Regional Traffic Signal Control Optimization Model based on Quantum Genetic Algorithm

Abstract

Abstract The paper proposes, for the first time in the field of optimizing regional traffic signals, a model based on a quantum genetic algorithm to solve the problem of traffic congestion at intersections under the existing infrastructure conditions. The model introduces four evaluation criteria: vehicle waiting time, standard deviation, collision percentage, and algorithm execution time. It conducts simulation experiments on three typical intersection types: cross intersections, roundabouts, and diamond intersections. A more optimal regional traffic signal control scheme is proposed. In order to verify the effectiveness of the scheme, a large number of subsequent simulation experiments are conducted. The results demonstrate that, compared to other traditional intelligent algorithms, the algorithm presented in this paper performs better at alleviating traffic congestion at intersections.