Abstract: Aiming at the shortcomings of the sparrow search algorithm such as slow convergence speed and easy falling into local optimum, this paper proposes an improved sparrow search algorithm. Firstly, the ICMIC chaotic mapping function is used to initialize the population and improve the diversity of the population so as to enhance the ability of the sparrow population to explore in unknown environments. Secondly, the position update formula of the sparrow algorithm is modified and optimized to improve its convergence speed. Finally, three different grid maps are designed, and the improved sparrow search algorithm and the original algorithm are compared in this map for path planning to verify the performance of the improved sparrow search algorithm. The experimental results show that the improved sparrow search algorithm has better performance in intelligent vehicle path planning, with faster convergence speed and better optimization ability.