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Intro to Traffic Flow Modeling and Intelligent Transport Systems

Intro to Traffic Flow Modeling and Intelligent Transport Systems

Learn how to describe, model and control urban traffic congestion in simple ways and gain insight into advanced traffic management schemes that improve mobility in cities and highways.

Travelers in large cities experience significant congestion during their everyday trips. Expanding roads and infrastructure is not a long-lasting remedy to urban congestion. This course will focus on understanding traffic congestion and will explore ways to improve mobility through advanced traffic management schemes. As we all experience, congestion is a highly complex process without a single explanation. An interesting question is: “Can we describe these complex interactions with simple and elegant ways? “

The course will introduce the fundamentals of traffic flow theory and will describe different traffic flow models in micro- and macroscopic level. Network-level aggregated modeling and control approaches are introduced based on the concept of the Macroscopic Fundamental Diagram (MFD). Advanced traffic management schemes (such as adaptive traffic signal control, ramp metering, variable speed limits) are discussed. User equilibrium analysis is introduced through applications of route and departure time choices. Relative reading material, exercises and real data sets are provided.

What you'll learn

  • Understand key concepts and the physics of the transport phenomena
  • Familiarize with major elements of transportation systems
  • Use simple and elegant models to identify the causes of congestion
  • Propose traffic management strategies to alleviate congestion
  • Apply the fundamentals of transportation engineering in real case studies


  • Nikolas Geroliminis
  • Anastasios Kouvelas
  • Raphaël Lamotte
  • Dimitrios Tsitsokas


You'll find more information about EPFL MOOCs here. This course in particular might be of interst to you: Introduction to Discrete Choice Models

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