Authorities in Sweden work systematically to develop and improve the transport system in the country. The development is often linked to investments in or changes to the transport infrastructure, such as road upgrades, new roads, congestion charging, increased railway capacity, etc. The Swedish Transport Administration and consultants in the transportation area work daily to create plans for this type of investment. The plans are often analysed before a decision by so-called transport forecast models.
A model of what today's transport system looks like, as well as a description of how it is used today, is the basis for a transport forecast model. The forecast model uses this basis to evaluate the effect of changes in travel needs and to illustrate the effects different decisions on investments in or regulations of the transport system may have.
A systematic way of working with forecasts for future transport systems are mathematical models. This type of model uses data on how the transport system works today, together with models that describe needs and behaviour when it comes to travelling.
This course provides basic knowledge regarding the planning and forecasting of traffic systems using traffic models. The focus of the course is on the underlying theories on which forecast models are based. These theories are based on mathematical concepts and models that come from mathematical analysis and optimization theory. The course covers both supply modelling and models of travel demand, with some focus on modelling travel demand using so-called discrete choice models. Within the framework of courses, minor experiments and analyses are performed with the models studied in the course in the format of computer-based exercises.
The course also provides an orientation on different types of issues and applications in traffic planning and provides insights into how traffic models can be used for the analysis of traffic systems to make the system more efficient, safer and more environmentally friendly.
The course presupposes basic knowledge in optimization theory. The examination consists of exercises and an on-campus exam. The exercises can be done at a distance from home but supervision is offered during specific hours day-time.