Due to the fact that infrastructure supply cannot keep up with the increasing mobility and travel demand, traffic congestion plays an important role in every day life. The objective of most traffic research is to improve current and future levels of service and the quality of travel. Transport policy analysts need tools such as a traffic assignment model that enable making forecasts about future traffic conditions on transportation networks, compare scenarios of different infrastructure investments, or estimate effects of traffic management measures. A traffic assignment model predicts route choice, network flows, link travel times and route travel costs on a given transportation network with a given travel demand. Dynamic assignment models take time dependencies explicitly into account. Given the inherent dynamic nature of traffic, these models are superior to static models. Many dynamic traffic assignment (DTA) models have been proposed in the literature, but most of them either lack a sound analytical problem formulation or do not produce realistic outcomes. In this thesis an analytical DTA model is proposed in which traffic is considered to be heterogeneous, instead of assuming - as about all other analytical models do - that all network users are identical. (A)
Samenvatting