With the development of transportation and logistics, higher requirements are put forward for the time complexity and accuracy of path planning algorithm. Aiming at this problem, this paper proposes an improved intelligent path selection algorithm based on grid map which uses the direction information to optimize the algorithm. Based on the direction information of the beginning and end positions in the original map, the weight matrix and direction weight vector are defined as the basis for the selection of the next grid in the path, and reward and punishment measures are taken to improve the convergence speed of the algorithm. In addition, the algorithm also takes the optimization measures of redundant grid to improve the performance of the algorithm. The effectiveness of the algorithm is verified by the simulation of a typical storage AVG problem model. Simulation results show that the time required for the path length to converge to the optimal solution can be reduced by more than 10% compared with A * algorithm and traditional Dijkstra algorithm. The proposed intelligent path selection algorithm has lower time complexity and higher optimization efficiency as well.