Traffic control and management

Traffic control and management applies systems engineering principles to understand and regulate how vehicles move through road networks, spanning everything from the second-by-second behavior of individual cars to citywide flow patterns captured by tools like the macroscopic fundamental diagram. As roads grow more congested and transportation accounts for a substantial share of energy use and emissions, better control strategies—whether at traffic signals, on highways through platooning, or across fleets of connected and autonomous vehicles—carry real consequences for safety, efficiency, and environmental impact. A central challenge is coordinating vehicles that can now communicate with each other and with infrastructure, since cooperative adaptive cruise control and similar technologies promise smoother, safer traffic but require control algorithms that are robust to mixed fleets of human-driven and automated vehicles. Researchers are actively exploring how data-driven methods, including reinforcement learning, can replace or augment classical control laws that struggle to scale as network complexity and vehicle heterogeneity increase.

Works

62,860

Total citations

784,859

Keywords

Traffic FlowMicroscopic SimulationCooperative Adaptive Cruise ControlConnected VehiclesTraffic Signal ControlPlatooning