  A macroscopic model is proposed to depict the traffic dynamics involved in
urban traffic systems. The link dynamics are described based on the
cell-transmission model and bounded by the link capacities, while the flow
dynamics are proposed based on the discharge headways and saturation flow at
intersections. To fulfill the requirement of a closed-loop traffic light
control strategy, an approach to estimate the branching ratios at intersections
is proposed and simulations show that the convergence would be achieved under
constant cyclic flow profiles. Furthermore, a system partitioning approach is
proposed based congestion level identification, which is achieved via a machine
learning method and a hybrid traffic network control strategy is proposed to
integrate different traffic light control schemes together.
