Optimizing Traffic Flow Using Quantum Annealing

This paper investigates the use of quantum annealing for optimizing traffic flow, serving as a case study for broader applications in network optimization tasks. We start by modeling the traffic network as a quantum system, where intersections, roads, and traffic parameters are represented as qubits within a quantum annealing framework. The optimization process is outlined, illustrating how the quantum system evolves to identify low-energy states that correspond to optimal traffic flow configurations. By harnessing the unique properties of quantum mechanics, such as superposition and quantum tunneling, quantum annealing has the potential to efficiently explore extensive solution spaces beyond the capabilities of classical algorithms. This research aims to expand the understanding of how quantum computing can be applied to complex network optimization challenges, providing insights that could lead to more efficient, responsive, and sustainable management systems across various domains.