Traffic Allocation

Traffic allocation optimizes the distribution of traffic flow across various transportation networks and systems, aiming to improve efficiency, reduce congestion, and enhance overall performance. Current research focuses on developing sophisticated models, including deep reinforcement learning frameworks, graph convolutional networks, and convolutional neural networks, to predict traffic demand, allocate resources (e.g., vehicles, ambulances), and dynamically adjust traffic routing in real-time. These advancements have significant implications for improving transportation management, optimizing resource utilization in e-commerce and ride-sharing services, and enhancing the safety and efficiency of road infrastructure maintenance.