To solve the problems of poor path search direction, slow convergence speed, and easy to fall into local optimum in intelligent vehicle path planning, and improve the optimization ability of intelligent vehicle path planning, a path planning method based on improved fruit fly optimization algorithm was proposed. Firstly, the digital map required for path planning is modeled by grid method, and the objective function of path planning evaluation is constructed with the shortest path as the goal. Secondly, by improving the update method of the fruit fly position in the fruit fly optimization algorithm, an improved fruit fly algorithm is proposed, so as to avoid falling into the local optimum and obtain the optimal driving path of the intelligent vehicle. Finally, a comparative analysis with the other Four methods is carried out in simple and complex environments to verify the excellent performance of the proposed method. The experimental results show that the proposed method has good randomness and extensiveness, it is not easy to fall into local optimum, and has better optimization ability. It has good advantages in terms of performance and can obtain comprehensive optimal path planning performance.