Abstract
Road traffic congestion is an increasing problem in urban areas. Building new roads often attracts latent demand and turns parts of the city into building sites for several years. Policy measures that stimulate more effective use of the existing network, such as variable road pricing, are therefore becoming increasingly popular among policy makers and citizens. These measures are often aimed at changing the temporal distribution of traffic. Yet transportation models taking departure time choice into account are rare. This paper describes the implementation of an urban transportation application for Stockholm, which includes departure time choice, mode choice and time dependent network assignment. Through iterations between demand and supply the objective of the transportation model is to forecast effects of congestion charges, intelligent transport systems and infrastructure investments on departure time choice. The complexity of large-scale departure time choice modelling and dynamic traffic assignment is high, which results in very long run times. Therefore, research on how to increase model efficiency is needed. This paper describes choices made in the implementation for a more efficient model.
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