Transport System Analysis
Overall Course Objectives
This course is about understanding the dynamics of transport systems. Students will gain knowledge on key mathematical methods used to model travel demand and supply in complex mobility systems.
Applications encompass a wide range of traditional as well as emerging modes of transport; spanning both private and public sectors, and travelers and cargo alike.
See course description in Danish
Learning Objectives
- Describe fundamental techniques and aggregation levels for modelling transport systems
- Formulate and apply generation and distribution of travel
- Analyse travel mode choice using logit and nested logit models
- Operate and evaluate a demand model for transport analysis
- Apply and assess different measures typically used to evaluate the performance of transport systems
- Implement, analyse and argue the strengths and weaknesses of different modelling and solution methods to solve traffic assignment problems
- Explain the structure of transport system models and discuss feedback mechanisms
- Create and apply a combined transport model to evaluate the impacts of potential policies
- Write technical notes and use traditional mathematical software for the analysis of transport systems and network performance
Course Content
The course covers quantitative methods that can be used to solve problems within transport modelling, and is built around 3 interconnected modules: demand (D), supply (S) and DS interactions. Related to demand modelling, the course focuses on statistical and mathematical methods, especially regression, discrete choice models, iterative proportional fitting in matrix estimation, and gravitation models.
Related to supply we focus on the performance of transport networks, traffic flow theory, network modelling and queueing. Finally, within demand-supply interactions we will focus on equilibrium analysis and traffic assignment. In addition to introducing the underlying fundamentals, the course will include numerous case-studies from different transportation settings. The classes are taught in an interactive manner, with theoretical parts combined with hands-on exercises using an interactive notebook environment. Knowledge of coding is not a must, although some exercises will be presented in Python.
Teaching Method
Lectures and exercise classes, reading the literature, and problem solving.