75%) are available for junior faculty, postdocs, and graduate students.
The course will be taught in a hybrid format with in-person and live online cohorts attending simultaneously. Invited lecturers include Prof. Scott Moura (UC Berkeley), Prof. Joan Walker (UC Berkeley), Prof. Eren Inci (Sabancı University), and Prof. Markos Papageorgiou (Technical University of Crete). Additional information is available here. We appreciate your help in making people aware of this unique opportunity to study this summer at MIT.
Thanks,
Moshe Ben-Akiva, Ennio Cascetta, Carlos Lima de Azevedo, Ravi Seshadri, and Pierluigi Coppola
Lead Instructors
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Moshe Ben-Akiva
Massachusetts Institute of Technology
Edmund K. Turner Professor of Civil & Environmental Engineering
Director, Intelligent Transportation Systems Lab
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