Transport is a sector of the society where the political goals often point in a direction different from the trend development. This is especially the case with the increasing transport demand and volumes that lead to increasing congestion and CO2 emissions. The users’ responses to policy initiatives and the derived impacts are difficult to forecast due to complex causal relationships. Traffic forecast models and socio-economic cost-benefit analyses are hence an important tool in the decision support, and they often make up an important part of the justification for new transport infrastructure projects.
The project analyzes and discusses forecast accuracy based on an extensive empirical study, refers this to an organizational context, and uses this for recommendations and guidelines for model use. This framework for model design and use will then be used as a context, within which models can be addressed with regards to uncertainties on cost estimates, traffic forecasts and cost-benefit analyses. The project is expected to have a major impact on Danish model and planning practices by reducing systematic model bias and by quantifying and reducing model uncertainties for decision support. The research is also expected to have similar international impacts.
The project includes the 5 leading Danish professors within the research area of model bias and uncertainties in transport planning, each of whom leads a sub-project. The Institute of Transport Economics (TØI) is included in the project to contribute with its research experience in the same area. Several international leading researchers are expected to be linked to the project, including the Nobel laureate in Economics Daniel Kahneman, US, and Professor David Banister, University of Oxford. The project will include 4 Ph.D.-studies and 1 post.doc.