Congestion in automated warehouses directly erodes throughput and increases fulfillment cost. When AGVs block each other in narrow aisles or cluster at high-traffic intersections, travel time spikes, robot utilization drops, and urgent orders miss carrier cutoffs. This operational bottleneck stems from static routing logic that cannot adapt to real-time material flow, sensor events, or shifting priorities. A custom multi-agent traffic management system solves this by modeling the warehouse as a dynamic graph, where each lane and intersection is a node with continuously updated occupancy and cost.




