  Quadratic unconstrained binary optimization (QUBO) is the mathematical
formalism for phrasing and solving a class of optimization problems that are
combinatorial in nature. Due to their natural equivalence with the two
dimensional Ising model for ferromagnetism in statistical mechanics, problems
from the QUBO class can be solved on quantum annealing hardware. In this paper,
we report a QUBO formatting of the problem of optimal control of time-dependent
traffic signals on an artificial grid-structured road network so as to ease the
flow of traffic, and the use of D-Wave Systems' quantum annealer to solve it.
Since current-generation D-Wave annealers have a limited number of qubits and
limited inter-qubit connectivity, we adopt a hybrid (classical/quantum)
approach to this problem. As traffic flow is a continuous and evolving
phenomenon, we address this time-dependent problem by adopting a workflow to
generate and solve multiple problem instances periodically.
