Dynamic Traffic Assignment (DTA) encompasses a class of models designed to represent and predict time‐dependent traffic flows in road networks, capturing the evolution of congestion, queue formation ...

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 ...

Traffic assignment and network equilibrium optimization form the theoretical and computational backbone of modern transportation planning, guiding the allocation of travel demand across a network of ...

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Most of the researches concentrated their efforts on power-aware networking under the non-bundled link scenarios by leveraging the dynamic power management based Low Power Idle (LPI) policy which was ...