  This paper develops a conservation-based approach to model traffic dynamics
and alleviate traffic congestion in a network of interconnected roads (NOIR).
We generate a NOIR by using the Simulation of Urban Mobility (SUMO) software
based on the real street map of Philadelphia Center City. The NOIR is then
represented by a directed graph with nodes identifying distinct streets in the
Center City area. By classifying the streets as inlets, outlets, and interior
nodes, the model predictive control (MPC) method is applied to alleviate the
network traffic congestion by optimizing the traffic inflow and outflow across
the boundary of the NOIR with consideration of the inner traffic dynamics as a
stochastic process. The proposed boundary control problem is defined as a
quadratic programming problem with constraints imposing the feasibility of
traffic coordination, and a cost function defined based on the traffic density
across the NOIR.
