Traffic Flow Modeling and ITS: Urban Congestion Solutions
Learn to model and manage urban traffic congestion using advanced traffic management techniques in this 7-week course.
Learn to model and manage urban traffic congestion using advanced traffic management techniques in this 7-week course.
Dive into the world of urban traffic management with this comprehensive course on traffic flow modeling and intelligent transport systems. Over seven weeks, you'll explore the complexities of traffic congestion and learn innovative approaches to improve urban mobility. The course covers fundamental concepts of traffic flow theory, introduces various traffic models at micro and macro levels, and delves into advanced traffic management schemes. You'll study the Macroscopic Fundamental Diagram (MFD) for network-level modeling, explore adaptive traffic signal control, ramp metering, and variable speed limits. By the end, you'll be equipped to analyze user equilibrium and apply your knowledge to real-world traffic management challenges. This course is ideal for those looking to understand and address urban congestion using cutting-edge techniques in transportation engineering.
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What you'll learn
Understand key concepts and physics of transport phenomena
Familiarize with major elements of transportation systems
Use simple models to identify causes of congestion
Propose traffic management strategies to alleviate congestion
Apply fundamentals of transportation engineering to real case studies
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 7 modules in this course
This course provides a comprehensive introduction to traffic flow modeling and intelligent transport systems, focusing on understanding and managing urban congestion. Students will learn about fundamental traffic variables, continuum models of traffic flow, and various modeling approaches including micro, meso, and macroscopic models. The course covers advanced topics such as the Cell Transmission Model, Macroscopic Fundamental Diagram, and network-level traffic management strategies. Participants will explore traffic signal control methods, including fixed-time plans and adaptive strategies, as well as concepts like variable speed limits. The course culminates with an introduction to User Equilibrium analysis for predicting and steering behavioral adjustments in transportation systems. Throughout the program, students will apply theoretical concepts to real-world case studies, gaining practical insights into improving mobility in urban environments.
Traffic Flow Basics
Module 1
Continuum Models of Traffic Flow
Module 2
Traffic Modeling and Control for Freeway Systems
Module 3
Macroscopic Fundamental Diagram (MFD)
Module 4
Network-level Traffic Management
Module 5
Control of Traffic Signals
Module 6
Equilibria in Transportation
Module 7
Fee Structure
Instructors
1 Course
Expert in Urban Transportation Systems and Traffic Flow Theory
Nikolas Geroliminis is a Full Professor at École polytechnique fédérale de Lausanne (EPFL) and heads the Urban Transport Systems Laboratory (LUTS). His academic journey includes a diploma in Civil Engineering from the National Technical University of Athens, followed by an M.S. and Ph.D. from the University of California, Berkeley. Before joining EPFL, he served as an Assistant Professor at the University of Minnesota. His research focuses on developing sustainable transportation systems by improving existing infrastructure, with particular emphasis on urban transportation systems, traffic flow theory, public transportation, and optimization of large-scale networks. Geroliminis has made significant contributions to the field, including creating an open-science large-scale dataset of naturalistic urban trajectories collected by drone swarms. He serves as an Associate Editor for several prestigious journals and has received numerous accolades for his work on modeling and controlling traffic congestion in large-scale urban multimodal networks. His research has been widely influential, particularly his work on urban-scale macroscopic fundamental diagrams and traffic control, which has shaped modern understanding of urban mobility patterns and transportation system management.
1 Course
Expert in Traffic Engineering and Transport Systems Optimization
Anastasios Kouvelas is the Director of the Traffic Engineering and Control research group at ETH Zurich's Institute for Transport Planning and Systems (IVT). His academic credentials include Diploma, M.Sc., and Ph.D. degrees from the Technical University of Crete's Department of Production & Management Engineering, focusing on Operations Research. Before his current role at ETH Zurich, which began in August 2018, he served as a Research Scientist at EPFL's Urban Transport Systems Laboratory and completed a Postdoctoral Fellowship at UC Berkeley's Partners for Advanced Transportation Technology. His research interests encompass traffic flow modeling and simulation, intelligent transportation systems, neural networks, adaptive optimization, and mobility patterns. Kouvelas leads a multidisciplinary team developing algorithmic solutions for traffic management, with particular emphasis on connected vehicles and sustainable urban transportation systems
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