edX
edXIntro to Traffic Flow Modeling and Intelligent Transport Systems
133 studentsINTERMEDIATEEnglish
Korshub's take
Solving Urban Traffic Through Theory and Innovation
Traffic congestion feels inevitable in cities, but this course reveals it's actually a solvable problem—if you understand the underlying dynamics. You'll learn how traffic flow theory explains complex interactions in surprisingly elegant mathematical models, moving from the micro (individual vehicle behavior) to the macro (network-wide patterns).
Beyond theory, the course connects you to real-world solutions: adaptive traffic signals that respond to conditions, ramp metering, variable speed limits, and the powerful concept of the Macroscopic Fundamental Diagram. With exercises and real datasets, you'll see how these tools have transformed mobility in actual cities, preparing you to think strategically about urban transportation challenges.
About this course
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.
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