This paper provides a review of transport model applications that not only provide a central
traffic forecast (or forecasts for a few scenarios), but also quantify the uncertainty in the traffic …

Uncertainties related to demand model system outputs is an important issue in travel
demand models. This paper focuses on uncertainties arisen from the fact that models are …

Traffic forecasts provide essential input for the appraisal of transport investment projects.
However, according to recent empirical evidence, long-term predictions are subject to high …

Traffic forecasters may find value in expressing the uncertainty of their forecasts as a range
of expected outcomes. Traditional methods for estimating such uncertainty windows rely on …

This paper deals with the accuracy of travel demand forecasts among Norwegian road
projects. We use data collected from tolled roads and toll free roads. The results reveal that …

Abstract Reasoning why uncertainty analysis will become important in years to come, this
paper reviews prior work on uncertainty analysis in travel demand forecasting. Different …

This paper presents results from the first statistically significant study of traffic forecasts in
transportation infrastructure projects. The sample used is the largest of its kind, covering 210 …

Evaluating uncertainty of traffic networks is very important. In order to assess the uncertainty
theoretically, we need an equilibrium model that can estimate probabilistic distributions of …

Over the past three years the credit rating agency Standard & Poor's has published a series
of reports reflecting on the performance of traffic forecasts. The original study concentrated …

In the last two decades, the growing need for short‐term prediction of traffic parameters
embedded in a real‐time intelligent transportation systems environment has led to the …