  The quantum annealing machine manufactured by D-Wave Systems is expected to
find the optimal solution for QUBO (Quadratic Unconstrained Binary
Optimization) accurately and quickly. This would be useful in future
applications where real-time calculation is needed. One such application is
traffic signal optimization. Some studies use quantum annealing for this.
However, they are formulated in unrealistic settings, such as only crossroads
on the map. Therefore, we suggest a QUBO, which can deal with T-junctions and
multi-forked roads. To validate the efficiency of our approach, SUMO
(Simulation of Urban MObility) is used. This enables us to experiment with
geographic information data very close to the real world. We compared results
with those using the Gurobi Optimizer in the experiment to confirm that quantum
annealing can find a ground state. The results show that the quantum annealing
cannot find the ground state, but our model can reduce the time that vehicles
wait at a red light. It is also inferior to the Gurobi Optimizer in calculation
time. This seems to be due to the D-Wave machine's hardware limitations and
noise effects, such as ambient temperature. If these problems are solved, and
the number of qubits is increased, the use of quantum annealing is likely to be
superior in terms of the speed of calculating an optimal solution.
