Dynamic traffic assignment (DTA) models are integral to modern transportation research, offering frameworks to predict and optimise the flow of vehicles over time within complex networks. These models ...

Traffic flow modelling and dynamics are at the forefront of efforts to understand and optimise urban transport systems. The field integrates theoretical and computational approaches to depict and ...

The MARL-OD-DA framework redesigns multi-agent reinforcement learning by using OD-pair–level agents and Dirichlet-based continuous routing actions, enabling scalable and stable traffic assignment in ...

This paper presents the development of a macroscopic dynamic traffic assignment model for continuum transportation systems with elastic demand. A reactive dynamic user equilibrium model is extended to ...