Vehicle Path Planning Based on Gradient Statistical Mutation Quantum Genetic Algorithm

In the field of vehicle path planning, traditional intelligent optimization algorithms have disadvantages slow convergence, poor stability and a tendency to fall into local extremes. Therefore, gradient statistical mutation quantum genetic algorithm (GSM-QGA) is proposed. Based on dynamic rotation angle adjustment by chromosome fitness value, gate strategy improved introducing idea descent. According properties chromosomal change trends, gradient-based operator designed realize operation. The shortest used as metric build planning model, effectiveness modified in demonstrated simulation experiments. Compared with other algorithms, length planned shorter search better. can be effectively controlled optimums.