spatiotemporal graph networks
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AI-Driven Real-Time Traffic Monitoring and Intelligent Control System: A Unified Deep Learning Framework for Smart Urban Mobility Management
Abstract: Urban traffic congestion imposes staggering economic and environmental costs on modern cities, with the INRIX Global Traffic Scorecard estimating annual per-driver productivity losses exceeding $1,348 in major metropolitan areas. Conventional traffic management infrastructure—fixed-cycle signal controllers, manual surveillance, and threshold-based incident detection—is fundamentally ill-equipped to address the dynamic, non-linear complexity of contemporary urban vehicular flows. This paper introduces TrafficNet-DRL, a unified deep learning and deep reinforcement learning framework for real-time traffic …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 2, 2026 · pp. 24–33 Read article