  Quantum annealing technologies aim to solve computational optimization and
sampling problems. QPU (Quantum Processing Unit) machines such as the D-Wave
system use the QUBO (Quadratic Unconstrained Binary Optimization) formula to
define model optimization problems for quantum annealing. This machine uses
quantum effects to speed up computing time better than classical computers. We
propose a vehicle routing problem that can be formulated in the QUBO model as a
combinatorial problem, which gives the possible route solutions increases
exponentially. The solution aims to optimize the vehicle's journey to reach a
destination. The study presents a QUBO formulation to solve traffic congestion
problems on certain roads. The resulting route selection by optimizing the
distribution of the flow of alternative road vehicles based on the weighting of
road segments. Constraints formulated as a condition for the level of road
density. The road weight parameter influences the cost function for each road
choice. The simulations on the D-Wave quantum annealer show optimal results on
the route deployment of several vehicles. So that each vehicle will be able to
go through different road options and reduce road congestion accurately. This
solution provides an opportunity to develop QUBO modeling for more complex
vehicle routing problems for road congestion.
