Dynamic traffic assignment (DTA) research has advanced greatly in terms of deployability, computational feasibility, and representing complex temporal phenomena. There have also been substantial contributions regarding various aspects of stochasticity within DTA. However, there are persisting limitations in terms of approaches which are both computationally tractable and provide more detailed representation of stochastic aspects.
Application 4 explores the application of a novel Strategic User Equilibrium DTA (StrDTA) modelling framework, which captures the impact of users making a priori route choice decisions based on the knowledge of a range of possible demand scenarios (e.g., differing days or representative situations). The resulting stochastic DTA problem becomes complex due to the integration of multiple demand scenarios and the algorithmic adjustments necessary to find optimal paths. The proposed new solution approach was implemented, and a detailed case study for the Sydney Central Business District (CBD) network was conducted. Results demonstrate the importance of accounting for stochasticity in the routing algorithm rather than relying on assumptions of average values. Similarly to previous applications of the project, Application 4 not only focuses on delivering cutting-edge research but also targets existing practical modelling questions and provides insights especially valuable to practitioners active in the areas of both traffic modelling and transport planning