The present invention relates to an electric taxi charging station planning method based on an adaptive quantum genetic algorithm. The method comprises the steps of (1) initializing basic data needed by planning, and estimating the value range of a charging station number, (2) randomly generating a chromosome corresponding formula, and forming a population, (3) carrying out solution space transformation and mapping a randomly generated angular space to a charging station address coordinate space, (4) using a Voronoi diagram to divide the service range of a charging station corresponding to chromosome, (5) calculating the average waiting time in queue of each charging station based on the charging requirement in the service range, (6) planning the expression of total society whole year total cost target function minimization according to electric taxi charging stations, (7) carrying out a quantum rotation gate updating operation and a quantum bit variation operation, (8) returning to the step (3) to carry out loop calculation until a convergence condition is satisfied. The method has the advantages that the optimized layout of charging station site is realized, the influence on the planning by taxi distribution, passenger demand distribution, and a road network structure can be reflected, and the method is effective and practical.