In this paper, we solved nonlinear problems in the traffic path planning with the hybrid GA-BP neural network algorithm. Although Back-Propagation neural network (BP) is able to solve nonlinear problems properly, it is tend to fall into the deficiency of local minimum. In the meanwhile, genetic algorithm (GA) is good at macro-searching and performs well at global optimization, which can make up for the deficiencies of BP. In this paper, using the A^* algorithm, we rough calculated several alternative paths quickly, which serve as the initial population of the GA. Then we conducted path planning precisely with the mixed GA-BP neural network algorithm. The simulation results showed that the hybrid GA-BP neural network algorithm has some advantages in the global optimal solution for path planning.