Low-complexity ramp metering for freeway congestion control via network utility maximization

In this paper, we present a novel framework for freeway ramp metering that is based on maximizing the aggregate utility of onramp flows. We show how solving the dual problem of maximizing the network utility via a gradient projection algorithm synthesizes a low-complexity control law that is simple enough to be implemented on real platforms, while being robust to measurement noises. Our control algorithm can be partially distributed at each time step, every onramp selects a traffic flow to maximize its own benefit, and the network adjusts unit traffic flow prices for different onramps. We provide theoretical guarantees on the convergence of our algorithm under mild technical assumptions. We further demonstrate the practicality of our method in an example where the state of the art controls fail (due to infeasibility) and introduce multiple interesting future directions.