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 individual car-following behavior captured in microscopic simulation to city-scale flow patterns described by the macroscopic fundamental diagram. As connected vehicles and cooperative adaptive cruise control enable cars to share real-time data with each other and with infrastructure, researchers are developing new signal control strategies and platooning algorithms that can reduce congestion, fuel consumption, and collision risk simultaneously. A central open question is how to design control policies—increasingly using reinforcement learning—that remain robust when only a fraction of vehicles in the network are equipped with intelligent transportation systems hardware, a mixed-autonomy condition that will define the transition period for decades to come.

Works

64,991

Total citations

802,189

Keywords

Traffic FlowMicroscopic SimulationCooperative Adaptive Cruise ControlConnected VehiclesTraffic Signal ControlPlatooning