This course gives an overview and technical details on scientific and computational methodologies for describing urban transportation systems, especially vehicular traffic in road networks. Mathematical theories of traffic flow and dynamic network traffic will be explained first. Then, solution algorithms, i.e., simulation methods, for the theoretical models will be explained. Finally, the students will implement the algorithms by their own and apply them to solve some problems. For the implementation, easy-to-use computation environments (e.g., Microsoft Excel and other spreadsheet software) are sufficient, but skilled students may use general programming languages.
The aim of this course is to understand abstract, mathematical models of urban transportation systems, how to materialize such abstract models using computer programming, and how to solve practical problems using these tools.
By the end of this course, students will be able to:
1. Understand what is traffic flow theory
2. Solve traffic flow models
3. Understand what is dynamic traffic assignment
4. Develop a primitive yet valid traffic flow simulator
5. Solve some problems using the simulator
Traffic engineering; Traffic flow theory; Dynamic traffic assignment; Traffic management
✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | Practical and/or problem-solving skills |
Lectures on fundamental knowledge will be given first. Occasional quizzes will be given. After the lectures, each student will develop her/his own simulator under guidance of the lecturer. Student will summarize the results of simulation as reports. The schedule of the course may be flexibly adjusted depending on the progress.
Course schedule | Required learning | |
---|---|---|
Class 1 | Introduction of transportation science and simulation, fundamentals of traffic flow theory | Understand fundamentals of traffic flow theory |
Class 2 | Traffic flow theory: macroscopic traffic flow model, analytical solution method | Understand macroscopic traffic flow model, analytical solution method |
Class 3 | Traffic flow theory: numerical solutions methods | Understand numerical solutions methods |
Class 4 | [Exercise] Implementation of macroscopic traffic flow model | Implement macroscopic traffic flow model |
Class 5 | Traffic flow theory: microscopic traffic flow models | Understand microscopic traffic flow models |
Class 6 | Traffic flow theory: Cellular automata | Understand cellular automata |
Class 7 | [Exercise] Implementation of microscopic traffic flow model | Implement of microscopic traffic flow model |
Class 8 | Road network traffic: Introduction and route choice models | Understand road network traffic and route choice models |
Class 9 | Road network traffic: node model | Understand node model |
Class 10 | [Exercise] Implementation of dynamic traffic assignment method | Implement of dynamic traffic assignment method |
Class 11 | Road network traffic: traffic management schemes | Understand traffic management schemes |
Class 12 | Departure time choice problem | Understand Departure time choice problem |
Class 13 | [Exercise] Implementation and application of dynamic traffic assignment method | Implement and apply of dynamic traffic assignment method |
Class 14 | [Exercise] Implementation and application of dynamic traffic assignment method | Implement and apply of dynamic traffic assignment method |
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
None
Martin Treiber and Arne Kesting. "Traffic Flow Dynamics: Data, Models and Simulation", Springer-Verlag Berlin Heidelberg (2013).
Small assignments (30%), reports (70%)
Basic skill to use spreadsheet software such as Microsoft Excel. It is not necessary to be able to use general programming languages, but students can use them by their own if they wish.