  This paper offers a finite-state abstraction of traffic coordination and
congestion in a network of interconnected roads (NOIR). By applying mass
conservation, we model traffic coordination as a Markov process. Model
Predictive Control (MPC) is applied to control traffic congestion through the
boundary of the traffic network. The optimal boundary inflow is assigned as the
solution of a constrained quadratic programming problem. Additionally, the
movement phases commanded by traffic signals are determined using receding
horizon optimization. In simulation, we show how traffic congestion can be
successfully controlled through optimizing boundary inflow and movement phases
at traffic network junctions.
