Application of Quantum Genetic Algorithms to Network Signal Setting Design

The regulation of traffic lights in a signalised urban network requires optimizing objective functions that represent performance indicators of one or more intersections (such as delay or queue length). In this scenario, evolutionary algorithms are adopted to find suitable approximate solutions, in cases when no deterministic algorithm for finding the exact solution is known. This paper attempts to further improve the performance of evolutionary approaches by using a hybrid quantum-classical genetic algorithm to find the optimal configuration of the green signal timing regulating the traffic flow across two interacting junctions. The adopted algorithm, run on IBM quantum computer simulators, is shown to be suitable for the optimization problem at hand. Indeed, the experimental results highlight some of the strengths of the proposed technique with respect to the purely evolutionary approach, and encourage the application of this approach to more complex and close-to-real application scenarios.