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Please be aware that this is a beta release. Beta means that the product may not be functionally or feature complete. At this early phase the product is not yet expected to fully meet the quality, ...

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 ...

The Tesla Model Y’s midcycle refresh brought significant enough changes to earn it a spot in our 2026 SUV of the Year competition. The full list of updates is extensive, but the highlights matter.

For solving assignment problems of staff, equipment and task in engineering support action, a 3-Dimensional assignment model is established, which contains staff skill level, equipment technique ...

Which 3D model site is the biggest? We used a different method to measure them. When one asks, “which is the biggest”, it depends on your measurement. Sometimes the biggest sites are measured by the ...

Modelling the traffic assignment problem (TAP) is essential to capture the travelers' behaviors and predict the flow distribution in transportation networks. This problem has been extensively studied ...

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 ...

Traffic assignment modelling and route choice analysis investigate how travellers select paths through a transportation network and how these decisions affect overall network performance. Central to ...

With the purpose to organize methodologies found in (recent) papers focusing on the development of genomic breed/population assignment tools, this review proposes to highlight good practice for the ...

ABSTRACT: Road traffic flow forecasting provides critical information for the operational management of road mobility challenges, and models are used to generate the forecast. This paper uses a random ...