Dynamic traffic flow and route choice modelling represent a vibrant research area that examines how travellers adjust their selected paths over time amid complex transport networks. By integrating ...
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 ...
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