A physics-inspired model integrates mass conservation and diffusion to enable interactive boundary and intersection controls that manage congestion in simulated networks of interconnected roads.
Traffic signal control based on reinforcement learning with graph convolutional neural nets
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Interactive Physics-Inspired Traffic Congestion Management
A physics-inspired model integrates mass conservation and diffusion to enable interactive boundary and intersection controls that manage congestion in simulated networks of interconnected roads.